Clustering Based Heuristics for Aligning Master Production Schedule and Delivery Schedule

Abstract

Abstract Making a Master Production Schedule (MPS) is a very important activity for a manufacturing industry. This is due to the fact that MPS serves as an input for material and production planning. Between the years 2020 and 2022, there were significant fluctuations observed in container freight rates. As response, a lot of manufacturing industry focus on optimizing their container delivery schedule. Hence, there is a need for aligning the master production schedule with the delivery schedule. This paper presents the development of a novel heuristic approach to address problems with the creation of MPS. Specifically, the focus is on the situation where container delivery schedules are prearranged and serve as a main input for creating the MPS. There are two objective functions that are going to be reached: 1) minimize the total number of product variations or Stock Keeping Units (SKU) per month; and 2) minimize the number of SKU per container. The proposed heuristic approach uses the similarity concept to group objects in a clustering technique. It is then implemented in a real-world case of a furniture manufacturing company. Further results were obtained and then compared to the heuristic technology that had previously been used by business entities. The results show that the number of product variations (SKU) that must be performed per month is 10% lower than that of the existing heuristic. In addition, the ratio of SKU variations per container is 9% lower than that of the existing heuristic. The time required to complete the task of creating MPS is less than one minute, as opposed to the one working day required by the company’s existing heuristic.