Integrated model for line balancing with workstation inventory management

Roy, D.; khan, D.

Abstract: In this paper, we address the optimization of an integrated line balancing process with workstation inventory management. While doing so, we have studied the interconnection between line balancing and its conversion process. Almost each and every moderate to large manufacturing industry depends on a long and integrated supply chain, consisting of inbound logistic, conversion process and outbound logistic. In this sense an approach addresses a very general problem of integrated line balancing. Research works reported in the literature so far mainly deals with minimization of cost for inbound and outbound logistic subsystems. In most of the cases conversion process has been ignored. We suggest a generic approach for linking the balancing of the line of production in the conversion area with the customers’ rate of demand in the market and for configuring the related stock chambers. Thus, the main aim of this paper is to translate the underlying problem in the form of mixed nonlinear programming problem and design the optimum supply chain so that the total inventory cost and the cost of balancing loss of the conversion process is jointly minimized and ideal cycle time of the production process is determined along with ideal sizes of the stock chambers. A numerical example has been added to demonstrate the suitability of our approach.

How to cite this paper

        APA: Roy, D & khan, D. (2010). Integrated model for line balancing with workstation inventory management. International Journal of Industrial Engineering Computations, 1(2), 139-146.
    

        Chicago/Turabian: Roy, D & khan, D. 2010. "Integrated model for line balancing with workstation inventory management." International Journal of Industrial Engineering Computations 1, no. 2 (2010): 139-146.
    

        AMA: Roy, D & khan, D. Integrated model for line balancing with workstation inventory management. International Journal of Industrial Engineering Computations. 2010;1(2):139-146.
    

References

Aitken, J., Childerhouse, P., & Towill, D. (2001). The impact of product life cycle on supply chain strategy. 16th International Conference on Production Research.

Bohme, T., Childerhouse, P., Deakins, E., & Corner, J. (2008a). Balancing power and dependency in buyer-supplier relationships. International Journal of Electronic Customer Relationship Management, 2(2), 120-139.

Bohme, T., Childerhouse, P., Deakins, E., Potter, A., & Towill, D. (2008b). Why diagnosis supply chain uncertainty? Operations Management, 34 (2), 19-23.

Childerhouse, P., Disney, S., & Towill, D. (2007). The effects of schedule volatility on supply chain performance. 19th International Conference on Production Research (ICPR19), Valparaiso, Chile.

Childerhouse, P. & Towill, D. (2002). Analysis of the factors affecting real-world value stream performance. International Journal of Production Research, 40 (15), 3499-3518.

Mondal, S. & Tiwari, M.K. (2003). Formulation of mobile agents for integration of supply chain using the KLAIM concept. International Journal of Production Research, 41(1), 97- 119.

Pontrandolfo, P., Gosavi, A., Okogbaa, O.G., & Das, T.K. (2002). Global supply chain management: a reinforcement learning approach. International Journal of Production Research, 40(6), 1299- 1317.

Wild, R. (2004), Operation Management. Thomson.

Scholl, A. (1999). Balancing and Sequencing of Assembly Lines. Second Edition, Physica-verlag Heidelberg.

Scholl, A., & Becker, C. (2006). State-of-the-art exact and heuristic solution procedures for simple assembly line balancing. European Journal of Operational Research, 168, 666-693.

Shen, W., Kremer, R., Ulieru, M., & Norrie, D. (2003). A collaborative agent-based infrastructure for Internet-enabled collaborative enterprise. International Journal of Production Research, 41(8), 1621- 1638.

Talluri, S., Narasimhan, R., & Viswanathan, S. (2007). Information technologies for procurement decisions: A decision support system for multi-attribute e-reverse auctions. International Journal of Production Research, 45(11), 2615- 2628.

Wadhwa, W., Saxena, A., & Chan, F.T.S. (2003). Framework for flexibility in dynamic supply chain management. International Journal of Production Research, 46(6), 1374- 1404.

Zhao, X. & Xie, J. (2002). Forecasting Errors and the Value of Information Sharing in a Supply Chain. International Journal of Production Research, 40(2), 311-335.

Zhao, X., Xie, J., & Leung, J. (2002). The Impact of Forecasting Models on the Value of Information Sharing in a Supply Chain. European Journal of Operations Research, 142(2), 321-344.

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