Extraction of Behavioural Requirements for Simulation-based Performance Evaluation of Manufacturing Systems

Junpil Kim , Hyunbo Cho

Journal of Systems Science and Systems Engineering ›› 2019, Vol. 28 ›› Issue (5) : 555 -579.

PDF
Journal of Systems Science and Systems Engineering ›› 2019, Vol. 28 ›› Issue (5) : 555 -579. DOI: 10.1007/s11518-018-5394-4
Article

Extraction of Behavioural Requirements for Simulation-based Performance Evaluation of Manufacturing Systems

Author information +
History +
PDF

Abstract

A simulation model enables manufacturers to accurately evaluate the performance of their manufacturing systems. A vital input to build simulation models of manufacturing systems is the system behaviour, which is modelled based on extensive data on manufacturing systems and their elements. However, for outsourced manufacturing systems, data provided from external suppliers to manufacturers are generally limited and insufficient. Therefore, a solution is required to identify and secure system behaviour from available data. We propose herein a behaviour extraction process along with detailed activities and diagrams to extract system behaviour from limited data. By using the systems engineering standard ANSI/EIA-632, the proposed process systematically restructures available data on a manufacturing system and its elements and then provides complete system behaviour to build a simulation model. A case study on a cooling water control system in a hot strip mill convincingly demonstrates the applicability and effectiveness of the proposed process.

Keywords

Behaviour extraction / manufacturing systems / simulation model / system behaviour / systems engineering

Cite this article

Download citation ▾
Junpil Kim, Hyunbo Cho. Extraction of Behavioural Requirements for Simulation-based Performance Evaluation of Manufacturing Systems. Journal of Systems Science and Systems Engineering, 2019, 28(5): 555-579 DOI:10.1007/s11518-018-5394-4

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

Akşin OZ, Masini A. Effective strategies for internal outsourcing and offshoring of business services: an empirical investigation. Journal of Operations Management, 2008, 26(2): 239-256.

[2]

Akşin OZ, Véricourt FD, Karaesmen F. Call center outsourcing contract analysis and choice. Management Science, 2008, 54(2): 354-368.

[3]

Borissova D, Mustakerov I. An integrated framework of designing a decision support system for engineering predictive maintenance. International Journal of Information Technology & Knowledge, 2012, 6(4): 366-376.

[4]

Brall A. Availability modeling for the application of manufacturing equipment, 2002.

[5]

Buede DM. The Engineering Design of Systems: Models and Methods, 2009.

[6]

Bustinza-Sanchez OF, Arias-Aranda D, Gutuerrez-Gutierezz L. Outsourcing, competitive capabilities and performance: an empirical study in service firms. International Journal of Production Economics, 2010, 126(2): 276-288.

[7]

Carrie A. Simulation of Manufacturing Systems, 1988

[8]

Chen SS. A transaction cost rational for private branching and its implications for the choice of domestic vs offshore outsourcing. Journal of International Business Studies, 2009, 40(1): 156-175.

[9]

Chetouani Y. Design of a multi-model observerbased estimator for fault detection and isolation (FDI) strategy: application to a chemical reactor. Brazilian Journal of Chemical Engineering, 2008, 25(4): 777-788.

[10]

Cohen G, Dubois D, Quadrat J, Viot M. A linear-system-theoretic view of discrete-event processes and its use for performance evaluation in manufacturing. IEEE Transactions on Automatic Control, 1985, 30(3): 210-220.

[11]

Efthymiou K, Pagoropoulos A, Papakostas N, Mourtzis D. Manufacturing systems complexity: an assessment of manufacturing performance indicators unpredictability. CIRP Journal of Manufacturing Science and Technology, 2014, 7(4): 324-334.

[12]

Electronic Industries Alliance ANSI/EIA-63. Processes for engineering a system. Electronic Industries Alliance, 1998

[13]

Ellram LM, Tate WL, Billington C. Offshore outsourcing of professional services: a transaction cost economics perspective. Journal of Operations Management, 2008, 26(2): 148-163.

[14]

Gunasekaran A, Irani Z, Choy K, Filippi L, Papadopoulos T. Performance measures and metrics in outsourcing decisions: a review for research and applications. International Journal of Production Economics, 2015, 161: 153-166.

