You searched for subject:(Process optimization).
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687 total matches.
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University of Waterloo
1.
Ali Yusuf, Yusuf.
Green Petroleum Refining - Mathematical Models for Optimizing Petroleum Refining Under Emission Constraints.
Degree: 2013, University of Waterloo
URL: http://hdl.handle.net/10012/7860 
► Petroleum refining processes provide the daily requirements of energy for the global market. Each refining process produces wastes that have the capacity to harm the…
(more)
▼ Petroleum refining processes provide the daily requirements of energy for the global market. Each refining process produces wastes that have the capacity to harm the environment if not properly disposed of. The treatment of refinery waste is one of the most complex issues faced by refinery managers. Also, the hazardous nature of these wastes makes them rather costly to dispose of for the refineries. In this thesis, system analysis tools are used to design a program that allows for the selection of the optimal control, minimization and treating options for petroleum refinery waste streams. The performance of the developed model is demonstrated via a case study. Optimal mitigation alternatives to meet the emission reduction targets were studied by evaluating their relative impact on the profitable operation of the given facility. It was found that the optimal mitigation steps was to reduce emission precursors by conducting feed switches at the refinery. In all cases, the optimal solution did not include a capital expansion of the emission control facilities and equipment.
Subjects/Keywords: Optimization Petroleum Refining; Process Optimization
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APA (6th Edition):
Ali Yusuf, Y. (2013). Green Petroleum Refining - Mathematical Models for Optimizing Petroleum Refining Under Emission Constraints. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/7860
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Ali Yusuf, Yusuf. “Green Petroleum Refining - Mathematical Models for Optimizing Petroleum Refining Under Emission Constraints.” 2013. Thesis, University of Waterloo. Accessed February 28, 2021.
http://hdl.handle.net/10012/7860.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Ali Yusuf, Yusuf. “Green Petroleum Refining - Mathematical Models for Optimizing Petroleum Refining Under Emission Constraints.” 2013. Web. 28 Feb 2021.
Vancouver:
Ali Yusuf Y. Green Petroleum Refining - Mathematical Models for Optimizing Petroleum Refining Under Emission Constraints. [Internet] [Thesis]. University of Waterloo; 2013. [cited 2021 Feb 28].
Available from: http://hdl.handle.net/10012/7860.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Ali Yusuf Y. Green Petroleum Refining - Mathematical Models for Optimizing Petroleum Refining Under Emission Constraints. [Thesis]. University of Waterloo; 2013. Available from: http://hdl.handle.net/10012/7860
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Cornell University
2.
Toscano Palmerin, Saul.
Grey-Box Bayesian Optimization: Improving Performance by Looking Inside the Black-Box.
Degree: PhD, Operations Research and Information Engineering, 2020, Cornell University
URL: http://hdl.handle.net/1813/70478
► Non-convex time-consuming objectives are often optimized using “black-box” optimization. These approaches assume very little about the objective. While broadly applicable, these approaches typically require more…
(more)
▼ Non-convex time-consuming objectives are often optimized using “black-box”
optimization. These approaches assume very little about the objective. While broadly applicable, these approaches typically require more evaluations than methods exploiting more problem structure. In particular, often, we can acquire information about the objective function in ways other than direct evaluation, which is less time-consuming than evaluating the objective directly. This allows us to develop novel Bayesian
optimization algorithms that outperform methods that rely only objective function evaluations. In this thesis, we consider three problems:
optimization of sum and integrals of expensive-to-evaluate integrands; optimizing hyperparameters for iteratively trained supervised learning machine learning algorithms; and optimizing non-convex functions with a new efficient multistart stochastic gradient descent algorithm.
Advisors/Committee Members: Frazier, Peter (chair), Henderson, Shane (committee member), Bindel, David (committee member).
Subjects/Keywords: Bayesian optimization; black-box optimization; Gaussian process
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APA (6th Edition):
Toscano Palmerin, S. (2020). Grey-Box Bayesian Optimization: Improving Performance by Looking Inside the Black-Box. (Doctoral Dissertation). Cornell University. Retrieved from http://hdl.handle.net/1813/70478
Chicago Manual of Style (16th Edition):
Toscano Palmerin, Saul. “Grey-Box Bayesian Optimization: Improving Performance by Looking Inside the Black-Box.” 2020. Doctoral Dissertation, Cornell University. Accessed February 28, 2021.
http://hdl.handle.net/1813/70478.
MLA Handbook (7th Edition):
Toscano Palmerin, Saul. “Grey-Box Bayesian Optimization: Improving Performance by Looking Inside the Black-Box.” 2020. Web. 28 Feb 2021.
Vancouver:
Toscano Palmerin S. Grey-Box Bayesian Optimization: Improving Performance by Looking Inside the Black-Box. [Internet] [Doctoral dissertation]. Cornell University; 2020. [cited 2021 Feb 28].
Available from: http://hdl.handle.net/1813/70478.
Council of Science Editors:
Toscano Palmerin S. Grey-Box Bayesian Optimization: Improving Performance by Looking Inside the Black-Box. [Doctoral Dissertation]. Cornell University; 2020. Available from: http://hdl.handle.net/1813/70478
3.
Nie, Yisu.
Integration of Scheduling and Dynamic Optimization: Computational Strategies and Industrial Applications.
Degree: 2014, Carnegie Mellon University
URL: http://repository.cmu.edu/dissertations/380
► This thesis study focuses on the development of model-based optimization strategies for the integration of process scheduling and dynamic optimization, and applications of the integrated…
(more)
▼ This thesis study focuses on the development of model-based optimization strategies for the integration of process scheduling and dynamic optimization, and applications of the integrated approaches to industrial polymerization processes. The integrated decision making approaches seek to explore the synergy between production schedule design and process unit control to improve process performance. The integration problem has received much attention from both the academia and industry since the past decade. For scheduling, we adopt two formulation approaches based on the state equipment network and resource task network, respectively. For dynamic optimization, we rely on the simultaneous collocation strategy to discretize the differential-algebraic equations. Two integrated formulations are proposed that result in mixed discrete/dynamic models, and solution methods based on decomposition approaches are addressed. A class of ring-opening polymerization processes are used for our industrial case studies. We develop rigorous dynamic reactor models for both semi-batch homopolymerization and copolymerization operations. The reactor models are based on first-principles such as mass and heat balances, reaction kinetics and vapor-liquid equilibria. We derive reactor models with both the population balance method and method of moments. The obtained reactor models are validated using historical plant data. Polymerization recipes are optimized with dynamic optimization algorithms to reduce polymerization times by modifying operating conditions such as the reactor temperature and monomer feed rates over time. Next, we study scheduling methods that involve multiple process units and products. The resource task network scheduling model is reformulated to the state space form that offers a good platform for incorporating dynamic models. Lastly for the integration study, we investigate a process with two parallel polymerization reactors and downstream storage and purification units. The dynamic behaviors of the two reactors are coupled through shared cooling resources. We formulate the integration problem by combining the state space resource task network model with the moment reactor model. The case study results indicate promising improvements of process performances by applying dynamic optimization and scheduling optimization separately, and more importantly, the integration of the two.
Subjects/Keywords: process scheduling; dynamic optimization; process integration; polymerization
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APA (6th Edition):
Nie, Y. (2014). Integration of Scheduling and Dynamic Optimization: Computational Strategies and Industrial Applications. (Thesis). Carnegie Mellon University. Retrieved from http://repository.cmu.edu/dissertations/380
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Nie, Yisu. “Integration of Scheduling and Dynamic Optimization: Computational Strategies and Industrial Applications.” 2014. Thesis, Carnegie Mellon University. Accessed February 28, 2021.
http://repository.cmu.edu/dissertations/380.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Nie, Yisu. “Integration of Scheduling and Dynamic Optimization: Computational Strategies and Industrial Applications.” 2014. Web. 28 Feb 2021.
Vancouver:
Nie Y. Integration of Scheduling and Dynamic Optimization: Computational Strategies and Industrial Applications. [Internet] [Thesis]. Carnegie Mellon University; 2014. [cited 2021 Feb 28].
Available from: http://repository.cmu.edu/dissertations/380.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Nie Y. Integration of Scheduling and Dynamic Optimization: Computational Strategies and Industrial Applications. [Thesis]. Carnegie Mellon University; 2014. Available from: http://repository.cmu.edu/dissertations/380
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
4.
Vijayachitra S.
Studies on process modeling and optimization;.
Degree: Studies on process modeling and
optimization, 2015, Anna University
URL: http://shodhganga.inflibnet.ac.in/handle/10603/32160
► Many of the industrial processes are difficult to model because of newlinetheir complex behavior influential characteristics and operational conditions newlineMathematical models of industrial processes provide…
(more)
▼ Many of the industrial processes are difficult to
model because of newlinetheir complex behavior influential
characteristics and operational conditions newlineMathematical
models of industrial processes provide useful tools for the
newlinesimulation and control of system operation Many of the
kinetic models are newlineprohibitively complex often analytically
unsolvable and not routinely useful newlinefor control applications
Instead of conventional kinetic modeling fuzzy newlinetechnology is
also applied to develop an adaptive model for industrial
newlineprocesses There are numerous cases where fuzzy logic has
been successfully newlineapplied to modeling systems One of its
main advantages is that it provides an newlineunderstandable
knowledge representation newline newline newline
Reference p.114-122
Advisors/Committee Members: Tamilarasi A.
Subjects/Keywords: electrical engineering; optimization; process modeling
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APA (6th Edition):
S, V. (2015). Studies on process modeling and optimization;. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/32160
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
S, Vijayachitra. “Studies on process modeling and optimization;.” 2015. Thesis, Anna University. Accessed February 28, 2021.
http://shodhganga.inflibnet.ac.in/handle/10603/32160.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
S, Vijayachitra. “Studies on process modeling and optimization;.” 2015. Web. 28 Feb 2021.
Vancouver:
S V. Studies on process modeling and optimization;. [Internet] [Thesis]. Anna University; 2015. [cited 2021 Feb 28].
Available from: http://shodhganga.inflibnet.ac.in/handle/10603/32160.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
S V. Studies on process modeling and optimization;. [Thesis]. Anna University; 2015. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/32160
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
University of Texas – Austin
5.
Zhang, Chuwen, active 21st century.
Controlling work in process during semiconductor assembly and test operations.
Degree: MSin Engineering, Operations Research and Industrial Engineering, 2017, University of Texas – Austin
URL: http://hdl.handle.net/2152/62683
► In the semiconductor industry, products go through a series of steps over a three- to four-month period that begins with the fabrication of chips and…
(more)
▼ In the semiconductor industry, products go through a series of steps over a three- to four-month period that begins with the fabrication of chips and ends with assembly and test (AT) and shipment. This paper introduces a mid-term planning model for scheduling AT operations aimed at minimizing the difference between customer demand and product completions each day. A secondary objective is to maximize daily throughput. Typically, semiconductor companies have 1000s of products or devices in their catalog that can be organized into unique groups of up to 100 devices each. This simplifies the planning
process because it is only necessary to consider the groups as a whole rather than the individual devices when constructing schedules.
In all, we developed and tested three related models. Each provides daily run rates at each processing step or logpoint for each device group for up to one month at a time. The models are distinguished by how cycle time is treated. The first takes a steady-state approach and uses Little’s Law to formulate a WIP target constraint based on the average cycle time at each processing step. The second and third include integer and fractional cycle times in the variable definitions. To find solutions, raw production data are analyzed in a preprocessing step and then converted to input files in a standard format. FlopC++ from the COIN-OR open source software project is used to write and solve the model. Testing was done using three datasets from the Taiwan AT facility of a global semiconductor firm. By comparing model output with historical data for 6 device groups and 33 logpoints, we were able to realize decreases in shortages of up to 40% per month.
Advisors/Committee Members: Bard, Jonathan F. (advisor), Chacon, Rodolfo (committee member).
