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You searched for subject:(process parameter optimization). Showing records 1 – 11 of 11 total matches.

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1. 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

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)

Subjects/Keywords: Friction Stir Welding; process parameter optimization

Page 1

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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 December 09, 2019. 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. 09 Dec 2019.

Vancouver:

S V. Process parameter optimization and Characterization of friction stir Welding of aluminium alloy AA 5083;. [Internet] [Thesis]. Anna University; 2014. [cited 2019 Dec 09]. 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


University of Waikato

2. Ma, Jinjin. Parameter Tuning Using Gaussian Processes .

Degree: 2012, University of Waikato

 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)

Subjects/Keywords: Parameter Tunning; Gaussian Process Optimization; Machine Learning

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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 December 09, 2019. http://hdl.handle.net/10289/6497.

MLA Handbook (7th Edition):

Ma, Jinjin. “Parameter Tuning Using Gaussian Processes .” 2012. Web. 09 Dec 2019.

Vancouver:

Ma J. Parameter Tuning Using Gaussian Processes . [Internet] [Masters thesis]. University of Waikato; 2012. [cited 2019 Dec 09]. 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


The Ohio State University

3. Jirathearanat, Suwat. Advanced methods for finite element simulation for part and process design in tube hydroforming.

Degree: PhD, Mechanical Engineering, 2004, The Ohio State University

 Tube HydroForming (THF) process offers several advantages over the conventional manufacturing via stamping and welding; a) part consolidation, b) weight reduction, c) improved structural stiffness,… (more)

Subjects/Keywords: Tube hydroforming; Finite element simulation; Optimization; Process parameter design

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APA (6th Edition):

Jirathearanat, S. (2004). Advanced methods for finite element simulation for part and process design in tube hydroforming. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1071878178

Chicago Manual of Style (16th Edition):

Jirathearanat, Suwat. “Advanced methods for finite element simulation for part and process design in tube hydroforming.” 2004. Doctoral Dissertation, The Ohio State University. Accessed December 09, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1071878178.

MLA Handbook (7th Edition):

Jirathearanat, Suwat. “Advanced methods for finite element simulation for part and process design in tube hydroforming.” 2004. Web. 09 Dec 2019.

Vancouver:

Jirathearanat S. Advanced methods for finite element simulation for part and process design in tube hydroforming. [Internet] [Doctoral dissertation]. The Ohio State University; 2004. [cited 2019 Dec 09]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1071878178.

Council of Science Editors:

Jirathearanat S. Advanced methods for finite element simulation for part and process design in tube hydroforming. [Doctoral Dissertation]. The Ohio State University; 2004. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1071878178


University of Michigan

4. Steimle, Lauren. Stochastic Dynamic Optimization Under Ambiguity.

Degree: PhD, Industrial & Operations Engineering, 2019, University of Michigan

 Stochastic dynamic optimization methods are powerful mathematical tools for informing sequential decision-making in environments where the outcomes of decisions are uncertain. For instance, the Markov… (more)

Subjects/Keywords: dynamic programming; Markov decision process; stochastic optimization; decomposition; parameter uncertainty; ambiguity; Industrial and Operations Engineering; Engineering

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APA (6th Edition):

Steimle, L. (2019). Stochastic Dynamic Optimization Under Ambiguity. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/149947

Chicago Manual of Style (16th Edition):

Steimle, Lauren. “Stochastic Dynamic Optimization Under Ambiguity.” 2019. Doctoral Dissertation, University of Michigan. Accessed December 09, 2019. http://hdl.handle.net/2027.42/149947.

MLA Handbook (7th Edition):

Steimle, Lauren. “Stochastic Dynamic Optimization Under Ambiguity.” 2019. Web. 09 Dec 2019.

Vancouver:

Steimle L. Stochastic Dynamic Optimization Under Ambiguity. [Internet] [Doctoral dissertation]. University of Michigan; 2019. [cited 2019 Dec 09]. Available from: http://hdl.handle.net/2027.42/149947.