[15]

Harrison R, Vera D, Ahmad B. Engineering methods and tools for cyber-physical automation systems. Proceedings of the IEEE, 2016, 104(5): 973-985.

[16]

Haskins C. Systems engineering handbook: a guide for system life cycle processes and activities, V3.2.2, 2011

[17]

Hubbard PG. Operating manual for the IIHR hot-wire and hot-film anemometers, 1957

[18]

Kakabadse A, Kakabadse N. Outsourcing: current and future trends. Thunderbird International Business Review, 2005, 47(2): 183-204.

[19]

Liu Z, Nagurney A. Supply chain outsourcing under exchange rate risk and competition. Omega, 2011, 39(5): 539-549.

[20]

Martin JN. Process for engineering a system: an overview of the ANSI/EIA 632 standard and its heritage. Systems Engineering, 2000, 3(1): 1-26.

[21]

McIvor R. How the transaction cost and resourcebased theories of the firm inform outsourcing evaluation. Journal of Operations Management, 2009, 27(1): 45-63.

[22]

Monica Z. Virtual modelling of components of a production system as the tool of lean engineering, 2015, IOP Conference Series: Materials Science and Engineering, Mamaia, Romania, June 17–20, 2015.

[23]

Montgomery DC. Design and analysis of experiments, 2012

[24]

Naser J, Shankar R. Next step: on-line early fault detection, diagnostics, and prognostics, 2005

[25]

Pandilove Z, Milecki A, Nowak A, Górski F, Grajewski D, Ciglar D, Klaic M, Mulc T. Virtual modelling and simulation of a CNC machine feed drive system. Transactions of FAMENA, 2016, 39(4): 37-54.

[26]

Pang Y, Lodewks G. Simulation-based knowledge acquisition for intelligent belt conveyor monitoring. Particle & Particle Systems Characterization, 2007, 24(4–5): 360-364.

[27]

Perera T, Liyanage K. Methodology for rapid identification and collection of input data in the simulation of manufacturing systems. Simulation Practice and Theory, 2000, 7(7): 645-656.

[28]

Robinson S, Bhatia V. Secrets of successful simulation projects, 1995

[29]

Rossetti MD. Simulation modeling and arena, 2015.

[30]

Rosenman MA, Gero JS. The what, the how, and the why in design. International Journal of Applied Artificial Intelligence, 1994, 8(2): 199-218.

[31]

Sanders NR, Locke A, Moore CB, Autry CW. A multidimensional framework for understanding outsourcing arrangements. Journal of Supply Chain Management, 2007, 43(4): 3-15.

[32]

Schlager KJ. Systems engineering–key to modern development, 2009

[33]

Schoenherr T. Diffusion of online reverse auctions for b2b procurement: an exploratory study. International Journal of Operations & Production Management, 2008, 28(3): 259-278.

[34]

Simchi-Levi D, Kaminsky P, Simchi-Levi E. Designing and Managing the Supply Chain: Concepts, Strategies, and Case Studies, 2003.

[35]

Sivakumar A, Saravanan K. A simulation-based analysis for improvement of productivity in sick chemical dyeing factory: a research article. International Journal of Electronic Transport, 2011, 1(1): 96-110.

[36]

Smith DR. The design of divide and conquer algorithms. Science of Computer Programming, 1985, 5: 37-58.

[37]

Stefano AD, Bello LL, Mirabella O. Virtual plant: a distributed environment for distance monitoring and control of industrial plants, 1997

[38]

Sullivan GP, Pugh R, Melendez AP, Hunt WD. Operation & maintenance best practice–a guide to achieving operational efficiency, 2010.

[39]

Trybula WJ. Building simulation models without data. IEEE International Conference on Systems, Man, and Cybernetics, 1994

[40]

Uzsoy R, Lee C, Martin-Vega LA. A review of production planning and scheduling models in the semiconductor industry part I: system characteristics, performance evaluation and production planning. IIE Transactions, 1992, 24(4): 47-60.

[41]

Wilo Wilo-Economy MHI » Economy MHI 202, 2016

[42]

Xu H, Guo J, Zeng H, Xiao Z. Study on distributed cooperative maintenance decision supporting system for hydropower plant, 2007.

AI Summary AI Mindmap
PDF

130

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/