Subjects/Keywords: Semiconductor; Work-in-process; Optimization
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APA (6th Edition):
Zhang, Chuwen, a. 2. c. (2017). Controlling work in process during semiconductor assembly and test operations. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/62683
Chicago Manual of Style (16th Edition):
Zhang, Chuwen, active 21st century. “Controlling work in process during semiconductor assembly and test operations.” 2017. Masters Thesis, University of Texas – Austin. Accessed February 28, 2021.
http://hdl.handle.net/2152/62683.
MLA Handbook (7th Edition):
Zhang, Chuwen, active 21st century. “Controlling work in process during semiconductor assembly and test operations.” 2017. Web. 28 Feb 2021.
Vancouver:
Zhang, Chuwen a2c. Controlling work in process during semiconductor assembly and test operations. [Internet] [Masters thesis]. University of Texas – Austin; 2017. [cited 2021 Feb 28].
Available from: http://hdl.handle.net/2152/62683.
Council of Science Editors:
Zhang, Chuwen a2c. Controlling work in process during semiconductor assembly and test operations. [Masters Thesis]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/62683
University of Pretoria
6.
[No author].
Steam system network synthesis using process
integration
.
Degree: 2008, University of Pretoria
URL: http://upetd.up.ac.za/thesis/available/etd-08252008-165312/
► Steam boilers are used to generate steam in order to meet cold process heat requirements. The most common heat exchanger network layout associated with the…
(more)
▼ Steam boilers are used to generate steam in order to
meet cold
process heat requirements. The most common heat exchanger
network layout associated with the boiler is a completely parallel
design. This observation suggests that the flowrate of steam needed
for the system can be reduced, while maintaining the required duty,
simply by changing the layout of the network. Phase change of
saturated steam to saturated liquid plays a vital role in the
targeting method as well as the design of the network layout. A
hybrid graphical and mathematical technique for targeting and
network synthesis is presented. The main objective of the technique
is to reduce steam flowrate without compromising duty requirements
of the
process heat exchangers. In order to assess the advantage of
a hybrid technique, a case study is used where steam savings of
29.6% is obtained. A complete mathematical technique to demonstrate
the advantage of the graphical targeting concept in solution time
improvement is further presented.
Advisors/Committee Members: Prof T Majozi (advisor).
Subjects/Keywords: Process integration;
Optimization;
Synthesis;
Utility;
Milp;
UCTD
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APA ·
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APA (6th Edition):
author], [. (2008). Steam system network synthesis using process
integration
. (Masters Thesis). University of Pretoria. Retrieved from http://upetd.up.ac.za/thesis/available/etd-08252008-165312/
Chicago Manual of Style (16th Edition):
author], [No. “Steam system network synthesis using process
integration
.” 2008. Masters Thesis, University of Pretoria. Accessed February 28, 2021.
http://upetd.up.ac.za/thesis/available/etd-08252008-165312/.
MLA Handbook (7th Edition):
author], [No. “Steam system network synthesis using process
integration
.” 2008. Web. 28 Feb 2021.
Vancouver:
author] [. Steam system network synthesis using process
integration
. [Internet] [Masters thesis]. University of Pretoria; 2008. [cited 2021 Feb 28].
Available from: http://upetd.up.ac.za/thesis/available/etd-08252008-165312/.
Council of Science Editors:
author] [. Steam system network synthesis using process
integration
. [Masters Thesis]. University of Pretoria; 2008. Available from: http://upetd.up.ac.za/thesis/available/etd-08252008-165312/
University of Pretoria
7.
Coetzee, Willem Andries
Sternberg.
Steam system
network synthesis using process integration.
Degree: Chemical Engineering, 2008, University of Pretoria
URL: http://hdl.handle.net/2263/27531
► Steam boilers are used to generate steam in order to meet cold process heat requirements. The most common heat exchanger network layout associated with the…
(more)
▼ Steam boilers are used to generate steam in order to meet
cold
process heat requirements. The most common heat exchanger
network layout associated with the boiler is a completely parallel
design. This observation suggests that the flowrate of steam needed
for the system can be reduced, while maintaining the required duty,
simply by changing the layout of the network. Phase change of
saturated steam to saturated liquid plays a vital role in the
targeting method as well as the design of the network layout. A
hybrid graphical and mathematical technique for targeting and
network synthesis is presented. The main objective of the technique
is to reduce steam flowrate without compromising duty requirements
of the
process heat exchangers. In order to assess the advantage of
a hybrid technique, a case study is used where steam savings of
29.6% is obtained. A complete mathematical technique to demonstrate
the advantage of the graphical targeting concept in solution time
improvement is further presented.
Advisors/Committee Members: Prof T Majozi (advisor).
Subjects/Keywords: Process
integration;
Optimization;
Synthesis;
Utility;
Milp;
UCTD
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APA ·
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Manager
APA (6th Edition):
Coetzee, W. A. (2008). Steam system
network synthesis using process integration. (Masters Thesis). University of Pretoria. Retrieved from http://hdl.handle.net/2263/27531
Chicago Manual of Style (16th Edition):
Coetzee, Willem Andries. “Steam system
network synthesis using process integration.” 2008. Masters Thesis, University of Pretoria. Accessed February 28, 2021.
http://hdl.handle.net/2263/27531.
MLA Handbook (7th Edition):
Coetzee, Willem Andries. “Steam system
network synthesis using process integration.” 2008. Web. 28 Feb 2021.
Vancouver:
Coetzee WA. Steam system
network synthesis using process integration. [Internet] [Masters thesis]. University of Pretoria; 2008. [cited 2021 Feb 28].
Available from: http://hdl.handle.net/2263/27531.
Council of Science Editors:
Coetzee WA. Steam system
network synthesis using process integration. [Masters Thesis]. University of Pretoria; 2008. Available from: http://hdl.handle.net/2263/27531
8.
Vijayan S.
Process parameter optimization and Characterization of
friction stir Welding of aluminium alloy AA 5083;.
Degree: Process parameter optimization and Characterization of
friction stir Welding of aluminium alloy AA 5083, 2014, Anna University
URL: http://shodhganga.inflibnet.ac.in/handle/10603/30463
► AA 5083 is an Al Mg based alloy which possesses many newlineinteresting characteristics such as structural material moderately high newlinestrength good corrosion resistance and low…
(more)
▼ AA 5083 is an Al Mg based alloy which possesses
many newlineinteresting characteristics such as structural material
moderately high newlinestrength good corrosion resistance and low
price These advantages of the newlinealloy are quite attractive in
the automobile industries and marine applications
newlineConvectional welding processes are found inadequate in
welding aluminium newlinealloys because of their higher
conductivity hot cracking and high incidence of newlineporosity
Another important issue in welding aluminium magnesium alloys
newlineis the pronounced vaporization of alloying elements The
selective newlinevaporization of volatile alloying elements
especially magnesium causes a newlinemetal composition change in
the joint thus affecting the mechanical newlineproperties and the
corrosion resistance of the weld Laser welding and newlineFriction
Stir Welding FSW are the feasible solutions to overcome this
newlineproblem as lower heat input welding techniques newlineFSW is
a solid state welding process in which the process newlineparameter
plays a vital role in determining the output quality
characteristics of newlinethe weld The process parameter
optimization of FSW process enhances the newlinequality of the weld
further newline newline newline
reference p120-130.
Advisors/Committee Members: R. Raju.
Subjects/Keywords: Friction Stir Welding; process parameter optimization
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APA ·
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Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
S, V. (2014). Process parameter optimization and Characterization of
friction stir Welding of aluminium alloy AA 5083;. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/30463
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
S, Vijayan. “Process parameter optimization and Characterization of
friction stir Welding of aluminium alloy AA 5083;.” 2014. Thesis, Anna University. Accessed February 28, 2021.
http://shodhganga.inflibnet.ac.in/handle/10603/30463.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
S, Vijayan. “Process parameter optimization and Characterization of
friction stir Welding of aluminium alloy AA 5083;.” 2014. Web. 28 Feb 2021.
Vancouver:
S V. Process parameter optimization and Characterization of
friction stir Welding of aluminium alloy AA 5083;. [Internet] [Thesis]. Anna University; 2014. [cited 2021 Feb 28].
Available from: http://shodhganga.inflibnet.ac.in/handle/10603/30463.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
S V. Process parameter optimization and Characterization of
friction stir Welding of aluminium alloy AA 5083;. [Thesis]. Anna University; 2014. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/30463
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
9.
Munagalla, Prabhavathy.
Production and process optimization off recombinant human
erythropoiietin in serum free medium using r chinese hamster ovary
cells; -.
Degree: Biochemistry, 2011, Acharya Nagarjuna University
URL: http://shodhganga.inflibnet.ac.in/handle/10603/38968
None
Bibliography p.236 - 263 and Appendix p.265 -
288
Advisors/Committee Members: Rao, Sashiidhar B.Subjects/Keywords: optimization; process; Production
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APA (6th Edition):
Munagalla, P. (2011). Production and process optimization off recombinant human
erythropoiietin in serum free medium using r chinese hamster ovary
cells; -. (Thesis). Acharya Nagarjuna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/38968
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Munagalla, Prabhavathy. “Production and process optimization off recombinant human
erythropoiietin in serum free medium using r chinese hamster ovary
cells; -.” 2011. Thesis, Acharya Nagarjuna University. Accessed February 28, 2021.
http://shodhganga.inflibnet.ac.in/handle/10603/38968.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Munagalla, Prabhavathy. “Production and process optimization off recombinant human
erythropoiietin in serum free medium using r chinese hamster ovary
cells; -.” 2011. Web. 28 Feb 2021.
Vancouver:
Munagalla P. Production and process optimization off recombinant human
erythropoiietin in serum free medium using r chinese hamster ovary
cells; -. [Internet] [Thesis]. Acharya Nagarjuna University; 2011. [cited 2021 Feb 28].
Available from: http://shodhganga.inflibnet.ac.in/handle/10603/38968.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Munagalla P. Production and process optimization off recombinant human
erythropoiietin in serum free medium using r chinese hamster ovary
cells; -. [Thesis]. Acharya Nagarjuna University; 2011. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/38968
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Texas A&M University
10.
Roy, Nitin.
DEVELOPMENT AND APPLICATION OF PROCESS SAFETY INDICES IN EARLY DESIGN PHASE OF CHEMICAL SUPPLY CHAIN.
Degree: PhD, Chemical Engineering, 2018, Texas A&M University
URL: http://hdl.handle.net/1969.1/174090
► Supply chain network design and optimization are very important in decision making, which gives the ability to stakeholders to assess the massive supply chains to…
(more)
▼ Supply chain network design and
optimization are very important in decision making, which gives the ability to stakeholders to assess the massive supply chains to increase profit while minimizing risks. Risks in supply chains arise from various sources such as demand, supply and manufacturing. One of the significant sources is the supply chain disruptions caused by chemical and
process hazards during the transportation, manufacturing and storage of chemicals.
Process safety engineering is the study of hazards and risks in the chemical
process industry and deals with the prevention and mitigation of the risks. The concept of
process safety has grown exponentially during the last two decades.
Risk analysis techniques such as Hazard and Operability (HazOp) Analysis and Layer of Protection Analysis (LOPA) are well-established. However, they need large amounts of information that is not available during early design. Several quantitative and semi-quantitative safety indices such as Inherent Safety Index and Dow Fire and Explosion Index have been published which can be used at early design. But, there is a need for classification and critical analyses of these indices for correct usage. This study presents a critical discussion of published indices which includes classification into categories such as application industry, input type, and model aggregation; and lists advantages and disadvantages of each index. This will help researchers and engineers select correct safety index for their application.
Supply chain is a part of product life-cycle. Often, supply chain analysis overlooks the hazards at consumer level. Several of the products used every day such as propane grills, batteries, and spot removers are hazardous if not used properly. This study shows a systematic way of analyzing injuries due to hazardous consumer products. A brief introduction of propane supply chain is presented. NEISS database has been analyzed for consumer propane injuries and several recommendations have been derived for the consumer propane market. It was inferred that there is a lack of awareness of hazards of propane products at home, which result in high number of injuries to face due to flash burns.
