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Abstract: It is essential to manage customers’ diverse desires and to keep manufacturing costs as low as possible for survival in competition and eventually in production. Sharing resources in manufacturing for different products is a vital method of accomplishing this goal. The advantages of using a common process in production are stated in the literature. However, the mathematical models as well as simulation or conceptual models are not sufficient. The main objective of this paper is to develop mathematical models for multiproduct and multistage production under quality and breakdown uncertainties. The idea of the process commonality is incorporated in the proposed models. The models are validated by primary data collected from a Malaysian company and comparison of the timely requirement schedules of earlier MRP II and the proposed models under stable and perfect production environments. An appreciable convergence of the outcomes is observed. However, the proposed models are carrying additional information about the available locations of the parts in a time frame. After validation, the effects of process commonality on cost, capacity and the requirement schedule under uncertainties are examined. It is observed that the use of common processes in manufacturing is always better than the non-commonality scenario in terms of production cost. However, the increase in capacity requirement for commonality designs is higher for an ideal system, while it is less when the system suffers from breakdowns and a quality problem.

[1]Arruda, E.F., do Val, J.B.R., 2008. Stability and optimality of a multi-product production and storage system under demand uncertainty. European Journal of Operational Research, 188(2):406-427.

[2]Balakrishnan, A., Brown, S., 1996. Process planning for aluminum tubes: An engineering operations perspective. Operations Research, 44(1):7-20.

[3]Balakrishnan, J., Cheng, C.H., 2007. Multi-period planning and uncertainty issues in cellular manufacturing: A review and future directions. European Journal of Operational Research, 177(1):281-309.

[4]Farrell, R.S., Simpson, T.W., 2003. Product platform design to improve commonality in custom products. Journal of Intelligent Manufacturing, 14(6):541-556.

[5]Fixson, S.K., 2007. Modularity and commonality research: past developments and future opportunities. Concurrent Engineering: Research and Applications, 15(2):85-111.

[6]Heese, H.S., Swaminathan, J.M., 2006. Product line design with component commonality and cost-reduction effort. Manufacturing & Service Operations Management, 8(2):206-219.

[7]Jiao, J.X., Tseng, M.M., 1999. A methodology of developing product family architecture for mass customization. Journal of Intelligent Manufacturing, 10(1):3-20.

[8]Jiao, J.X., Tseng, M.M., 2000. Understanding product family for mass customization by developing commonality indices. Journal of Engineering Design, 11(3):225-243.

[9]Jiao, J.X., Tseng, M.M., Ma, Q.H., Zhou, Y., 2000. Generic bill-of-material-and-operations for high-variety production management. Concurrent Engineering: Research and Applications, 8(4):297-321.

[10]Kamrani, A.K., Salhieh, S.E.M., 2002. Product Design for Modularity. Springer.

[11]Kim, J., Gershwin, S.B., 2005. Integrated quality and quantity modeling of a production line. OR Spectrum, 27(2-3):287-314.

[12]Koh, S.C.L., Gunasekaran, A., 2006. A knowledge management approach for managing uncertainty in manufacturing. Industrial Management & Data Systems, 106(4):439-459.

[13]Koh, S.C.L., Jones, M.H., Saad, S.M., Arunachalam, A., Gunasekaran, A., 2000. Measuring uncertainties in MRP environments. Logistics Information Management, 13(3):177-183.

[14]Koh, S.C.L., Simpson, M., Lin, Y., 2006. Uncertainty and contingency plans in ERP-controlled manufacturing environments. Journal of Enterprise Information Management, 19(6):625-645.

[15]Mayer, M., Nusswald, M., 2001. Improving manufacturing costs and lead times with quality-oriented operating curves. Journal of Materials Processing Technology, 119(1-3):83-89.

[16]Mukhopadhyay, S.K., Ma, H., 2009. Joint procurement and production decisions in remanufacturing under quality and demand uncertainty. International Journal of Production Economics, 120(1):5-17.

[17]Qin, H.B., Zhong, Y.F., Xiao, R.B., Zhang, W.G., 2005. Product platform commonization: Platform construction and platform elements capture. The International Journal of Advanced Manufacturing Technology, 25(11-12):1071-1077.

[18]Shenoy, D., Bhadury, B., 1998. Maintenance Resources Management: Adapting MRP. Taylor & Francis, London.

[19]Ulrich, K.T., Eppinger, S.D., 2000. Product Design and Development. McGraw-Hill, Boston, USA.

[20]Voß, S., Woodruff, D., 2003. Introduction to Computational Optimization Models for Production Planning in a Supply Chain. Springer-Verlag, New York Inc.

[21]Wazed, M.A., Ahmed, S., Nukman, Y., 2009. Uncertainty factors in real manufacturing environment. Australian Journal of Basic and Applied Sciences Research, 3(2):342-351.

[22]Wazed, M.A., Ahmed, S., Nukman, Y., 2010a. Commonality in manufacturing resources planning—issues and models: a review. European Journal of Industrial Engineering, 4(2):167-188.

[23]Wazed, M.A., Ahmed, S., Nukman, Y., 2010b. Impacts of quality and processing time uncertainties in multistage production system. International Journal of the Physical Sciences, 5(6):814-825.

[24]Wazed, M.A., Ahmed, S., Nukman, Y., 2010c. A review of manufacturing resources planning models under different uncertainties: state-of-the-art and future directions. South African Journal of Industrial Engineering, 21(1):17-33.

[25]Wazed, M.A., Ahmed, S., Nukman, Y., 2011. Application of Taguchi method to analyse the impacts of common process and batch size in multistage production system under uncertain conditions. European Journal of Industrial Engineering, 5(2):215-231.

[26]Xu, H.M., Li, D.B., 2007. A meta-modeling paradigm of the manufacturing resources using mathematical logic for process planning. The International Journal of Advanced Manufacturing Technology, 36(9-10):1022-1031.