Development of manufacturing - distribution plan considering quality cost

Abstract

In the current complex business world, making decisions on the manufacturing-distribution problem is a tedious task to the supply chain managers. Solving mathematical model with many entities requires a suitable algorithm for optimum results which increase the profitability of any industrial activity. Any model without considering the percentage of rejection in a particular plant, will not supply the right quality and quantity of products to the customers. Here, a mathematical model is developed by considering the quality cost in addition to normal time manufacturing cost, subcontracting cost, transportation cost, overtime manufacturing cost, holding cost, cost of hiring, and cost of firing. Mixed integer linear programming (MILP) model is developed and solved using a modified heuristic based discrete particle swarm algorithm (DPSA) which generates the manufacturing-distribution plan in order to bring the total cost minimum for the bearing industry under study. The normal time manufacturing loss and the overtime loss in terms of product quantity and cost are calculated and manufactured.