IMPACT OF DYNAMIC LOT SIZING TECHNIQUES ON COSTS OF MATERIAL REQUIREMENT PLANNING

Abstract

Since the beginning of computerised production management, material requirement planning has been a central part of optimising company processes. The reason for this is that the precise computation and optimisation of material requirements can result in significant cost savings for the company in the short term, which can have a significant impact on the overall efficiency of the company's processes. To this end, the definition of the material requirements for production has been complemented by new optimisation methods that can be used to further improve the solution of the problem of dynamic lot sizing. In this paper, the authors investigate the effectiveness of the Wagner-Whitin and Silver-Meal algorithms through a scenario analysis. The results demonstrate that significant cost savings can be achieved by using both algorithms.