Abstract
This chapter introduces a computational model to support the system user along the decision making process regarding the type and timing of system configurations to be acquired and the appropriate flexibility degree. Based on the empirical evidence described in Chap. 2, Focused Flexibility Manufacturing Systems (FFMS) seem to be a viable alternative to solve the classical dichotomy between rigid and fully flexible systems. This focused flexibility concept, as introduced in Chap. 3, can be a valuable solution for manufacturing firms to satisfy the market needs. Previous chapters tackled the system flexibility design process from the machine tool builder standpoint. Once the potential system configurations have been defined and the capital outlays required for acquiring and/or transitioning among them have been quantified, the machine tool builder makes an offer to the system user. The latter needs to select the most profitable solution by evaluating the performance generated by each configuration under different demand profiles from a financial point of view. This decision is supported by two optimization models, one static – i.e. not affected by the time dimension – and one dynamic, wrapped up in a valuation model which simulates a profit function on different variable values over a multi-period time horizon, matching the user’s expected demand levels with his manufacturing strategies.
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References
Bengtsson J, Olhager J (2001) Valuation of product-mix flexibility using real options. Int J Prod Econ 74:213–224
Cantamessa M, Fichera S, Grieco A, Perrone G, Tolio T (2007) Methodologies and tools to design production systems with focused flexibility. Proceeding of the 4th intenrational conference on digital enterprise technology, Bath, UK, 19–21 September, pp 627–636
Cheng L, Subrahmanian E, Westerberg A W (2003) Design and planning under uncertainty: issues on problem formulation and solution. Comput Chem Eng 27:781–801
Choi S, Kim J (1998) A study of measurement of comprehensive flexibility in manufacturing systems. Comput Ind Eng 34(1):103–118
Elkins D A, Huang N, Alden J M (2004) Agile manufacturing systems in the automotive industry. Int J Prod Econ 91:201–214
Kulatilaka N (1988) Valuing the flexibility of flexible manufacturing systems. IEEE Trans Eng Manag 35(4):250–257
Matta A, Tolio T, Karaesmen F, Dallery Y (2001) An integer approach for the configuration of automated manufacturing systems. Robot Compute Integr Manuf 17:19–26
Matta A, Tomasella M, Valente A (2008) Impact of ramp-up on the optimal capacity reconfiguration policy. Int J Flex Manuf Syst 19(3):173–194
Perrone G, Amico M, Lo Nigro G, Noto La Diega S (2002) Long term capacity decisions in uncertain markets for advanced manufacturing systems incorporating scope economies. Eur J Oper Res 143:125–137
Tolio T, Valente A (2006) An approach to design the flexibility degree in flexible manufacturing system. Proc of Flex Autom & Intell Manuf Conf, Limerick, Ireland, June 25–27, 2006, pp 1229–1236
Tolio T, Valente A (2007) A stochastic approach to design the flexibility degree in manufacturing systems with focused flexibility. Proceedings of DET2007 – international conference in digital enterprise, Bath, UK, 19–21 September, pp 380–390
Tolio T, Valente A (2008) A stochastic programming approach to design the production system flexibility considering the evolution of the part families. To appear in Int J Manuf Technol Manag – Special Issue on Reconfigurable Manufacturing Systems
Tolio T, Terkaj W, Valente A (2007) Focused flexibility and production system evolution. Proceedings of 2nd international conference on changeable, Agile, reconfigurable and virtual production. Toronto, Ontario, Canada, July 23–24, 2007
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© 2009 Springer-Verlag Berlin Heidelberg
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Cantamessa, M., Capello, C., Cordella, G. (2009). System Life-Cycle Planning. In: Tolio, T. (eds) Design of Flexible Production Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85414-2_8
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DOI: https://doi.org/10.1007/978-3-540-85414-2_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-85413-5
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