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You searched for subject:(COSYSMO). Showing records 1 – 3 of 3 total matches.

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University of Southern California

1. Fortune, Jared. Estimating systems engineering reuse with the constructive systems engineering cost model (COSYSMO 2.0).

Degree: PhD, Industrial & Systems Engineering, 2009, University of Southern California

The Constructive Systems Engineering Cost Model (COSYSMO) is an open, parametric model developed at the University of Southern California Center for Systems and Software Engineering (USC-CSSE) as a tool for estimating the amount of systems engineering effort for a large-scale system. This dissertation presents an improvement to COSYSMO by introducing the ability to account for systems engineering reuse through 1) a framework for the reuse process and 2) a refined characterization of systems engineering reuse.; Complex systems have reached the point where reuse is the norm rather than the exception. In an effort to address increasing complexity while maintaining manageability, systems engineers frequently leverage (or reuse) previously developed systems engineering products (i.e. requirements, test plans, interfaces, etc.) as a means of reducing development schedule, system cost, or risk; however, the effects of reuse have historically been difficult to quantify, and therefore justify. Through past and on-going work at USC-CSSE in systems engineering cost modeling as well as the close relationship between USC-CSSE and its industry affiliates, the need for a systems engineering reuse cost model was identified. COSYSMO 2.0 addresses this need by providing systems engineers with a tool that enables the quantification and rationalization of the effect of reuse. The model has broad usability for and direct applicability to practitioners, and has been validated by both subject matter expert opinion and across over 40 projects at a large and diversified systems engineering organization.; The intellectual contributions of this dissertation are not solely limited to COSYSMO 2.0 as an improvement to COSYSMO and a model for estimating the effect of systems engineering reuse, but also include a) the identification of research gaps in the field of systems engineering, b) the characterization of systems engineering reuse through industry-accepted definitions, and c) the development of a framework and heuristics for how systems engineering organizations can approach and manage reuse. Advisors/Committee Members: Boehm, Barry W.Settles, Stan (Committee Chair), Steece, Bert M. (Committee Member), Valerdi, Ricardo (Committee Member).

Subjects/Keywords: COSYSMO; COSYSMO 2.0; cost; systems engineering; reuse

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Fortune, J. (2009). Estimating systems engineering reuse with the constructive systems engineering cost model (COSYSMO 2.0). (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/266642/rec/2499

Chicago Manual of Style (16th Edition):

Fortune, Jared. “Estimating systems engineering reuse with the constructive systems engineering cost model (COSYSMO 2.0).” 2009. Doctoral Dissertation, University of Southern California. Accessed July 16, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/266642/rec/2499.

MLA Handbook (7th Edition):

Fortune, Jared. “Estimating systems engineering reuse with the constructive systems engineering cost model (COSYSMO 2.0).” 2009. Web. 16 Jul 2019.

Vancouver:

Fortune J. Estimating systems engineering reuse with the constructive systems engineering cost model (COSYSMO 2.0). [Internet] [Doctoral dissertation]. University of Southern California; 2009. [cited 2019 Jul 16]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/266642/rec/2499.

Council of Science Editors:

Fortune J. Estimating systems engineering reuse with the constructive systems engineering cost model (COSYSMO 2.0). [Doctoral Dissertation]. University of Southern California; 2009. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/266642/rec/2499


University of Southern California

2. Peña, Mauricio Eduardo. Quantifying the impact of requirements volatility on systems engineering effort.

Degree: PhD, Industrial and Systems Engineering, 2012, University of Southern California

Although changes in requirements are expected as part of a system’s development, excessive volatility after the requirements baseline is likely to result in cost overruns and schedule extensions in large complex systems. Furthermore, late changes in requirements may cause significant rework of engineering products and lead to project failure. Changes in requirements should be expected, accounted for and managed within the context of the system of interest. Unfortunately, system developers lack adequate methods and tools to anticipate and manage the impact of volatile requirements, and cost estimating techniques often fail to account for their economic consequences. ❧ This dissertation presents an extension to COSYSMO, a generally-available parametric systems engineering cost model, which incorporates requirements volatility as a predictor of systems engineering effort within COSYSMO’s structure and scope with the aim of improving the model’s cost estimation capabilities. The requirements volatility model extension was developed through a combination of expert judgment gathered through surveys and discussions in six different research workshops and historical data collected from 25 projects. The null hypothesis that the volatility of requirements throughout a system’s life cycle is not a statistically significant predictor of systems engineering effort was rejected in factor of the alternative hypothesis with a P-value of 0.03. A comparison of the estimation accuracy of COSYSMO to that of the model that includes volatility effects shows an improvement in predictive accuracy from 52% to 80% at the PRED (20) level and a reduction in the mean magnitude error (MMRE) from 21% to 16%. In addition, the coefficient of determination between the predictor, systems engineering size adjusted for diseconomies of scale, and the response, actual systems engineering effort improved from an R2 of 0.85 to an R2 of 0.92 when the volatility factor was applied to the model. ❧ In addition to the mathematical model that quantifies the impact of volatility on systems engineering effort; the contributions of the research include a-) a set of project organizational, technical, and contextual factors ranked by subject matter experts in terms of their influence on requirements volatility; b-) the operationalization of the requirements volatility parameter in COSYMO through a 5-point rating scale; c-) a documented set of observations, developed from the literature and the research workshops, that describe the behaviors and effects of requirements volatility throughout the system life cycle. Advisors/Committee Members: Boehm, Barry W.Settles, F. Stan (Committee Chair), Valerdi, Ricardo (Committee Member), Ghanem, Roger G. (Committee Member).

