Evaluating Quantity Management Policies

On any manufacturing floor, there must be policies in place to support the cost effective utilization of capacity and movement of work in progress (WIP). This is true whether the factory is building to stock or to order, whether the process is fabrication or assembly (or both), whether execution is primarily manual or highly automated. The problem for any manufacturing organization is to select and implement the most appropriate quantity management policy to meet its business goals, realizing that this policy will have to evolve over time given the process of manufacturing technology (both equiptment and process), the continuous flow of new products and the dynamics of the global marketplace. A source of confusion for maufacturing personnel is the variety of quantity management policies available in the technical literature. The "kanban" approach controls small buffers at each station in a manufacturing line as a way to control the overall factory performance (Just-in-Time Manufacturing, ed. C. A. Voss, IFS Publications Ltd., U.K. 1987). The "hedging" approach exercises global factory control by controlling production rates at each individual station (S. Gershwin, Hierarchal Flow Control, Proc. IEEE, vol. 77, no. 1, pp 195-209, 1989). The "contraint" approach uses one buffer and one rate to control the performance of the entire factory (The Goal, E. M. Goldratt and J. Cox, North River Press Inc., 1986). This list could go on.

Although in principal, given an appropriate model of the factory under consideration, each approach could be simulated or subjected to analysis, such comparison is a practical nightmare. Commercial simulation packages do not support such high level strategies. Although they do allow users to exit into their implementation languages to construct custom features, building these high level quantity management policies from scratch is a serious undertaking. Furthermore, it is not the case that analysismethods exist that are powerful enough to directly compare such sophisticated policies. In any case, it is not often that manufacturing organizations have personnel with the skill set or time to build these custom features for simulators or to develop new analysis methods.

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