Quantification of chemical and
process hazard is necessary in decision making and is one of the challenges faced by the chemical
process industry. Moreover, due to the complexities of the
process and limited understanding of the chemicals, the risk and hazards posed are uncertain in nature. This study develops a novel framework of holistically analyzing supply chain network design and
process safety. This work shows how the hazards in the supply chain drive the upper bounds on the flow for each entity in the supply chain. Secondly, the general supply chain formulation has been revised to integrate these bounds. The supply chain formulation described here is a non-linear mixed integer programming (MINLP) model with a case study in ammonia supply chain. The results show that in a chemical supply chain profit is an increasing function of hazard…
Advisors/Committee Members: Mannan, M Sam (advisor), Hasan, MM Faruque (advisor), El-Halwagi, Mahmoud (committee member), El-Jack, Fadwa (committee member), Butenko, Sergiy (committee member).
Subjects/Keywords: process safety index; supply chain optimization
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APA (6th Edition):
Roy, N. (2018). DEVELOPMENT AND APPLICATION OF PROCESS SAFETY INDICES IN EARLY DESIGN PHASE OF CHEMICAL SUPPLY CHAIN. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/174090
Chicago Manual of Style (16th Edition):
Roy, Nitin. “DEVELOPMENT AND APPLICATION OF PROCESS SAFETY INDICES IN EARLY DESIGN PHASE OF CHEMICAL SUPPLY CHAIN.” 2018. Doctoral Dissertation, Texas A&M University. Accessed February 28, 2021.
http://hdl.handle.net/1969.1/174090.
MLA Handbook (7th Edition):
Roy, Nitin. “DEVELOPMENT AND APPLICATION OF PROCESS SAFETY INDICES IN EARLY DESIGN PHASE OF CHEMICAL SUPPLY CHAIN.” 2018. Web. 28 Feb 2021.
Vancouver:
Roy N. DEVELOPMENT AND APPLICATION OF PROCESS SAFETY INDICES IN EARLY DESIGN PHASE OF CHEMICAL SUPPLY CHAIN. [Internet] [Doctoral dissertation]. Texas A&M University; 2018. [cited 2021 Feb 28].
Available from: http://hdl.handle.net/1969.1/174090.
Council of Science Editors:
Roy N. DEVELOPMENT AND APPLICATION OF PROCESS SAFETY INDICES IN EARLY DESIGN PHASE OF CHEMICAL SUPPLY CHAIN. [Doctoral Dissertation]. Texas A&M University; 2018. Available from: http://hdl.handle.net/1969.1/174090
Texas A&M University
11.
Bao, Buping.
Process Design and Optimization of Biorefining Pathways.
Degree: PhD, Chemical Engineering, 2012, Texas A&M University
URL: http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-10836
► Synthesis and screening of technology alternatives is a key process-development activity in the process industries. Recently, this has become particularly important for the conceptual design…
(more)
▼ Synthesis and screening of technology alternatives is a key
process-development activity in the
process industries. Recently, this has become particularly important for the conceptual design of biorefineries. A structural representation (referred to as the chemical species/conversion operator) is introduced. It is used to track individual chemicals while allowing for the processing of multiple chemicals in processing technologies. The representation is used to embed potential configurations of interest. An
optimization approach is developed to screen and determine optimum network configurations for various technology pathways using simple data.
The design of separation systems is an essential component in the design of biorefineries and hydrocarbon processing facilities. This work introduces methodical techniques for the synthesis and selection of separation networks. A shortcut method is developed for the separation of intermediates and products in biorefineries. The optimal allocation of conversion technologies and recycle design is determined in conjunction with the selection of the separation systems. The work also investigates the selection of separation systems for gas-to-liquid (GTL) technologies using supercritical Fischer-Tropsch synthesis. The task of the separation network is to exploit the pressure profile of the
process, the availability of the solvent as a
process product, and the techno-economic advantages of recovering and recycling the solvent. Case studies are solved to illustrate the effectiveness of the various techniques developed in this work.
The result shows 1, the optimal pathway based on minimum payback period for cost efficiency is pathway through alcohol fermentation and oligomerized to gasoline as 11.7 years with 1620 tonne/day of feedstock. When the capacity is increased to 120,000 BPD of gasoline production, the payback period will be reduced to 3.4 years. 2, from the proposed separation configuration, the solvent is recovered 99% from the FT products, while not affecting the heavier components recovery and light gas recovery, and 99% of waster is recycled. The SCF-FT case is competitive with the traditional FT case with similar ROI 0.2. 3, The proposed
process has comparable major parts cost with typical GTL
process and the capital investment per BPD is within the range of existing GTL plant.
Advisors/Committee Members: Elbashir, Nimir (advisor), El-Halwagi, Mahmoud (advisor), Mannan, M. Sam (committee member), Ehlig-Economides, Christine (committee member).
Subjects/Keywords: biorefinery; biofuel; optimization; process synthesis; integration
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APA (6th Edition):
Bao, B. (2012). Process Design and Optimization of Biorefining Pathways. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-10836
Chicago Manual of Style (16th Edition):
Bao, Buping. “Process Design and Optimization of Biorefining Pathways.” 2012. Doctoral Dissertation, Texas A&M University. Accessed February 28, 2021.
http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-10836.
MLA Handbook (7th Edition):
Bao, Buping. “Process Design and Optimization of Biorefining Pathways.” 2012. Web. 28 Feb 2021.
Vancouver:
Bao B. Process Design and Optimization of Biorefining Pathways. [Internet] [Doctoral dissertation]. Texas A&M University; 2012. [cited 2021 Feb 28].
Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-10836.
Council of Science Editors:
Bao B. Process Design and Optimization of Biorefining Pathways. [Doctoral Dissertation]. Texas A&M University; 2012. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-10836
12.
Washington, Ian D.
Large-Scale Dynamic Optimization Under Uncertainty using Parallel Computing.
Degree: PhD, 2016, McMaster University
URL: http://hdl.handle.net/11375/19092
► This research focuses on the development of a solution strategy for the optimization of large-scale dynamic systems under uncertainty. Uncertainty resides naturally within the external…
(more)
▼ This research focuses on the development of a solution strategy for the optimization of
large-scale dynamic systems under uncertainty. Uncertainty resides naturally within the
external forces posed to the system or from within the system itself. For example, in chemical
process systems, external inputs include flow rates, temperatures or compositions; while
internal sources include kinetic or mass transport parameters; and empirical parameters
used within thermodynamic correlations and expressions. The goal in devising a dynamic
optimization approach which explicitly accounts for uncertainty is to do so in a manner
which is computationally tractable and is general enough to handle various types and
sources of uncertainty. The approach developed in this thesis follows a so-called multiperiod
technique whereby the infinite dimensional uncertainty space is discretized at numerous
points (known as periods or scenarios) which creates different possible realizations of the
uncertain parameters. The resulting optimization formulation encompasses an approximated
expected value of a chosen objective functional subject to a dynamic model for all the
generated realizations of the uncertain parameters. The dynamic model can be solved,
using an appropriate numerical method, in an embedded manner for which the solution
is used to construct the optimization formulation constraints; or alternatively the model
could be completely discretized over the temporal domain and posed directly as part of the
optimization formulation.
Our approach in this thesis has mainly focused on the embedded model technique for
dynamic optimization which can either follow a single- or multiple-shooting solution method.
The first contribution of the thesis investigates a combined multiperiod multiple-shooting
dynamic optimization approach for the design of dynamic systems using ordinary differential
equation (ODE) or differential-algebraic equation (DAE) process models. A major aspect
of this approach is the analysis of the parallel solution of the embedded model within the
optimization formulation. As part of this analysis, we further consider the application of
the dynamic optimization approach to several design and operation applications. Another
vmajor contribution of the thesis is the development of a nonlinear programming (NLP) solver
based on an approach that combines sequential quadratic programming (SQP) with an
interior-point method (IPM) for the quadratic programming subproblem. A unique aspect of
the approach is that the inherent structure (and parallelism) of the multiperiod formulation
is exploited at the linear algebra level within the SQP-IPM nonlinear programming algorithm
using an explicit Schur-complement decomposition. Our NLP solution approach is further
assessed using several static and dynamic optimization benchmark examples.
Thesis
Doctor of Philosophy (PhD)
Advisors/Committee Members: Swartz, Christopher L.E., Chemical Engineering.
Subjects/Keywords: Dynamic Optimization; DAE process models; Parallel Computing
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APA (6th Edition):
Washington, I. D. (2016). Large-Scale Dynamic Optimization Under Uncertainty using Parallel Computing. (Doctoral Dissertation). McMaster University. Retrieved from http://hdl.handle.net/11375/19092
Chicago Manual of Style (16th Edition):
Washington, Ian D. “Large-Scale Dynamic Optimization Under Uncertainty using Parallel Computing.” 2016. Doctoral Dissertation, McMaster University. Accessed February 28, 2021.
http://hdl.handle.net/11375/19092.
MLA Handbook (7th Edition):
Washington, Ian D. “Large-Scale Dynamic Optimization Under Uncertainty using Parallel Computing.” 2016. Web. 28 Feb 2021.
Vancouver:
Washington ID. Large-Scale Dynamic Optimization Under Uncertainty using Parallel Computing. [Internet] [Doctoral dissertation]. McMaster University; 2016. [cited 2021 Feb 28].
Available from: http://hdl.handle.net/11375/19092.
Council of Science Editors:
Washington ID. Large-Scale Dynamic Optimization Under Uncertainty using Parallel Computing. [Doctoral Dissertation]. McMaster University; 2016. Available from: http://hdl.handle.net/11375/19092
Penn State University
13.
Hatim, Qais Yahya.
Integrating Sustainability in Manufacturing Process Planning.
Degree: 2015, Penn State University
URL: https://submit-etda.libraries.psu.edu/catalog/26369
► More recently, interest in designing products and manufacturing processes with major consideration given to the resources used and waste produced over the entirety of product/process…
(more)
▼ More recently, interest in designing products and manufacturing processes with major consideration given to the resources used and waste produced over the entirety of product/
process life cycle, viz. sustainable manufacturing has increased. Unlike design and manufacturing
process development activities that generally have access to a wealth of material information, sustainability assessment activities are generally made difficult by lack of a centralized source of information to incorporate sustainability knowledge into current manufacturing life cycle strategies. Even though considerable research has been accomplished in sustainable manufacturing domain, its application to real life problems is known to be in the early stages due to complexity in information representation, model compositions, system integrations, and computation. Moreover, isolated activities of
process planning within the gate-to-gate life cycle can lead to localized solutions in sustainability assessment. Integrating operation plans and
process plans provides globalized sustainable and productive solutions in the manufacturing gate-to-gate life cycle. This thesis, first, presents an attempt to understand these complexities for building material information model by addressing the requirements for defining a high-level material information model for sustainability that can capture this information across different life cycle stages as well as primary stakeholders. Second, the performance of job shop manufacturing is often related to diversified activities that impact sustainability and productivity.
Process and operation plans are particularly considered as the main activities that significantly impact different key performance indicators. The research proposed a systematic methodology for supporting manufacturing decision-making regarding sustainability and productivity assessment by integrating these plans.
In the first stage the different ways in which materials and material information influence the decision-making
process were analyzed. For this purpose information modeling techniques were employed to generate manufacturing scenarios. Activity models were generated and analyzed to collect and categorize key concepts towards constructing a Materials Information Model for Sustainability. The analysis helped in identifying locations where materials factor into the decision-making
process, the key information requirements that help build a material information model for sustainability. In the second stage of this research, a systematic methodology was developed for enabling the sustainability and productivity performance assessment for integrated
process and operation plans at the machine cell level of manufacturing systems. Selection of processes and operations is accomplished through building a Multi-Criteria-Decision-Making formulation. This formulation enables the combined assessment of sustainability and productivity in selecting the optimum
process and operation plans. Analytical Hierarchical
Process (AHP) is employed to address the…
Advisors/Committee Members: Christopher Saldana, Dissertation Advisor/Co-Advisor, Soundar Rajan Tirupatikumara, Committee Chair/Co-Chair, Lyle Norman Long, Committee Member, David R Riley Ii, Committee Member, Robert Carl Voigt, Committee Member, Sudarsan Rachuri, Special Member.
