Aggregate Production Planning Considering Performance Evolution: A Case Study

Abstract

Due to the violent market competition, organizations should respond quickly to customer needs. This strategic objective can be reached through the development of robust production planning. One of the most important factors in production planning is the workforce productivity which is a dynamic manufacturing property, i.e. the workforce productivity increases thanks to in-job training. This phenomenon is known as production progress function or work-based-learning. Considering this phenomenon in industrial planning can lead to robust manufacturing plans. The current study introduces a novel model for a medium term production planning, which used to find the yearly optimum aggregate production plan in order to minimize the total production costs in respecting the operational constraints and considering the production progress function. The resultant model is a linear mixed integer program that can be solved optimally. The data used in validating and running the model was taken from an Egyptian factory that is dedicated to produce electric motors. The model was solved optimally using ILOG CPLEX Software. By comparing the results of this study against the adopted approach in the factory; one can find that the model succeeded to minimize the production costs by about 5.43 % for first year, 2.66% for the second, and 1.86% for the third one. In monetary units these percentages can be translated respectively to 11.7 million L.E., 6.3 million L.E., and 4.7 million L.E.