Analyzing the effectiveness and ranking engineering changes for complex engineered systems viability improvement
Subject Areas :مالک طهوری 1 , جعفر قیدرخلجانی 2 , Mohammad Hussein Karimi gavareshki 3
1 - Faculty of Management, Imam Khomeini International University, Qazvin, Iran
2 - Associate Professor, University Complex of Management and Industrial Engineering, Malik Ashtar University of Technology
3 - Associate Professor, University Complex of Management and Industrial Engineering, Malik Ashtar University of Technology
Keywords: Complex Engineered Systems (CES), engineering changes, Viability, Uncertainty, Electre, Monte Carlo.,
Abstract :
Viability is one of the non-functional requirements in the complex engineered systems literature which is uses for assessing the ability of complex engineered systems under uncertainty. Usually in the earlier phase of systems design and development, systems stakeholders have the request for increased value of viability and for this mean, system engineers propose several engineering changes. The main problem here is the lack of a method for analyzing the effectiveness of these engineering changes and also ranking them based on different criteria such as cost, time and risk. For promoting this gap, in this paper we propose a 11 step model for analyzing the effectiveness and also ranking the engineering changes for increasing systems viability with the use of Monte Carlo and Electre methods. The applicability of the model is shown by using illustrative example of space system datas
L. Chung, B. A. Nixon, E. Yu, and J. Mylopoulos, Non-Functional Requirements in Software Engineering. Boston, MA: Springer US, 2000.#
[2] D. Mairiza, D. Zowghi, and N. Nurmuliani, “An investigation into the notion of non-functional requirements,” in Proceedings of the 2010 ACM Symposium on Applied Computing - SAC ’10, 2010, p. 311.#
[3] B. W. Boehm, J. R. Brown, and M. Lipow, “Quantitative evaluation of software quality,” in IN ICSE ’76: PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING, 1976, pp. 592--605.#
[4] J. P. Cavano, J. A. McCall, J. P. Cavano, J. A. McCall, J. P. Cavano, and J. A. McCall, “A framework for the measurement of software quality,” in Proceedings of the software quality assurance workshop on Functional and performance issues -, 1978, vol. 7, no. 3–4, pp. 133–139.#
[5] J. A. McCall and M. T. Matsumoto, “Software Quality Metrics Enhancements. Volume 1.” 1980.#
[6] T. P. Bowen, G. B. Wigle, and J. T. Tsai, Specification of Software Quality Attributes. Volume 3. Software Quality Evaluation Guidebook. BOEING AEROSPACE CO SEATTLE WA, 1985.#
[7] K. M. Adams, Nonfunctional Requirements in Systems Analysis and Design, vol. 28. 2015.#
[8] M. Tahoori, J. Gheidar-Kheljani, and M. H. K. Gavara, “Design for Viability of Complex Engineered Systems under Uncertainty,” Industrial Engineering & Management Systems, vol. 16, no. 4, pp. 619–631, Dec. 2017.#
[9] N. Kattner and U. Lindemann, “Performance Metrics in Engineering Change Management: Towards a Methodology to Investigate the Efficiency of Handling Engineering Changes,” in 2017 Portland International Conference on Management of Engineering and Technology (PICMET), 2017, pp. 1–8.#
[10] T. E. Serapelo, L. Erasmus, and J.-H. Pretorius, “Engineering Change Management Impact on Project Success within a South African Petrochemical Company,” in 2017 Portland International Conference on Management of Engineering and Technology (PICMET), 2017, pp. 1–8.#
[11] W. Wade and N. Wagner, Scenario planning : a field guide to the future. Wiley, 2012.#
[12] A. Stevenson, Oxford dictionary of English. Oxford University Press, 2010.#
[13] R. E. (Ronnie E. 1970- Thebeau, “Knowledge management of system interfaces and interactions from product development processes,” 2001.#
[14] K. C. . 1976- Kalligeros, “Platforms and real options in large-scale engineering systems,” 2006.#
[15] A. Skabar and K. Abdalgader, “Clustering Sentence-Level Text Using a Novel Fuzzy Relational Clustering Algorithm,” IEEE Transactions on Knowledge and Data Engineering, vol. 25, no. 1, pp. 62–75, Jan. 2013.#
[16] P. D. Grünwald, The minimum description length principle. MIT Press, 2007.#
[17] J. Rissanen and J., “Modeling by shortest data description,” Automatica, vol. 14, no. 5, pp. 465–471, Sep. 1978.#
[18] A. M. Ross, D. B. Stein, and D. E. Hastings, “Multi-Attribute Tradespace Exploration for Survivability,” Journal of Spacecraft and Rockets, vol. 51, no. 5, pp. 1735–1752, Sep. 2014.#
[19] S. Jackson and T. L. J. Ferris, “Resilience principles for engineered systems,” Systems Engineering, vol. 16, no. 2, pp. 152–164, Jun. 2013.#
[20] P. A. A. Carrillo, J. C. L. Lopez, and D. A. G. Chavira, “Deriving parameters and preferential model for a total order in ELECTRE III,” in 2017 4th International Conference on Systems and Informatics (ICSAI), 2017, pp. 532–537.#
[21] M. E. Sosa, S. D. Eppinger, and C. M. Rowles, “A Network Approach to Define Modularity of Components in Complex Products,” Journal of Mechanical Design, vol. 129, no. 11, p. 1118, 2007.#