Subjects/Keywords: Sustainability; Process Planning; Simulation; Optimization; Methodology
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APA (6th Edition):
Hatim, Q. Y. (2015). Integrating Sustainability in Manufacturing Process Planning. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/26369
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Hatim, Qais Yahya. “Integrating Sustainability in Manufacturing Process Planning.” 2015. Thesis, Penn State University. Accessed February 28, 2021.
https://submit-etda.libraries.psu.edu/catalog/26369.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Hatim, Qais Yahya. “Integrating Sustainability in Manufacturing Process Planning.” 2015. Web. 28 Feb 2021.
Vancouver:
Hatim QY. Integrating Sustainability in Manufacturing Process Planning. [Internet] [Thesis]. Penn State University; 2015. [cited 2021 Feb 28].
Available from: https://submit-etda.libraries.psu.edu/catalog/26369.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Hatim QY. Integrating Sustainability in Manufacturing Process Planning. [Thesis]. Penn State University; 2015. Available from: https://submit-etda.libraries.psu.edu/catalog/26369
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
14.
Elsholkami, Mohamed.
Energy Management and Environmental Sustainability of the Canadian Oil Sands Industry.
Degree: 2018, University of Waterloo
URL: http://hdl.handle.net/10012/13081
► By 2030 the worldwide energy demand is expected to increase by twofold, in which fossil fuels inevitably will still play a major role in this…
(more)
▼ By 2030 the worldwide energy demand is expected to increase by twofold, in which fossil fuels inevitably will still play a major role in this transition. Canadian oil sands, the second largest proven oil reserves, represent a major pillar in providing energy and economic security in North America. Their development on a large scale is hindered due to associated environmental impacts, which include greenhouse gas emissions, water usage, and management of by-products of downstream operations (e.g. Sulfur, petroleum coke, etc.). In this work optimization techniques are employed to address the management of various environmental issues while minimizing the cost of operations of the oil sands industry. In this context, this thesis makes four principal contributions.
First, an extensive review is conducted on potential production pathways of renewable energy that can be integrated in the energy infrastructure of oil sands. Renewable technologies such as wind, geothermal, hydro, bioenergy, and solar are considered the most environmentally benign options for energy production that would contribute in achieving significant carbon emissions reductions. A mixed integer non-linear optimization model is developed to simultaneously optimize the capacity expansion and new investment decisions of both conventional and renewable energy technologies, and determine the optimal configurations of oil producers. The rolling horizon approach is used for the consecutive planning of multiple operational periods. To illustrate the applicability of the model, it was applied to a case study based on operational data for oil sands operators in Alberta for the period of 2010 – 2025.
Second, a generalized optimization model was developed for the energy planning of energy intensive industries. An extensive superstructure was developed that incorporates conventional, renewable, nuclear, and gasification of alternative fuels (e.g. petroleum coke, asphaltenes, etc.) technologies for the production of energy in the form of power, heat and hydrogen. Various carbon mitigation measures were incorporated, including carbon capture and sequestration, and purchase of carbon credits to satisfy emission targets. Finally, the superstructure incorporated the possibility of selling excess energy commodities in competitive markets. The superstructure is represented by a multi-period mixed integer optimization model with the objective of identifying the optimal set of energy supply technologies to satisfy a set of demands and emission targets at the minimum cost. Time-dependent parameters are incorporated in the model formulation, including energy demands, fuel prices, emission targets, carbon tax, construction lead time, etc. The model is applied to a case study based on the oil sands operations over the planning period 2015–2050. A scenario based approach is used to investigate the effect of variability in energy demand levels, various carbon mitigation policies, and variability in fuel and energy commodity prices.
Third, a multi-objective and multi-period…
Subjects/Keywords: Process systems engineering; Optimization; Oil sands; Sustainability
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APA (6th Edition):
Elsholkami, M. (2018). Energy Management and Environmental Sustainability of the Canadian Oil Sands Industry. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/13081
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Elsholkami, Mohamed. “Energy Management and Environmental Sustainability of the Canadian Oil Sands Industry.” 2018. Thesis, University of Waterloo. Accessed February 28, 2021.
http://hdl.handle.net/10012/13081.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Elsholkami, Mohamed. “Energy Management and Environmental Sustainability of the Canadian Oil Sands Industry.” 2018. Web. 28 Feb 2021.
Vancouver:
Elsholkami M. Energy Management and Environmental Sustainability of the Canadian Oil Sands Industry. [Internet] [Thesis]. University of Waterloo; 2018. [cited 2021 Feb 28].
Available from: http://hdl.handle.net/10012/13081.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Elsholkami M. Energy Management and Environmental Sustainability of the Canadian Oil Sands Industry. [Thesis]. University of Waterloo; 2018. Available from: http://hdl.handle.net/10012/13081
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
University of Toronto
15.
Tang, Tai Fung Stephen.
Optimizing Chemical Dosage in Municipal Wastewater Disinfection with Model-based Control.
Degree: 2015, University of Toronto
URL: http://hdl.handle.net/1807/77695
► This research thesis developed a feedforward model-based chemical dose control algorithm for municipal wastewater disinfection process and an algorithm to simulate unsteady stochastic process conditions…
(more)
▼ This research thesis developed a feedforward model-based chemical dose control algorithm for municipal wastewater disinfection process and an algorithm to simulate unsteady stochastic process conditions using steady state computational fluid dynamics particle tracks. The control algorithm and simulation model utilize mechanistic models that describe disinfectant decay, CT, and disinfection levels. CT is the product of the effluent disinfectant concentration and the process average residence time. The models are integrated into the particle tracks generated from the disinfection process simulation. By utilizing the mechanistic models and the particle tracks, the control algorithm and the simulation model predict and control the process disinfection performance. The control algorithm is a feedforward control that predicts the disinfection performance, and it is not affected by the long feedback signal dead time commonly found in municipal wastewater disinfection. This thesis has shown that the mode-based dose control algorithm has reduced the disinfectant consumption up to 17%.
M.A.S.
2017-06-30 00:00:00
Advisors/Committee Members: Lawryshyn, Yuri, Chemical Engineering Applied Chemistry.
Subjects/Keywords: CFD; Chemical; Disinfection; Optimization; Process; Wastewater; 0595
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APA (6th Edition):
Tang, T. F. S. (2015). Optimizing Chemical Dosage in Municipal Wastewater Disinfection with Model-based Control. (Masters Thesis). University of Toronto. Retrieved from http://hdl.handle.net/1807/77695
Chicago Manual of Style (16th Edition):
Tang, Tai Fung Stephen. “Optimizing Chemical Dosage in Municipal Wastewater Disinfection with Model-based Control.” 2015. Masters Thesis, University of Toronto. Accessed February 28, 2021.
http://hdl.handle.net/1807/77695.
MLA Handbook (7th Edition):
Tang, Tai Fung Stephen. “Optimizing Chemical Dosage in Municipal Wastewater Disinfection with Model-based Control.” 2015. Web. 28 Feb 2021.
Vancouver:
Tang TFS. Optimizing Chemical Dosage in Municipal Wastewater Disinfection with Model-based Control. [Internet] [Masters thesis]. University of Toronto; 2015. [cited 2021 Feb 28].
Available from: http://hdl.handle.net/1807/77695.
Council of Science Editors:
Tang TFS. Optimizing Chemical Dosage in Municipal Wastewater Disinfection with Model-based Control. [Masters Thesis]. University of Toronto; 2015. Available from: http://hdl.handle.net/1807/77695
University of Waikato
16.
Ma, Jinjin.
Parameter Tuning Using Gaussian Processes
.
Degree: 2012, University of Waikato
URL: http://hdl.handle.net/10289/6497
► Most machine learning algorithms require us to set up their parameter values before applying these algorithms to solve problems. Appropriate parameter settings will bring good…
(more)
▼ Most machine learning algorithms require us to set up their parameter values before applying these algorithms to solve problems. Appropriate parameter settings will bring good performance while inappropriate parameter settings generally result in poor modelling. Hence, it is necessary to acquire the “best” parameter values for a particular algorithm before building the model. The “best” model not only reflects the “real” function and is well fitted to existing points, but also gives good performance when making predictions for new points with previously unseen values.
A number of methods exist that have been proposed to optimize parameter values. The basic idea of all such methods is a trial-and-error
process whereas the work presented in this thesis employs Gaussian
process (GP) regression to optimize the parameter values of a given machine learning algorithm. In this thesis, we consider the
optimization of only two-parameter learning algorithms. All the possible parameter values are specified in a 2-dimensional grid in this work. To avoid brute-force search, Gaussian
Process Optimization (GPO) makes use of “expected improvement” to pick useful points rather than validating every point of the grid step by step. The point with the highest expected improvement is evaluated using cross-validation and the resulting data point is added to the training set for the Gaussian
process model. This
process is repeated until a stopping criterion is met. The final model is built using the learning algorithm based on the best parameter values identified in this
process.
In order to test the effectiveness of this
optimization method on regression and classification problems, we use it to optimize parameters of some well-known machine learning algorithms, such as decision tree learning, support vector machines and boosting with trees. Through the analysis of experimental results obtained on datasets from the UCI repository, we find that the GPO algorithm yields competitive performance compared with a brute-force approach, while exhibiting a distinct advantage in terms of training time and number of cross-validation runs. Overall, the GPO method is a promising method for the
optimization of parameter values in machine learning.
Advisors/Committee Members: Frank, Eibe (advisor), Holmes, Geoffrey (advisor).
Subjects/Keywords: Parameter Tunning;
Gaussian Process Optimization;
Machine Learning
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APA ·
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Manager
APA (6th Edition):
Ma, J. (2012). Parameter Tuning Using Gaussian Processes
. (Masters Thesis). University of Waikato. Retrieved from http://hdl.handle.net/10289/6497
Chicago Manual of Style (16th Edition):
Ma, Jinjin. “Parameter Tuning Using Gaussian Processes
.” 2012. Masters Thesis, University of Waikato. Accessed February 28, 2021.
http://hdl.handle.net/10289/6497.
MLA Handbook (7th Edition):
Ma, Jinjin. “Parameter Tuning Using Gaussian Processes
.” 2012. Web. 28 Feb 2021.
Vancouver:
Ma J. Parameter Tuning Using Gaussian Processes
. [Internet] [Masters thesis]. University of Waikato; 2012. [cited 2021 Feb 28].
Available from: http://hdl.handle.net/10289/6497.
Council of Science Editors:
Ma J. Parameter Tuning Using Gaussian Processes
. [Masters Thesis]. University of Waikato; 2012. Available from: http://hdl.handle.net/10289/6497
Siauliai University
17.
Armanavičienė,
Nastė; Armanavičius,
Juozas.
Valdymo procesų optimizavimas bendrastatybinių
darbų įmonėje.
Degree: Master, Marketing and
Administration, 2009, Siauliai University
URL: http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2009~D_20090828_131902-64156
;
► Magistro darbe yra suformuluotos bendrastatybinių įmonių valdymo problemos, išanalizuoti ir susisteminti įvairių Lietuvos ir užsienio autorių mokslinės literatūros šaltiniai apie organizacijų valdymo proceso esmę, valdymo…
(more)
▼ Magistro darbe yra suformuluotos
bendrastatybinių įmonių valdymo problemos, išanalizuoti ir
susisteminti įvairių Lietuvos ir užsienio autorių mokslinės
literatūros šaltiniai apie organizacijų valdymo proceso esmę,
valdymo teorijų taikymo praktinius aspektus. Darbe analizuojamos
„Izobara“ grupės įmonių valdymo probleminės sritys, išryškinti
atotrūkio ir tapatumo taškai tarp praktinės organizacijos veiklos
ir valdymo teorijų pagrindinių nuostatų, įmonių vadovų darbo
stiliai, numatomos valdymo optimizavimo kryptys. Patvirtinta
autorių suformuluota mokslinio tyrimo hipotezė, kad kompleksinis
valdymo teorijų teiginių įgyvendinimas praktinėje bendrastatybinės
įmonės veikloje didina organizacijos veiklos efektyvumą. Pateikiami
pasiūlymai dėl valdymo teorijų nuostatų efektyvesnio panaudojimo
organizacijų vadybinės veiklos kokybei
gerinti.