Council of Science Editors:

Steimle L. Stochastic Dynamic Optimization Under Ambiguity. [Doctoral Dissertation]. University of Michigan; 2019. Available from: http://hdl.handle.net/2027.42/149947


Georgia Tech

5. Tang, Yanyan. Stereolithography Cure Process Modeling.

Degree: PhD, Chemical Engineering, 2005, Georgia Tech

 Although stereolithography (SL) is a remarkable improvement over conventional prototyping production, it is being pushed aggressively for improvements in both speed and resolution. However, it… (more)

Subjects/Keywords: Kinetics; Photopolymerization; Stereolithography; Process simulation; Parameter effect significance; Parameter optimization

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APA (6th Edition):

Tang, Y. (2005). Stereolithography Cure Process Modeling. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/7235

Chicago Manual of Style (16th Edition):

Tang, Yanyan. “Stereolithography Cure Process Modeling.” 2005. Doctoral Dissertation, Georgia Tech. Accessed December 09, 2019. http://hdl.handle.net/1853/7235.

MLA Handbook (7th Edition):

Tang, Yanyan. “Stereolithography Cure Process Modeling.” 2005. Web. 09 Dec 2019.

Vancouver:

Tang Y. Stereolithography Cure Process Modeling. [Internet] [Doctoral dissertation]. Georgia Tech; 2005. [cited 2019 Dec 09]. Available from: http://hdl.handle.net/1853/7235.

Council of Science Editors:

Tang Y. Stereolithography Cure Process Modeling. [Doctoral Dissertation]. Georgia Tech; 2005. Available from: http://hdl.handle.net/1853/7235

6. Ramaswami, Hemant. An integrated framework for virtual machining and inspection of turned parts.

Degree: PhD, Engineering and Applied Science: Industrial Engineering, 2010, University of Cincinnati

  The research presented in this dissertation focuses on a two-stage methodology of virtual machining of parts produced on a three-axis turning center and virtual… (more)

Subjects/Keywords: Industrial Engineering; Virtual Machining; Virtual Inspection; Machining Advisor; Inspection Advisor; Process Parameter Optimization

…14 2.1.7. Turning Parameter Optimization… …23 3.1. Process Parameter Model… …91 6.1.5. Optimization of Process Parameters to achieve desired GD&T Parameters… …99 6.19 Comparison of GD&T parameter results from optimization and actual parts… …process parameters, and tool wear. The model so developed is used to calculate various geometric… 

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APA (6th Edition):

Ramaswami, H. (2010). An integrated framework for virtual machining and inspection of turned parts. (Doctoral Dissertation). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1282574694

Chicago Manual of Style (16th Edition):

Ramaswami, Hemant. “An integrated framework for virtual machining and inspection of turned parts.” 2010. Doctoral Dissertation, University of Cincinnati. Accessed December 09, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1282574694.

MLA Handbook (7th Edition):

Ramaswami, Hemant. “An integrated framework for virtual machining and inspection of turned parts.” 2010. Web. 09 Dec 2019.

Vancouver:

Ramaswami H. An integrated framework for virtual machining and inspection of turned parts. [Internet] [Doctoral dissertation]. University of Cincinnati; 2010. [cited 2019 Dec 09]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1282574694.

Council of Science Editors:

Ramaswami H. An integrated framework for virtual machining and inspection of turned parts. [Doctoral Dissertation]. University of Cincinnati; 2010. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1282574694


Georgia Tech

7. An, Na. Resource Modeling and Allocation in Competitive Systems.

Degree: PhD, Industrial and Systems Engineering, 2005, Georgia Tech

 This thesis includes three self-contained projects: In the first project Bidding strategies and their impact on the auctioneer's revenue in combinatorial auctions, focusing on combinatorial… (more)

Subjects/Keywords: Shelf-space allocation; Trade allowance; Multistage process; Robust parameter design; Bidding strategy; Combinatorial auctions; Mathematical optimization; Resource allocation; Game theory

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APA (6th Edition):

An, N. (2005). Resource Modeling and Allocation in Competitive Systems. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/6997

Chicago Manual of Style (16th Edition):

An, Na. “Resource Modeling and Allocation in Competitive Systems.” 2005. Doctoral Dissertation, Georgia Tech. Accessed December 09, 2019. http://hdl.handle.net/1853/6997.