Subjects/Keywords: systems engineering; requirements volatility; COSYSMO

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Peña, M. E. (2012). Quantifying the impact of requirements volatility on systems engineering effort. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/52794/rec/5345

Chicago Manual of Style (16th Edition):

Peña, Mauricio Eduardo. “Quantifying the impact of requirements volatility on systems engineering effort.” 2012. Doctoral Dissertation, University of Southern California. Accessed July 16, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/52794/rec/5345.

MLA Handbook (7th Edition):

Peña, Mauricio Eduardo. “Quantifying the impact of requirements volatility on systems engineering effort.” 2012. Web. 16 Jul 2019.

Vancouver:

Peña ME. Quantifying the impact of requirements volatility on systems engineering effort. [Internet] [Doctoral dissertation]. University of Southern California; 2012. [cited 2019 Jul 16]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/52794/rec/5345.

Council of Science Editors:

Peña ME. Quantifying the impact of requirements volatility on systems engineering effort. [Doctoral Dissertation]. University of Southern California; 2012. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/52794/rec/5345


University of Arizona

3. Dabkowski, Matthew Francis. Using Network Science to Estimate the Cost of Architectural Growth .

Degree: 2016, University of Arizona

Between 1997 and 2009, 47 major defense acquisition programs experienced cost overruns of at least 15% or 30% over their current or original baseline estimates, respectively (GAO, 2011, p. 1). Known formally as a Nunn-McCurdy breach (GAO, 2011, p. 1), the reasons for this excessive growth are myriad, although nearly 70% of the cases identified engineering and design issues as a contributing factor (GAO, 2011, p. 5). Accordingly, Congress legislatively acknowledged the need for change in 2009 with the passage of the Weapon Systems Acquisition Reform Act (WSARA, 2009), which mandated additional rigor and accountability in early life cycle (or Pre-Milestone A) cost estimation. Consistent with this effort, the Department of Defense has recently required more system specification earlier in the life cycle, notably the submission of detailed architectural models, and this has created opportunities for new approaches. In this dissertation, I describe my effort to transform one such model (or view), namely the SV-3, into computational knowledge that can be leveraged in Pre-Milestone A cost estimation and risk analysis. The principal contribution of my work is Algorithm 3-a novel, network science-based method for estimating the cost of unforeseen architectural growth in defense programs. Specifically, using number theory, network science, simulation, and statistical analysis, I simultaneously find the best fitting probability mass functions and strengths of preferential attachment for an incoming subsystem's interfaces, and I apply blockmodeling to find the SV-3's globally optimal macrostructure. Leveraging these inputs, I use Monte Carlo simulation and the Constructive Systems Engineering Cost Model to estimate the systems engineering effort required to connect a new subsystem to the existing architecture. This effort is chronicled by the five articles given in Appendices A through C, and it is summarized in Chapter 2.In addition to Algorithm 3, there are several important, tangential outcomes of this work, including: an explicit connection between Model Based System Engineering and parametric cost modeling, a general procedure for organizations to improve the measurement reliability of their early life cycle cost estimates, and several exact and heuristic methods for the blockmodeling of one-, two-, and mixed-mode networks. More generally, this research highlights the benefits of applying network science to systems engineering, and it reinforces the value of viewing architectural models as computational objects. Advisors/Committee Members: Valerdi, Ricardo (advisor), Head, Kenneth L. (committeemember), Furfaro, Roberto (committeemember), Breiger, Ronald L. (committeemember), Valerdi, Ricardo (committeemember).

Subjects/Keywords: community detection; COSYSMO; DoDAF; network science; preferential attachment; Systems & Industrial Engineering; blockmodeling

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Dabkowski, M. F. (2016). Using Network Science to Estimate the Cost of Architectural Growth . (Doctoral Dissertation). University of Arizona. Retrieved from http://hdl.handle.net/10150/612431

Chicago Manual of Style (16th Edition):

Dabkowski, Matthew Francis. “Using Network Science to Estimate the Cost of Architectural Growth .” 2016. Doctoral Dissertation, University of Arizona. Accessed July 16, 2019. http://hdl.handle.net/10150/612431.

MLA Handbook (7th Edition):

Dabkowski, Matthew Francis. “Using Network Science to Estimate the Cost of Architectural Growth .” 2016. Web. 16 Jul 2019.

Vancouver:

Dabkowski MF. Using Network Science to Estimate the Cost of Architectural Growth . [Internet] [Doctoral dissertation]. University of Arizona; 2016. [cited 2019 Jul 16]. Available from: http://hdl.handle.net/10150/612431.

Council of Science Editors:

Dabkowski MF. Using Network Science to Estimate the Cost of Architectural Growth . [Doctoral Dissertation]. University of Arizona; 2016. Available from: http://hdl.handle.net/10150/612431

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