In master’s thesis the problems of the
management of joint – constructional companies are formulated,
different sources of nonfiction related to the essence of the
companies’ management process written by various Lithuanian and
foreign authors as well as to practical dimensions of the
application of management theories are analyzed and structured. In
the thesis the problematic fields of companies of the group
“Izobara” are analyzed, the points of gaps and identity between the
practical activity of organization and the main attitudes of the
management theories as well as the work style of the heads of
companies and the prospective directions of the management
optimization are highlighted. The hypotheses of the research
formulated by the authors are certified: it is supposed that the
companies of the group “Izobara” have the chance to optimize the
management in the structure, budget formation, introduction of
management standards and in clustering; the implementation of
affirmations of management theories in practical activity of the
joint – constructional company increases the effectiveness of the
organizational activity. The suggestions about more effective use
of provisions of the management theories in order to improve the
quality of the organizations’ managerial activity are
made.
Advisors/Committee Members: Žičkienė, Skaidrė (Master’s degree committee member), Garalis, Algirdas (Master’s thesis reviewer), Stoškus, Stasys (Master’s thesis supervisor), Merkys, Gediminas (Master’s degree committee chair), Pabedinskaitė, Arnoldina (Master’s degree committee member), Tijūnaitienė, Rigita (Master’s degree committee member), Stoškus, Stasys (Master’s degree committee member).
Subjects/Keywords: Valdymas; Procesas; Optimizavimas; Management; Process; Optimization
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Manager
APA (6th Edition):
Armanavičius,
Juozas, A
Nastė;. (2009). Valdymo procesų optimizavimas bendrastatybinių
darbų įmonėje. (Masters Thesis). Siauliai University. Retrieved from http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2009~D_20090828_131902-64156 ;
Chicago Manual of Style (16th Edition):
Armanavičius,
Juozas, Armanavičienė,
Nastė;. “Valdymo procesų optimizavimas bendrastatybinių
darbų įmonėje.” 2009. Masters Thesis, Siauliai University. Accessed February 28, 2021.
http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2009~D_20090828_131902-64156 ;.
MLA Handbook (7th Edition):
Armanavičius,
Juozas, Armanavičienė,
Nastė;. “Valdymo procesų optimizavimas bendrastatybinių
darbų įmonėje.” 2009. Web. 28 Feb 2021.
Vancouver:
Armanavičius,
Juozas A
Nastė;. Valdymo procesų optimizavimas bendrastatybinių
darbų įmonėje. [Internet] [Masters thesis]. Siauliai University; 2009. [cited 2021 Feb 28].
Available from: http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2009~D_20090828_131902-64156 ;.
Council of Science Editors:
Armanavičius,
Juozas A
Nastė;. Valdymo procesų optimizavimas bendrastatybinių
darbų įmonėje. [Masters Thesis]. Siauliai University; 2009. Available from: http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2009~D_20090828_131902-64156 ;
University of Ghana
18.
Oduro-Yeboah, C.
Process Optimization and Product Characteristics of White Kenkey (Nsiho)
.
Degree: 2015, University of Ghana
URL: http://ugspace.ug.edu.gh/handle/123456789/21477
► Kenkey, is a maize based sour, stiff dumpling, and it is among the most common fermented cereal food products in Ghana. There are several types…
(more)
▼ Kenkey, is a maize based sour, stiff dumpling, and it is among the most common fermented
cereal food products in Ghana. There are several types of kenkey, and while some are made
from whole maize grains others are produced using degermed/and dehulled maize grains.
The kenkey types made using dehulled maize grains are less popular and have largely
remained at the level of “ethnic food”, restricted to very few socio-cultural communities.
Current trends in urbanization, and the increasing popularity of kenkey among consumers,
require larger scale production with consistent quality. The study was carried out to
examine the traditional white kenkey
process and to optimize the key processing variables
in order to obtain reproducible quality white kenkey that will be acceptable to native and
non-native consumers.
A survey was conducted in three white kenkey production districts to collate information
on production, vending and consumption practices. The sensory profile and consumer
acceptance of different types of kenkey and other fermented maize products in Ghana were
investigated. A total of two hundred consumers including 110 Ghanaians and 90
internationals were used for the consumer test. Traditional white kenkey types were
analyzed for their physicochemical, textural, microstructure and sensory characteristics.
Physicochemical analysis involved determination of pH, titratable acidity, sugars, lactic
acids, minerals, vitamins and amino acids using high performance liquid chromatography
procedures. The textural characteristics of white kenkey randomly obtained from traditional
processors were determined using instrumental (texture analyser) and consumer
assessments.
The effects of processing variables of steeping time (12, 30 and 48 h) and dough
fermentation time (0, 12 and 24 h) on the physicochemical properties of white kenkey were determined. A (three variable) Box-Behnken design was used to optimize the processing
variables of steeping time, steeping temperature, and fermentation time on white kenkey
quality parameters of moisture, pH, titratable acidity, glucose and lactic acid content. The
optimum region of the
process variables was obtained by hedonic tests on the white kenkey
using balanced incomplete block design (for k= 5, b= 21, λ=2, r =7)
Quantitative Descriptive Analysis (QDA) was conducted on white kenkey made from
within and outside the optimum region of the
process variables, as well as white kenkey
obtained from vendors using a panel of 18 trained members. Consumer acceptance study
was conducted using 65 consumers for white kenkey obtained from the optimum region
and traditionally processed white kenkey obtained from vendors.
The results of the survey showed that there were two main types of white kenkey, nonsweetened
white kenkey and sweetened white kenkey to which sugar is added during
production. All three procedures involved steeping of dehulled maize grains which is then
milled into a meal. In the (procedure at Atimpoku), the meal was not fermented any
further but…
Advisors/Committee Members: Saalia, F.K (advisor), Amoa-Awua, W (advisor), Mestres, C (advisor), Sakyi-Dawson, E (advisor).
Subjects/Keywords: Process Optimization;
Product Characteristics;
White Kenkey (Nsiho)
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Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Oduro-Yeboah, C. (2015). Process Optimization and Product Characteristics of White Kenkey (Nsiho)
. (Doctoral Dissertation). University of Ghana. Retrieved from http://ugspace.ug.edu.gh/handle/123456789/21477
Chicago Manual of Style (16th Edition):
Oduro-Yeboah, C. “Process Optimization and Product Characteristics of White Kenkey (Nsiho)
.” 2015. Doctoral Dissertation, University of Ghana. Accessed February 28, 2021.
http://ugspace.ug.edu.gh/handle/123456789/21477.
MLA Handbook (7th Edition):
Oduro-Yeboah, C. “Process Optimization and Product Characteristics of White Kenkey (Nsiho)
.” 2015. Web. 28 Feb 2021.
Vancouver:
Oduro-Yeboah C. Process Optimization and Product Characteristics of White Kenkey (Nsiho)
. [Internet] [Doctoral dissertation]. University of Ghana; 2015. [cited 2021 Feb 28].
Available from: http://ugspace.ug.edu.gh/handle/123456789/21477.
Council of Science Editors:
Oduro-Yeboah C. Process Optimization and Product Characteristics of White Kenkey (Nsiho)
. [Doctoral Dissertation]. University of Ghana; 2015. Available from: http://ugspace.ug.edu.gh/handle/123456789/21477
Delft University of Technology
19.
Turan, Taylan (author).
Reduced Order Model Base Creation with Bayesian Optimization.
Degree: 2020, Delft University of Technology
URL: http://resolver.tudelft.nl/uuid:972caf56-3621-414b-a582-2561e2a5ff54
► This research considers the offline training stage of the Reduced Order Models (ROM), that has been getting attention recently on the endeavor to come up…
(more)
▼ This research considers the offline training stage of the Reduced Order Models (ROM), that has been getting attention recently on the endeavor to come up with efficient solutions for the highly complex numerical models. In this work, a simply supported beam problem has been considered, for which a reduced basis creation has been investigated. Reduced basis creation is in utmost importance for the accuracy and reliability of the ROM. Main focus is on the efficient parameter sampling strategies to enrich the reduced basis, which brings forth computational burden. To decrease this burden, a statistical tool Gaussian Processes Regression (GPR) based Bayesian
Optimization (BO) is utilized. These tools are used to create a surrogate function of error indicator that is used to select additional training points for ROM. Results of this work show that randomness in the proposed procedure influences parameter sampling but does not have an impact on the overall accuracy. Finally, this work suggests further work on creation of a stopping criteria and finding a method of storing previous information and combining it with current information regarding training points without losing information. With the help of proposed further research topics, this work intends to be used as a foundation for efficient reduced basis construction.
Advisors/Committee Members: van der Meer, Frans (mentor), Rocha, I.B.C.M. (graduation committee), Bessa, Miguel (graduation committee), Delft University of Technology (degree granting institution).
Subjects/Keywords: Bayesian Optimization; Reduced Order Model; Gaussian Process
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APA ·
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to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Turan, T. (. (2020). Reduced Order Model Base Creation with Bayesian Optimization. (Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:972caf56-3621-414b-a582-2561e2a5ff54
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Turan, Taylan (author). “Reduced Order Model Base Creation with Bayesian Optimization.” 2020. Thesis, Delft University of Technology. Accessed February 28, 2021.
http://resolver.tudelft.nl/uuid:972caf56-3621-414b-a582-2561e2a5ff54.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Turan, Taylan (author). “Reduced Order Model Base Creation with Bayesian Optimization.” 2020. Web. 28 Feb 2021.
Vancouver:
Turan T(. Reduced Order Model Base Creation with Bayesian Optimization. [Internet] [Thesis]. Delft University of Technology; 2020. [cited 2021 Feb 28].
Available from: http://resolver.tudelft.nl/uuid:972caf56-3621-414b-a582-2561e2a5ff54.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Turan T(. Reduced Order Model Base Creation with Bayesian Optimization. [Thesis]. Delft University of Technology; 2020. Available from: http://resolver.tudelft.nl/uuid:972caf56-3621-414b-a582-2561e2a5ff54
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
University of Ontario Institute of Technology
20.
Bender, Dylan J.
Integrated topology optimization design and process planning for additive manufacturing.
Degree: 2019, University of Ontario Institute of Technology
URL: http://hdl.handle.net/10155/1081
► Industry 4.0 demands that the systems and processes in today???s product design and manufacturing not just be automated, but to be robust and containing many…
(more)
▼ Industry 4.0 demands that the systems and processes in today???s product design and manufacturing not just be automated, but to be robust and containing many feedback mechanisms which enables it to be self-correcting. The hypothetical upcoming Industry 5.0 promises on demand and personalized products which this thesis aims to take a step in the direction of. It is proposed that an integrated and optimized
process for structural topology
optimization and subsequent additive manufacturing is possible for automated design and manufacturing starting from its problem definition. An improvement on the benchmarked topology
optimization methods is shown which allows the user control over the
optimization???s convergence characteristics which is then further studied to find a robust set of
optimization parameters. The resulting topology of the structure is then analyzed for its optimal printing orientation based on a custom-made algorithm which minimizes manufacturing costs. Furthermore, the structure is then sliced for instruction generation of layer-based manufacturing techniques in a novel fashion which also serves to provide feedback of the manufacturing
process planning to the topology
optimization design stage.
Advisors/Committee Members: Barari, Ahmad.
