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ISSN:2222-7059 (Print);EISSN: 2222-7067 (Online)
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Title : Integrated Capacity Coordination-matching Process in Make-to-forecast Production Environments
Author(s) : Hamed Rafiei, Masoud Rabbani, Hanan Mostaghimi
Author affiliation : Hamed Rafiei, Masoud Rabbani, School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, P.O. Box: 11155-4563, Iran
Hanan Mostaghimi, Industrial and Manufacturing Systems Engineering, University of Winsor, Ontario, Canada
Corresponding author img Corresponding author at : Corresponding author img  

Although Make-To-Forecast (MTF) production environment is one of production systems have been utilized in real industrial world, academicians have not paid considerable attention to this field of production planning. In this paper, a novel capacity coordination framework in MTF production environments is proposed. The proposed framework includes four steps. At the first step, production value is determined based on Analytic Hierarchy Process (AHP) method upon which estimated capacity is allocated to correction process in the second step. Next, product lot sizes are optimized in the third stage using a proposed mathematical programming model. The final step is related to order acceptance/rejection and matching process. In this regard, negotiability of receiving orders is considered in order to make proper acceptance/rejection decision. Also, an assignment model is developed for the matching process, which is tackled using the well-known Hungarian method. Finally, results of a real-world industrial case study are reported to show performance of the proposed framework.

Key words:Capacity coordination; make-to-forecast; matching process; order acceptance/rejection; production plannin

Cite it:
Hamed Rafiei, Masoud Rabbani, Hanan Mostaghimi, Integrated Capacity Coordination-matching Process in Make-to-forecast Production Environments, Advances in Industrial Engineering and Management, Vol.3, No.4, 2014, pp.63-76, doi: 10.7508/AIEM-V3-N4-63-76

Full Text : PDF(size: 647.16 kB, pp. 63-76, Download times:232)

DOI : 10.7508/AIEM-V3-N4-63-76

[1] T.E. Vollmann, W.L. Berry, D.C. Whybark, F.R. Jacobs, 2005. Manufacturing planning and control systems for supply chain management. Irwin, Boston.
[2] U. Akinc, J. Meredith, 2006. “Choosing the appropriate capacity for make-to-forecast production environment using a Markov analysis approach”, IIE Trans, vol. 38, pp. 847-858.
[3] A.S. Raturi, J.R. Meredith, D.M. Mccutcheon, J.D. Camm, 1990. “Coping with the build-to-forecast environment”, J Oper Manag, vol. 9, pp. 230-249.
[4] A.C. Hax, H.C. Meal, 1975. “Hierarchical integration of production planning and scheduling. In: TIMS studies in the management sciences. North-Holland, Amsterdam, pp. 53-69.
[5] J. Ashayeri, W.J. Selen, 2001. “Order selection optimization in hybrid make-to-order and make-to-stock markets”, J Oper Res Soc, vol. 52, pp. 1098-1106.
[6] C.A. Soman, D.P. van Donk, G. Gaalman, 2004. “Combined make-to-order and make-to-stock in a food production system,” Int J Prod Econ, vol. 90, pp. 223-235.
[7] H. Rafiei, M. Rabbani, 2012. “Capacity coordination in hybrid make-to-stock/ make-to-order production environments”, Int J Prod Res, vol. 50, pp. 773-789.
[8] C.A. Soman, D.P. van Donk, G. Gaalman, 2006. “Comparison of dynamic scheduling policies for hybrid make-to-order and make-to-stock production systems with stochastic demand”, Int J Prod Econ, vol. 104, pp. 441-453.
[9] N. Zaerpour, M. Rabbani, A.H. Gharegozli, R. Tavakkoli-Moghaddam, 2008. “Make to order or make to stock decision by a novel hybrid approach”, Adv Eng Inf, vol. 22, pp. 186-201.
[10] N. Zaerpour, M. Rabbani, A.H. Gharegozli, R. Tavakkoli-Moghaddam, 2009. “A comprehensive decision making structure for partitioning of make-to-order, make-to-stock and hybrid products”, Soft Comput, vol. 13, pp. 1035-1054.
[11] H. Rafiei, M. Rabbani, M. Alimardani, 2013. “Novel bi-level hierarchical production planning in hybrid MTS/MTO production contexts”, Int J Prod Res, vol. 51, pp. 1331-1346.
[12] J. Meredith, U Aknic, 2007. “Characterizing and structuring a new make-to-forecast production strategy”, J Oper Manag, vol. 25, pp. 623-642.
[13] D.P. van Donk, 2001. “Make to stock or make to order: the decoupling point in the food processing industries”, Int J Prod Econ, vol. 69, no. 3, pp. 297-306.
[14] J. Olhager, 2003. “Strategic positioning of order penetration point”, Int J Prod Econ, vol. 85, no. 3, pp. 319-329.
[15] M. Ebadian, M. Rabbani, F. Jolai, S.A. Torabi, R. Tavakkoli-Moghadam, 2008. “A new decision-making structure for the order entry stage in make to order environments”, Int J Prod Econ, vol. 111, pp. 351-367.
[16] M. Ebadian, M. Rabbani, S.A. Torabi, F. Jolai, 2009. “Hierarchical production planning and scheduling in make-to-order environments: reaching short and reliable delivery dates”, Int J Prod Res, vol. 47, pp. 5761-5789.
[17] H.L. Lee, C.S. Tang, 1997. “Modelling the costs and benefits of delayed product differentiation”, Manag Sci, vol. 43, no. 1, pp. 40-53.
[18] K. Kim, D. Chhajed, 2000. “Commonality in product design: Cost saving, valuation change and cannibalization”, Eur J Oper Res, vol. 125, no. 3, pp. 602-621.
[19] D. Gupta, S. Benjaafar, 2004. “Make-to-order, make-to-stock, or delay product differentiation? A common framework for modeling and analysis”, IIE Trans, vol. 36, pp. 529-546.
[20] T.L. Saaty, 1980. The analytic hierarchy process, planning, priority settings, resource allocation. New York : McGraw-Hill.
[21] B. Kingsman, L. Hendry, 2002. “The relative contribution of input and output controls on the performance of a workload control system in make-to-order companies”, Prod Plan Control, vol. 13, pp. 579-590.
[22] M. Kalantari, M. Rabbani, M. Ebadian, 2011. “A decision support system for order acceptance/rejection in hybrid MTS/MTO production systems”, Appl Math Model, vol. 35, pp. 1363-1377.
[23] F.F. Easton, D.R. Moodie, 1999. “Pricing and lead time decision for make-to-order firms with contingent orders”, Eur J Oper Res, vol. 16, pp. 305-318.

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