Optimal Allocation of Module Inventories for the Estimation of Earlier Due Dates Subject to Volatile Customer Demand
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概要
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The present paper proposes a methodology for maximizing the effect of module inventories, which are allocated at multiple points in manufacturing processes, for the estimation of earlier due dates in make-to-order production. In this research, modules are defined as semi-finished products or processed parts that can be used for producing plural final products or higher-level semi-finished products with the intention of increasing operational efficiency. The use of modules allows manufacturing costs to be reduced in the present industrial environment of product diversification and helps to secure customer orders through estimating earlier due dates. However, the strategy of holding module inventories is accompanied by the burden of incurring unnecessary inventory investment, inventory carrying cost and obsolescence cost. Therefore, the strategy must be applied by a method that minimizes such performance measures regarding the module inventories, considering trends in customer demand and the comprehensive product structure, which is defined as a network of plural product structures. Specifically, the positions and levels of module inventories in the given comprehensive product structure are optimized using a genetic algorithm. All final products, semi-finished products and processed parts including modules are produced based on customer orders. However, modules can be produced based on the manufacturing orders released according to a make-to-stock production strategy when the required facilities are not busy. This situation sometimes occurs because customer demand is generally volatile. The module inventories are controlled by the Max-Min reordering policy, where Max is the only parameter if Min can be set equal to Max. In the present paper, the values of parameter Max, which control the module inventory levels, are optimized. Two measures of production performance are considered. One is the average lead time for all customer orders, and the other is the total inventory investment required for holding modules in a comprehensive product structure. The computation results were obtained through performing a number of simulation runs using a due-date estimation algorithm in a framework of multiple-objective optimization. As a result, it was proven that the Pareto-optimal solutions, which involved information on the optimal allocation of module inventories under the given customer demand patterns and inventory investment coefficients assigned to modules, could be successfully found.
- 2008-06-15
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- Optimal Allocation of Module Inventories for the Estimation of Earlier Due Dates Subject to Volatile Customer Demand