Subjects/Keywords: Topology optimization; Additive manufacturing; Process planning
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APA ·
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CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Bender, D. J. (2019). Integrated topology optimization design and process planning for additive manufacturing. (Thesis). University of Ontario Institute of Technology. Retrieved from http://hdl.handle.net/10155/1081
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Bender, Dylan J. “Integrated topology optimization design and process planning for additive manufacturing.” 2019. Thesis, University of Ontario Institute of Technology. Accessed February 28, 2021.
http://hdl.handle.net/10155/1081.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Bender, Dylan J. “Integrated topology optimization design and process planning for additive manufacturing.” 2019. Web. 28 Feb 2021.
Vancouver:
Bender DJ. Integrated topology optimization design and process planning for additive manufacturing. [Internet] [Thesis]. University of Ontario Institute of Technology; 2019. [cited 2021 Feb 28].
Available from: http://hdl.handle.net/10155/1081.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Bender DJ. Integrated topology optimization design and process planning for additive manufacturing. [Thesis]. University of Ontario Institute of Technology; 2019. Available from: http://hdl.handle.net/10155/1081
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
University of Arizona
21.
Sharma, Yashika.
Machine Learning and Additive Manufacturing Based Antenna Design Techniques
.
Degree: 2020, University of Arizona
URL: http://hdl.handle.net/10150/637723
► This dissertation investigates the application of machine learning (ML) techniques to additive manufacturing (AM) technology with the ultimate goal of tackling the universal antenna design…
(more)
▼ This dissertation investigates the application of machine learning (ML) techniques to additive manufacturing (AM) technology with the ultimate goal of tackling the universal antenna design challenges and achieving automated antenna design for a broad range of applications.
First, we investigate the implementation and accuracy of few modern machine learning techniques including, least absolute shrinkage and selection operator (lasso), artificial neural networks (ANN) and k-nearest neighbor (kNN) methods, for antenna design
optimization for antennas. The automated techniques provide an efficient, flexible, and reliable framework to identify optimal design parameters for a reference dual-band double T-shaped monopole antenna to achieve favorite performance in terms of its dual bandwidth. We first provide a brief background for these techniques and then explain how these techniques can be used to optimize the performance of the referenced antenna. Then the accuracy of these techniques is tested by doing a comparative analysis with HFSS simulations as well.
After obtaining encouraging results from the primitive work mentioned above, we implement ML techniques for the
optimization of a more complex 3D-printed slotted waveguide antenna. The design has more design parameters that are be tuned and, also multiple performance parameters, including bandwidth, realized gain, sidelobe level, and back lobe level, are optimized. This is a higher-dimensional and non-linear problem. Hence, we use an artificial neural network for this work.
Next, we demonstrate the advantages and challenges of using ML techniques compared to heuristic
optimization techniques. We apply ML techniques first for ‘modeling’ that refers to prediction of the performance curve (e.g., reflection coefficient w.r.t. frequency, gain plots in a given plane, etc.) for a given design of antenna with particular set of design parameters and then use it for obtaining ‘optimization’ results that refers to searching the value of the design parameters that can give optimized results for a particular goal (e.g., specific frequency band of operation, maximum gain, minimum sidelobe level, etc.). To explain modeling using ML-techniques, we use two antenna examples in this work, first is the modeling of the reflection coefficient curve with respect to frequency for a planar patch antenna when its shape changes from square to circular and second is the modeling of gain response of a monopole antenna when it is loaded with 3D-printed dielectric material. To explain the
optimization process, we use the behavioral model obtained in the second antenna example, and find the design parameter values that are capable of providing single-beam, and multiple-beam radiation. The performance of ML is compared with a heuristic technique like genetic algorithm for this work and the benefits of using ML over GA are mentioned in this work. One of the prototypes that can provide a 3-beam radiation pattern is manufactured and its fabrication
process and measurement results are also presented in…
Advisors/Committee Members: Xin, Hao (advisor), Dvorak, Steven L. (committeemember), Roveda, Janet Meiling (committeemember), Zhang, Hao Helen (committeemember).
Subjects/Keywords: Antenna;
Gaussian Process;
lasso;
Machine Learning;
Optimization
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APA ·
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MLA ·
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CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Sharma, Y. (2020). Machine Learning and Additive Manufacturing Based Antenna Design Techniques
. (Doctoral Dissertation). University of Arizona. Retrieved from http://hdl.handle.net/10150/637723
Chicago Manual of Style (16th Edition):
Sharma, Yashika. “Machine Learning and Additive Manufacturing Based Antenna Design Techniques
.” 2020. Doctoral Dissertation, University of Arizona. Accessed February 28, 2021.
http://hdl.handle.net/10150/637723.
MLA Handbook (7th Edition):
Sharma, Yashika. “Machine Learning and Additive Manufacturing Based Antenna Design Techniques
.” 2020. Web. 28 Feb 2021.
Vancouver:
Sharma Y. Machine Learning and Additive Manufacturing Based Antenna Design Techniques
. [Internet] [Doctoral dissertation]. University of Arizona; 2020. [cited 2021 Feb 28].
Available from: http://hdl.handle.net/10150/637723.
Council of Science Editors:
Sharma Y. Machine Learning and Additive Manufacturing Based Antenna Design Techniques
. [Doctoral Dissertation]. University of Arizona; 2020. Available from: http://hdl.handle.net/10150/637723
Virginia Tech
22.
Chang, Ai-Fu.
Process Modeling of Next-Generation Liquid Fuel Production - Commercial Hydrocracking Process and Biodiesel Manufacturing.
Degree: PhD, Chemical Engineering, 2011, Virginia Tech
URL: http://hdl.handle.net/10919/58043
► This dissertation includes two process modeling studies – (1) predictive modeling of large-scale integrated refinery reaction and fractionation systems from plant data – hydrocracking process;…
(more)
▼ This dissertation includes two
process modeling studies – (1) predictive modeling of large-scale integrated refinery reaction and fractionation systems from plant data – hydrocracking
process; and (2) integrated
process modeling and product design of biodiesel manufacturing. \r\n1. Predictive Modeling of Large-Scale Integrated Refinery Reaction and Fractionation Systems from Plant Data – Hydrocracking Processes: This work represents a workflow to develop, validate and apply a predictive model for rating and
optimization of large-scale integrated refinery reaction and fractionation systems from plant data. We demonstrate the workflow with two commercial processes – medium-pressure hydrocracking unit with a feed capacity of 1 million ton per year and high-pressure hydrocracking unit with a feed capacity of 2 million ton per year in the Asia Pacific. This work represents the detailed procedure for data acquisition to ensure accurate mass balances, and for implementing the workflow using Excel spreadsheets and a commercial software tool, Aspen HYSYS from Aspen Technology, Inc. The workflow includes special tools to facilitate an accurate transition from lumped kinetic components used in reactor modeling to the boiling point based pseudo-components required in the rigorous tray-by-tray distillation simulation. Two to three months of plant data are used to validate models' predictability. The resulting models accurately predict unit performance, product yields, and fuel properties from the corresponding operating conditions.\r\n2. Integrated
Process Modeling and Product Design of Biodiesel Manufacturing: This work represents first a comprehensive review of published literature pertaining to developing an integrated
process modeling and product design of biodiesel manufacturing, and identifies those deficient areas for further development. It also represents new modeling tools and a methodology for the integrated
process modeling and product design of an entire biodiesel manufacturing train. We demonstrate the methodology by simulating an integrated
process to predict reactor and \r\nseparator performance, stream conditions, and product qualities with different feedstocks. The results show that the methodology is effective not only for the rating and
optimization of an existing biodiesel manufacturing, and but also for the design of a new
process to produce biodiesel with specified fuel properties.
Advisors/Committee Members: Liu, Y. A. (committeechair), Achenie, Luke E. K. (committee member), Davis, Richey M. (committee member), Durrill, Preston L. (committee member).
Subjects/Keywords: product design; process optimization; biodiesel; hydrocracking; model
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Manager
APA (6th Edition):
Chang, A. (2011). Process Modeling of Next-Generation Liquid Fuel Production - Commercial Hydrocracking Process and Biodiesel Manufacturing. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/58043
Chicago Manual of Style (16th Edition):
Chang, Ai-Fu. “Process Modeling of Next-Generation Liquid Fuel Production - Commercial Hydrocracking Process and Biodiesel Manufacturing.” 2011. Doctoral Dissertation, Virginia Tech. Accessed February 28, 2021.
http://hdl.handle.net/10919/58043.
MLA Handbook (7th Edition):
Chang, Ai-Fu. “Process Modeling of Next-Generation Liquid Fuel Production - Commercial Hydrocracking Process and Biodiesel Manufacturing.” 2011. Web. 28 Feb 2021.
Vancouver:
Chang A. Process Modeling of Next-Generation Liquid Fuel Production - Commercial Hydrocracking Process and Biodiesel Manufacturing. [Internet] [Doctoral dissertation]. Virginia Tech; 2011. [cited 2021 Feb 28].
Available from: http://hdl.handle.net/10919/58043.
Council of Science Editors:
Chang A. Process Modeling of Next-Generation Liquid Fuel Production - Commercial Hydrocracking Process and Biodiesel Manufacturing. [Doctoral Dissertation]. Virginia Tech; 2011. Available from: http://hdl.handle.net/10919/58043
King Abdullah University of Science and Technology
23.
Alhazmi, Khalid.
Control and Optimization of Chemical Reactors with Model-free Deep Reinforcement Learning.
Degree: Physical Science and Engineering (PSE) Division, 2020, King Abdullah University of Science and Technology
URL: http://hdl.handle.net/10754/664024
► Abstract: Model-based control and optimization is the predominant paradigm in process systems engineering. The performance of model-based methods, however, rely heavily on the accuracy of…
(more)
▼ Abstract: Model-based control and
optimization is the predominant paradigm in
process systems
engineering. The performance of model-based methods, however, rely heavily
on the accuracy of the
process model, which declines over the operation cycle due to
various causes, such as catalyst deactivation, equipment aging, feedstock variability,
and others. This work aims to tackle this challenge by considering two alternative
approaches. The first approach replaces existing control and
optimization methods
with model-free reinforcement learning (RL). We apply a state-of-the-art reinforcement
learning algorithm to a network of reactions, evaluate the performance of the
RL controller in terms of setpoint tracking, disturbance rejection, and robustness to
parameter uncertainties, and optimize the reward function to achieve the desired control
and
optimization performance. The second approach presents a novel framework
for integrating Economic Model Predictive Control (EMPC) and RL for online model
parameters estimation. In this framework, EMPC optimally operates the closed-loop
system while maintaining closed-loop stability and recursive feasibility. At the same
time, the RL agent continuously compares the measured state of the
process with the
model’s predictions, and modifies the model parameters accordingly to optimize the
process. The performance of the proposed framework is illustrated on a network of
reactions with challenging dynamics and practical significance.
Advisors/Committee Members: Sarathy, Mani (advisor), Shamma, Jeff S. (committee member), Pinnau, Ingo (committee member).
Subjects/Keywords: Process control; Optimization; Artifical intelligence; Chemical reactors
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to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Alhazmi, K. (2020). Control and Optimization of Chemical Reactors with Model-free Deep Reinforcement Learning. (Thesis). King Abdullah University of Science and Technology. Retrieved from http://hdl.handle.net/10754/664024
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Alhazmi, Khalid. “Control and Optimization of Chemical Reactors with Model-free Deep Reinforcement Learning.” 2020. Thesis, King Abdullah University of Science and Technology. Accessed February 28, 2021.
http://hdl.handle.net/10754/664024.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Alhazmi, Khalid. “Control and Optimization of Chemical Reactors with Model-free Deep Reinforcement Learning.” 2020. Web. 28 Feb 2021.
Vancouver:
Alhazmi K. Control and Optimization of Chemical Reactors with Model-free Deep Reinforcement Learning. [Internet] [Thesis]. King Abdullah University of Science and Technology; 2020. [cited 2021 Feb 28].