MLA Handbook (7th Edition):

An, Na. “Resource Modeling and Allocation in Competitive Systems.” 2005. Web. 09 Dec 2019.

Vancouver:

An N. Resource Modeling and Allocation in Competitive Systems. [Internet] [Doctoral dissertation]. Georgia Tech; 2005. [cited 2019 Dec 09]. Available from: http://hdl.handle.net/1853/6997.

Council of Science Editors:

An N. Resource Modeling and Allocation in Competitive Systems. [Doctoral Dissertation]. Georgia Tech; 2005. Available from: http://hdl.handle.net/1853/6997

8. Ghobara, Emad Moustafa Yasser. Modeling, Optimization and Estimation in Electric Arc Furnace (EAF) Operation.

Degree: MASc, 2013, McMaster University

The electric arc furnace (EAF) is a highly energy intensive process used to convert scrap metal into molten steel. The aim of this research… (more)

Subjects/Keywords: Electric Arc Furnace; State Estimation; Dynamic Optimization; Sensitivity Analysis; Parameter Estimation; Modeling; Process Control and Systems; Process Control and Systems

process and which can be used to implement different optimization and control strategies. This… …complex industrial process, dynamic optimization is carried out which focuses on determining the… …Optimization Model validation is presented through parameter estimation and calibration against… …identified through dynamic optimization of the EAF process. Different scenarios are considered that… …the EAF process in terms of optimal control. This is usually formulated as an optimization… 

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APA (6th Edition):

Ghobara, E. M. Y. (2013). Modeling, Optimization and Estimation in Electric Arc Furnace (EAF) Operation. (Masters Thesis). McMaster University. Retrieved from http://hdl.handle.net/11375/13345

Chicago Manual of Style (16th Edition):

Ghobara, Emad Moustafa Yasser. “Modeling, Optimization and Estimation in Electric Arc Furnace (EAF) Operation.” 2013. Masters Thesis, McMaster University. Accessed December 09, 2019. http://hdl.handle.net/11375/13345.

MLA Handbook (7th Edition):

Ghobara, Emad Moustafa Yasser. “Modeling, Optimization and Estimation in Electric Arc Furnace (EAF) Operation.” 2013. Web. 09 Dec 2019.

Vancouver:

Ghobara EMY. Modeling, Optimization and Estimation in Electric Arc Furnace (EAF) Operation. [Internet] [Masters thesis]. McMaster University; 2013. [cited 2019 Dec 09]. Available from: http://hdl.handle.net/11375/13345.

Council of Science Editors:

Ghobara EMY. Modeling, Optimization and Estimation in Electric Arc Furnace (EAF) Operation. [Masters Thesis]. McMaster University; 2013. Available from: http://hdl.handle.net/11375/13345


The Ohio State University

9. Ittiwattana, Waraporn. A Method for Simulation Optimization with Applications in Robust Process Design and Locating Supply Chain Operations.

Degree: PhD, Industrial and Systems Engineering, 2002, The Ohio State University

  This dissertation contains the first proof of convergence of a genetic algorithm in the context of stochastic optimization. The class of stochastic optimization problems… (more)

Subjects/Keywords: Genetic Algorithms; Stochastic Optimization; Monte Carlo Methods; Time Non-homogenous Markov Process; Taguchi Methods; Signal-to-Noise Ratio; Parameter Design; Multicriterion Optimization; Global Supply Chain Modeling and Optimization; Facility Location

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APA (6th Edition):

Ittiwattana, W. (2002). A Method for Simulation Optimization with Applications in Robust Process Design and Locating Supply Chain Operations. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1030366020

Chicago Manual of Style (16th Edition):

Ittiwattana, Waraporn. “A Method for Simulation Optimization with Applications in Robust Process Design and Locating Supply Chain Operations.” 2002. Doctoral Dissertation, The Ohio State University. Accessed December 09, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1030366020.

MLA Handbook (7th Edition):

Ittiwattana, Waraporn. “A Method for Simulation Optimization with Applications in Robust Process Design and Locating Supply Chain Operations.” 2002. Web. 09 Dec 2019.

