Abstract
Minimising the total delay in the procurement of materials is one of the most important objectives in the production management of a manufacturing shop with multi-assembly products. This criterion is affected by the lot sizes of the materials used in the assembly of final products. Therefore, the optimum production lot size of products should be determined to minimise the total delay. In this paper, four types of delay, namely priority, processing, staging and requirements delay are formulated based on a multi-product MRP (MP-MRP) graph activity. To optimise lot sizes and minimise total delay (TD), the lead time and due date of products are considered. Artificial neural network (ANN) and regression methods are then applied to obtain the nonlinear function of TD versus the lot sizes of products. The delay-based lot size approximation (DBLSA) algorithm is proposed for obtaining the approximated lot size of products. Results obtained for a 2P-MRP case study show the effectiveness of the solutions obtained by the proposed algorithm.
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