Available from: http://hdl.handle.net/10754/664024.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Alhazmi K. Control and Optimization of Chemical Reactors with Model-free Deep Reinforcement Learning. [Thesis]. King Abdullah University of Science and Technology; 2020. Available from: http://hdl.handle.net/10754/664024
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Penn State University
24.
Alshraideh, Hussam.
Analysis and Optimization of Profile and Shape Response Experiments.
Degree: 2011, Penn State University
URL: https://submit-etda.libraries.psu.edu/catalog/12126
► An engineering process that exhibits a response in the form of a univariate (or one-dimensional) curve whenever new experimental conditions are tried is said to…
(more)
▼ An engineering
process that exhibits a response in the form of a univariate (or
one-dimensional) curve whenever new experimental conditions are tried is said
to have a profile, or functional response. Likewise, a manufacturing
process or
engineering system where the response of interest is the geometry of a product or
part is said to have a shape response. A shape response can relate to a planar
(two-dimensional) geometrical feature, or to a three-dimensional one. The overall
theme of this dissertation is the modeling and
optimization of engineering processes
that have either a profile or a shape response. The models and methods described
in this dissertation have application mainly in manufacturing, engineering design,
and computer experiments.
Statistical Shape Analysis (SSA) is a relatively new area within Statistics.
Traditionally the realm of biological applications, it has been recently applied
to manufacturing problems. D.G. Kendall, in pioneering work conducted in the
1980’s, defined the shape of an object as the geometrical information that remains
once certain similarity transformations, namely, rotations excluding reflections,
translations, and dilatations (or dilations) are filtered out. His work is based on
a landmark representation of an object, where a landmark consists of the coordinates
of a point measured on the object together with a label, with labels that
correspond from object to object. This representation turns out to be relevant
in manufacturing, since data obtained using a coordinate measuring machine will
typically have this appearance. Over the last 20 years, several SSA tests have
been proposed to detect differences in the mean shape between objects, but little
work exists on the relative merits of these methods. The first part of this dissertation
consists of a comprehensive performance analysis of landmark-based tests
for mean shape differences. Since the performance of these tests depends on the
types of shapes being tested, we consider both shapes that have been studied in the scarce extant literature on the
subject, namely triangles and arbitrary polygons
with few landmarks, and also consider shapes of specific interest in manufacturing
applications, such as circular and cylindrical geometries with tens to hundreds of
landmarks.
An additional problem studied in this dissertation is that of shape
optimization,
that is, find the best operating conditions that lead to the most desirable shape
of the product under fabrication. Previous tests for shape differences are based
on Kendall’s definition of shape, which neglects differences in size between objects
since it removes dilation (scale) effects, and make up for this deficiency by testing
separately for differences in size. As an alternative, we present statistical tests for
differences in form between the objects, where we define the form of an object as
the geometrical information that remains once the effect of rotations and translations,
but not dilations, is filtered out. We further develop a form
optimization
method when noise…
Advisors/Committee Members: Enrique Del Castillo, Dissertation Advisor/Co-Advisor, Enrique Del Castillo, Committee Chair/Co-Chair, M Jeya Chandra, Committee Member, Paul Griffin, Committee Member, Murali Haran, Committee Member.
Subjects/Keywords: Profile; Shape; Gaussian Process; Geometry; shape optimization; Statistical shape analysis; process optimization.
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APA (6th Edition):
Alshraideh, H. (2011). Analysis and Optimization of Profile and Shape Response Experiments. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/12126
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Alshraideh, Hussam. “Analysis and Optimization of Profile and Shape Response Experiments.” 2011. Thesis, Penn State University. Accessed February 28, 2021.
https://submit-etda.libraries.psu.edu/catalog/12126.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Alshraideh, Hussam. “Analysis and Optimization of Profile and Shape Response Experiments.” 2011. Web. 28 Feb 2021.
Vancouver:
Alshraideh H. Analysis and Optimization of Profile and Shape Response Experiments. [Internet] [Thesis]. Penn State University; 2011. [cited 2021 Feb 28].
Available from: https://submit-etda.libraries.psu.edu/catalog/12126.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Alshraideh H. Analysis and Optimization of Profile and Shape Response Experiments. [Thesis]. Penn State University; 2011. Available from: https://submit-etda.libraries.psu.edu/catalog/12126
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Princeton University
25.
Matthews, Logan Ryan.
Advancing Robust Optimization for Process Systems Engineering Applications
.
Degree: PhD, 2018, Princeton University
URL: http://arks.princeton.edu/ark:/88435/dsp01hh63sz60j
► Robust optimization is a popular method for incorporating parameter uncertainty into optimization models. Whether parameters represent the price of a feedstock or product, the operability…
(more)
▼ Robust
optimization is a popular method for incorporating parameter uncertainty into
optimization models. Whether parameters represent the price of a feedstock or product, the operability of an edge in a network, or length of time required for a unit operation, the actual realization of a parameter can have a tremendous impact on the optimal solution of a model. Robust
optimization centers on the use of uncertainty sets, which represent the possible parameter realizations which must be considered. In many cases, this uncertainty set may be directly imposed onto a constraint using duality theory, providing deterministic robust counterparts. In other cases, algorithmic developments are required to tractably solve robust
optimization problems, which may occur in multiple stages.
This dissertation seeks to expand the theory and application of robust
optimization for problems in
process systems engineering. Theoretically, this focuses on decreasing the conservatism and increasing the applicability of robust
optimization methods. This is addressed first through the development of new, tight bounds on the probability of constraint violation. These probabilistic bounds use the available information regarding the uncertain parameter distributions to determine the likelihood that a constraint becomes infeasible, using either the size of the uncertainty set a priori or the optimal solution values a posteriori. Then, new uncertainty sets are also derived for the case when both bounded and unbounded parameters exist in the same constraint, a previously unaddressed area of robust
optimization.
Robust
optimization is also shown to be effective in two major application areas. First, it is applied to
process synthesis and global
optimization of liquid transportation fuel refineries from natural gas and biomass, when feedstock prices, product prices, and investment costs are uncertain. The impact of parameter uncertainty on plant topologies and the probabilistic guarantees on profits are seen through multiple case studies. Finally, two-stage robust
optimization is also applied to resilient network design, for which edges in a network may fail at random, rendering flow impossible along that edge. In these cases, a tailored column and constraint generation algorithm is developed to solve the two-stage problem, for which the relatively complete recourse assumption does not hold.
Advisors/Committee Members: Kevrekidis, Ioannis G (advisor).
Subjects/Keywords: Global Optimization;
Optimization Under Uncertainty;
Process Synthesis;
Resilient Network Design;
Robust Optimization
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APA (6th Edition):
Matthews, L. R. (2018). Advancing Robust Optimization for Process Systems Engineering Applications
. (Doctoral Dissertation). Princeton University. Retrieved from http://arks.princeton.edu/ark:/88435/dsp01hh63sz60j
Chicago Manual of Style (16th Edition):
Matthews, Logan Ryan. “Advancing Robust Optimization for Process Systems Engineering Applications
.” 2018. Doctoral Dissertation, Princeton University. Accessed February 28, 2021.
http://arks.princeton.edu/ark:/88435/dsp01hh63sz60j.
MLA Handbook (7th Edition):
Matthews, Logan Ryan. “Advancing Robust Optimization for Process Systems Engineering Applications
.” 2018. Web. 28 Feb 2021.
Vancouver:
Matthews LR. Advancing Robust Optimization for Process Systems Engineering Applications
. [Internet] [Doctoral dissertation]. Princeton University; 2018. [cited 2021 Feb 28].
Available from: http://arks.princeton.edu/ark:/88435/dsp01hh63sz60j.
Council of Science Editors:
Matthews LR. Advancing Robust Optimization for Process Systems Engineering Applications
. [Doctoral Dissertation]. Princeton University; 2018. Available from: http://arks.princeton.edu/ark:/88435/dsp01hh63sz60j
Cornell University
26.
Ajagekar, Akshay.
Quantum Computing for Process Systems Optimization and Data Analytics.
Degree: M.S., Chemical Engineering, Chemical Engineering, 2020, Cornell University
URL: http://hdl.handle.net/1813/70302
► Quantum computing (QC) is the next frontier in computation and has attracted a lot of attention from the scientific community in recent years. With the…
(more)
▼ Quantum computing (QC) is the next frontier in computation and has attracted a lot of attention from the scientific community in recent years. With the ever-increasing complexity of combinatorial
optimization problems accompanied by a quickly growing search space, there arises a need for novel solution approaches capable of overcoming limitations of the current
optimization paradigms carried out on state-of-the-art classical computers. QC provides a novel approach to help solve some of the most complex
optimization problems while offering an essential speed advantage over classical methods. Complex nature of energy systems due to their structure and large number of design and operational constraints make energy systems
optimization a hard problem for most available algorithms. We propose novel reformulations of energy systems
optimization problems namely facility location-allocation for energy systems infrastructure development, unit commitment of electric power systems operations, and heat exchanger network synthesis into unconstrained binary
optimization problems to facilitate ease of mapping and solving on quantum hardware. Several technological limitations face commercially available quantum computers, therefore, harnessing the complementary strengths of classical and quantum computers to solve complex large-scale
optimization problems is of utmost importance. We further develop novel hybrid QC-based models and methods that exploit the complementary strengths of QC and exact solution techniques to overcome the combinatorial complexity when solving large-scale discrete-continuous
optimization problems. The applicability of these QC-based algorithms is demonstrated by large-scale applications across scales that are relevant to molecular design,
process scheduling, manufacturing systems operations, and logistics
optimization. Apart from
optimization, QC-based techniques can also be applied to fault diagnosis of complex chemical processes.
Advisors/Committee Members: You, Fengqi (chair), Varner, Jeffrey (committee member).
Subjects/Keywords: Deep learning; Hybrid techniques; Optimization; Process monitoring; Process systems; Quantum computing
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APA (6th Edition):
Ajagekar, A. (2020). Quantum Computing for Process Systems Optimization and Data Analytics. (Masters Thesis). Cornell University. Retrieved from http://hdl.handle.net/1813/70302
Chicago Manual of Style (16th Edition):
Ajagekar, Akshay. “Quantum Computing for Process Systems Optimization and Data Analytics.” 2020. Masters Thesis, Cornell University. Accessed February 28, 2021.
http://hdl.handle.net/1813/70302.
MLA Handbook (7th Edition):
Ajagekar, Akshay. “Quantum Computing for Process Systems Optimization and Data Analytics.” 2020. Web. 28 Feb 2021.
Vancouver:
Ajagekar A. Quantum Computing for Process Systems Optimization and Data Analytics. [Internet] [Masters thesis]. Cornell University; 2020. [cited 2021 Feb 28].
Available from: http://hdl.handle.net/1813/70302.
Council of Science Editors:
Ajagekar A. Quantum Computing for Process Systems Optimization and Data Analytics. [Masters Thesis]. Cornell University; 2020. Available from: http://hdl.handle.net/1813/70302
Louisiana State University
27.
Ma, Yan.
Machine Learning Based Applications for Data Visualization, Modeling, Control, and Optimization for Chemical and Biological Systems.