Vancouver:

Ittiwattana W. A Method for Simulation Optimization with Applications in Robust Process Design and Locating Supply Chain Operations. [Internet] [Doctoral dissertation]. The Ohio State University; 2002. [cited 2019 Dec 09]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1030366020.

Council of Science Editors:

Ittiwattana W. A Method for Simulation Optimization with Applications in Robust Process Design and Locating Supply Chain Operations. [Doctoral Dissertation]. The Ohio State University; 2002. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1030366020

10. Bentley, Jason A. Systematic process development by simultaneous modeling and optimization of simulated moving bed chromatography.

Degree: PhD, Chemical and Biomolecular Engineering, 2013, Georgia Tech

 Adsorption separation processes are extremely important to the chemical industry, especially in the manufacturing of food, pharmaceutical, and fine chemical products. This work addresses three… (more)

Subjects/Keywords: Simulated moving bed chromatography; Adsorption processes; Model selection; Parameter estimation; Numerical optimization; Transient process control; Adsorption; Separation (Technology); Chromatographic analysis

…development that utilizes dynamic optimization, transient experimental data, and parameter… …multi-objective optimization of each process, and this information is used to choose between… …conditions, parameter estimation, and optimal control of transient operation. These optimization… …that can also be used for process design with model-based optimization [78]. This… …SMB process that can be considered in an optimization problem. In this work, the main focus… 

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APA (6th Edition):

Bentley, J. A. (2013). Systematic process development by simultaneous modeling and optimization of simulated moving bed chromatography. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/47531

Chicago Manual of Style (16th Edition):

Bentley, Jason A. “Systematic process development by simultaneous modeling and optimization of simulated moving bed chromatography.” 2013. Doctoral Dissertation, Georgia Tech. Accessed December 09, 2019. http://hdl.handle.net/1853/47531.

MLA Handbook (7th Edition):

Bentley, Jason A. “Systematic process development by simultaneous modeling and optimization of simulated moving bed chromatography.” 2013. Web. 09 Dec 2019.

Vancouver:

Bentley JA. Systematic process development by simultaneous modeling and optimization of simulated moving bed chromatography. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2019 Dec 09]. Available from: http://hdl.handle.net/1853/47531.

Council of Science Editors:

Bentley JA. Systematic process development by simultaneous modeling and optimization of simulated moving bed chromatography. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/47531


Indian Institute of Science

11. Anilkumar, A K. Application Of Controlled Random Search Optimization Technique In MMLE With Process Noise.

Degree: 2000, Indian Institute of Science

 Generally in most of the applications of estimation theory using the Method of Maximum Likelihood Estimation (MMLE) to dynamical systems one deals with a situation… (more)

Subjects/Keywords: Aerospace Engineering; Estimation Theory; Kalman Filter; Aircraft - Random Search Optimization; Method of Maximum Likelihood Estimation(MMLE); Parameter Estimation; Controlled Random Search (CRS); Process Noise; Extended Kalman Filter (EKF)

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APA (6th Edition):

Anilkumar, A. K. (2000). Application Of Controlled Random Search Optimization Technique In MMLE With Process Noise. (Thesis). Indian Institute of Science. Retrieved from http://hdl.handle.net/2005/232

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):

Anilkumar, A K. “Application Of Controlled Random Search Optimization Technique In MMLE With Process Noise.” 2000. Thesis, Indian Institute of Science. Accessed December 09, 2019. http://hdl.handle.net/2005/232.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Anilkumar, A K. “Application Of Controlled Random Search Optimization Technique In MMLE With Process Noise.” 2000. Web. 09 Dec 2019.

Vancouver:

Anilkumar AK. Application Of Controlled Random Search Optimization Technique In MMLE With Process Noise. [Internet] [Thesis]. Indian Institute of Science; 2000. [cited 2019 Dec 09]. Available from: http://hdl.handle.net/2005/232.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Anilkumar AK. Application Of Controlled Random Search Optimization Technique In MMLE With Process Noise. [Thesis]. Indian Institute of Science; 2000. Available from: http://hdl.handle.net/2005/232

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

.