Degree: PhD, Chemical Engineering, 2020, Louisiana State University
URL: https://digitalcommons.lsu.edu/gradschool_dissertations/5427
► This dissertation report covers Yan Ma’s Ph.D. research with applicational studies of machine learning in manufacturing and biological systems. The research work mainly focuses…
(more)
▼ This dissertation report covers Yan Ma’s Ph.D. research with applicational studies of machine learning in manufacturing and biological systems. The research work mainly focuses on reaction modeling, optimization, and control using a deep learning-based approaches, and the work mainly concentrates on deep reinforcement learning (DRL). Yan Ma’s research also involves with data mining with bioinformatics. Large-scale data obtained in RNA-seq is analyzed using non-linear dimensionality reduction with Principal Component Analysis (PCA), t-Distributed Stochastic Neighbor Embedding (t-SNE), and Uniform Manifold Approximation and Projection (UMAP), followed by clustering analysis using k-Means and Hierarchical Density-Based Spatial Clustering with Noise (HDBSCAN). This report focuses on 3 case studies with DRL optimization control including a polymerization reaction control with deep reinforcement learning, a bioreactor optimization, and a fed-batch reaction optimization from a reactor at Dow Inc.. In the first study, a data-driven controller based on DRL is developed for a fed-batch polymerization reaction with multiple continuous manipulative variables with continuous control. The second case study is the modeling and optimization of a bioreactor. In this study, a data-driven reaction model is developed using Artificial Neural Network (ANN) to simulate the growth curve and bio-product accumulation of cyanobacteria Plectonema. Then a DRL control agent that optimizes the daily nutrient input is applied to maximize the yield of valuable bio-product C-phycocyanin. C-phycocyanin yield is increased by 52.1% compared to a control group with the same total nutrient content in experimental validation. The third case study is employing the data-driven control scheme for optimization of a reactor from Dow Inc, where a DRL-based optimization framework is established for the optimization of the Multi-Input, Multi-Output (MIMO) reaction system with reaction surrogate modeling. Yan Ma’s research overall shows promising directions for employing the emerging technologies of data-driven methods and deep learning in the field of manufacturing and biological systems. It is demonstrated that DRL is an efficient algorithm in the study of three different reaction systems with both stochastic and deterministic policies. Also, the use of data-driven models in reaction simulation also shows promising results with the non-linear nature and fast computational speed of the neural network models.
Subjects/Keywords: process control; optimization; machine learning; reinforcement learning; process modeling
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APA (6th Edition):
Ma, Y. (2020). Machine Learning Based Applications for Data Visualization, Modeling, Control, and Optimization for Chemical and Biological Systems. (Doctoral Dissertation). Louisiana State University. Retrieved from https://digitalcommons.lsu.edu/gradschool_dissertations/5427
Chicago Manual of Style (16th Edition):
Ma, Yan. “Machine Learning Based Applications for Data Visualization, Modeling, Control, and Optimization for Chemical and Biological Systems.” 2020. Doctoral Dissertation, Louisiana State University. Accessed February 28, 2021.
https://digitalcommons.lsu.edu/gradschool_dissertations/5427.
MLA Handbook (7th Edition):
Ma, Yan. “Machine Learning Based Applications for Data Visualization, Modeling, Control, and Optimization for Chemical and Biological Systems.” 2020. Web. 28 Feb 2021.
Vancouver:
Ma Y. Machine Learning Based Applications for Data Visualization, Modeling, Control, and Optimization for Chemical and Biological Systems. [Internet] [Doctoral dissertation]. Louisiana State University; 2020. [cited 2021 Feb 28].
Available from: https://digitalcommons.lsu.edu/gradschool_dissertations/5427.
Council of Science Editors:
Ma Y. Machine Learning Based Applications for Data Visualization, Modeling, Control, and Optimization for Chemical and Biological Systems. [Doctoral Dissertation]. Louisiana State University; 2020. Available from: https://digitalcommons.lsu.edu/gradschool_dissertations/5427
University of Waterloo
28.
Zavatti, Vanessa.
Monitoring of an Antigen Manufacturing Process Using Fluorescence.
Degree: 2014, University of Waterloo
URL: http://hdl.handle.net/10012/8521
► Bordetella pertussis is one of two Gram-negative bacteria responsible for causing whooping cough in humans, a highly contagious disease that infects the human upper respiratory…
(more)
▼ Bordetella pertussis is one of two Gram-negative bacteria responsible for causing whooping cough in humans, a highly contagious disease that infects the human upper respiratory tract. Whole-cell and acellular vaccines have been developed but due to side-effects resulting from whole-cell vaccines, acellular vaccines are currently preferred to prevent this disease. A second bacterium known to cause whooping cough is Bordetella parapertussis, but since it causes less aggressive symptoms, only B. pertussis is utilized in the manufacture of the vaccine. One acellular vaccine is based on four virulence factors: pertussis toxin (PT), filamentous hemagglutinin (FHA), pertactin (PRN), and fimbriae (FIM).
The focus of this thesis was to explore the use of spectrofluorometry for monitoring and forecasting the performance of the upstream and downstream operations in the PRN purification process at Sanofi Pasteur. The upstream fermentation process includes a series of reactors of increasing volume where the microorganism is grown under controlled conditions. The PRN purification process involves a series of sequential steps for separating this protein from other proteins for later use in the vaccine. The PRN is precipitated in three steps with ammonium sulphate at three different concentrations. The pellet is collected by centrifugation and dissolved in a buffer solution followed by chromatographic separation. The run-through is then ultra-filtered and diafiltered in two separate steps. The resulting concentrate is dissolved in water and subjected to another chromatographic step and diafiltration. The final filtration of PRN involves a pre-filtration and sterile filtration. Finally, the samples are collected for quality control.
The objective of this work was to monitor the process at different steps of the upstream and downstream purification process by multi-wavelength fluorescence spectroscopy in combination with multi-variate statistical methods. From the spectra, it was possible to identify fluorescent compounds, such as amino acids and enzyme cofactors, without performing an additional pre-treatment or purification step. Also, the identification of conformational changes in proteins and formation of complexes, such as NAD(P)-enzyme complex, was possible based on the shift in the emission peaks of the compounds identified. These results demonstrated the feasibility of using this tool for qualitative evaluation of the process.
Multivariate methods, such as PCA and PLS, were used to extract relevant information and compress the fluorescence data acquired. PCA was effective for correlating variability in the yield of pertactin to a particular fluorescence fingerprint. As a result of the study, it was concluded that a possible source of variability in the productivity that is observed might be a metabolic shift during the fermentation steps that leads to the accumulation of NAD(P)H (or NAD(P)H-enzyme complex) probably due to oxygen transfer limitations. This conclusion was reached after investigating changes in the…
Subjects/Keywords: antigen manufacturing; process monitoring; spectro-fluorescence; multivariate statistics; process diagnosis; process optimization
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APA (6th Edition):
Zavatti, V. (2014). Monitoring of an Antigen Manufacturing Process Using Fluorescence. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/8521
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Zavatti, Vanessa. “Monitoring of an Antigen Manufacturing Process Using Fluorescence.” 2014. Thesis, University of Waterloo. Accessed February 28, 2021.
http://hdl.handle.net/10012/8521.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Zavatti, Vanessa. “Monitoring of an Antigen Manufacturing Process Using Fluorescence.” 2014. Web. 28 Feb 2021.
Vancouver:
Zavatti V. Monitoring of an Antigen Manufacturing Process Using Fluorescence. [Internet] [Thesis]. University of Waterloo; 2014. [cited 2021 Feb 28].
Available from: http://hdl.handle.net/10012/8521.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Zavatti V. Monitoring of an Antigen Manufacturing Process Using Fluorescence. [Thesis]. University of Waterloo; 2014. Available from: http://hdl.handle.net/10012/8521
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
UCLA
29.
ALANQAR, ANAS WAEL.
Economic Model Predictive Control of Nonlinear Process Systems Using Empirical Models.
Degree: Chemical Engineering, 2015, UCLA
URL: http://www.escholarship.org/uc/item/8r63q1dj
► Economic model predictive control (EMPC) is a feedback control technique that attemptsto tightly integrate economic optimization and feedback control since it is a predictive control…
(more)
▼ Economic model predictive control (EMPC) is a feedback control technique that attemptsto tightly integrate economic optimization and feedback control since it is a predictive control scheme that is formulated with an objective function representing the process economics. As its name implies, EMPC requires the availability of a dynamic model to compute its control actions and such a model may be obtained either through application of first-principles or though system identification techniques. However, in industrial practice, it may be difficult in general to obtain an accurate first-principles model of the process. Motivated by this, in the present work, Lyapunov-based economic model predictive control (LEMPC) is designed with an empirical model that allows for closed-loop stability guarantees in the context of nonlinear chemical processes. Specifically, when the linear model provides a sufficient degree of accuracy in the region where time-varying economically optimal operation is considered, conditions for closed-loop stability under the LEMPC scheme based on the empirical model are derived. The LEMPC scheme is applied to a chemical process example to demonstrate its closed-loop stability and performance properties as well as significant computational advantages
Subjects/Keywords: Chemical engineering; CHEMICAL PROCESS; ECONOMIC MODEL PREDICTIVE CONTROL; PROCESS CONTROL; PROCESS ECONOMIC; PROCESS OPTIMIZATION; SYSTEM IDENTIFICATION
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APA (6th Edition):
ALANQAR, A. W. (2015). Economic Model Predictive Control of Nonlinear Process Systems Using Empirical Models. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/8r63q1dj
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
ALANQAR, ANAS WAEL. “Economic Model Predictive Control of Nonlinear Process Systems Using Empirical Models.” 2015. Thesis, UCLA. Accessed February 28, 2021.
http://www.escholarship.org/uc/item/8r63q1dj.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
ALANQAR, ANAS WAEL. “Economic Model Predictive Control of Nonlinear Process Systems Using Empirical Models.” 2015. Web. 28 Feb 2021.
Vancouver:
ALANQAR AW. Economic Model Predictive Control of Nonlinear Process Systems Using Empirical Models. [Internet] [Thesis]. UCLA; 2015. [cited 2021 Feb 28].
Available from: http://www.escholarship.org/uc/item/8r63q1dj.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
ALANQAR AW. Economic Model Predictive Control of Nonlinear Process Systems Using Empirical Models. [Thesis]. UCLA; 2015. Available from: http://www.escholarship.org/uc/item/8r63q1dj
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Brno University of Technology
30.
Kutílek, Vladislav.
Tvorba procesního řízení zakázky ve vybrané profesi stavebnictví: Creation of Process Order Management in Selected Construction Professions.
Degree: 2019, Brno University of Technology
URL: http://hdl.handle.net/11012/178467
► The bachelor thesis deals with the ordering process of a selected manufacturing company. The thesis is divided into several sections. In the first part is…
(more)
▼ The bachelor thesis deals with the ordering
process of a selected manufacturing company. The thesis is divided into several sections. In the first part is described theoretical knowledge in the field of
process management. In the following section is introduced a carpentry and roofing company where I worked for some time and gained required information for this thesis. In the analytical part is analysed the current state of the company in attitude to order management and revealed its lack. Based on this knowledge, I will optimize order management.
Advisors/Committee Members: Jurová, Marie (advisor), Poledník, Jan (referee).
Subjects/Keywords: Procesní řízení; analýza; průběh zakázky; optimalizace procesu; proces; Process management; analysis; order process; process optimization; process
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APA (6th Edition):
Kutílek, V. (2019). Tvorba procesního řízení zakázky ve vybrané profesi stavebnictví: Creation of Process Order Management in Selected Construction Professions. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/178467
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Kutílek, Vladislav. “Tvorba procesního řízení zakázky ve vybrané profesi stavebnictví: Creation of Process Order Management in Selected Construction Professions.” 2019. Thesis, Brno University of Technology. Accessed February 28, 2021.
http://hdl.handle.net/11012/178467.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Kutílek, Vladislav. “Tvorba procesního řízení zakázky ve vybrané profesi stavebnictví: Creation of Process Order Management in Selected Construction Professions.” 2019. Web. 28 Feb 2021.
Vancouver:
Kutílek V. Tvorba procesního řízení zakázky ve vybrané profesi stavebnictví: Creation of Process Order Management in Selected Construction Professions. [Internet] [Thesis]. Brno University of Technology; 2019. [cited 2021 Feb 28].
Available from: http://hdl.handle.net/11012/178467.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Kutílek V. Tvorba procesního řízení zakázky ve vybrané profesi stavebnictví: Creation of Process Order Management in Selected Construction Professions. [Thesis]. Brno University of Technology; 2019. Available from: http://hdl.handle.net/11012/178467
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
◁ [1] [2] [3] [4] [5] … [23] ▶
. 
Open Access Theses and Dissertations
