A Single Side Priority Based GA Approach for 3D Printing Center Integration to Spare Part Supply Chain in Automotive Industry

Abstract

Developments in manufacturing technologies and new opportunities lead to reconsider the design of the spare part supply chains. In this paper, 3D printing technology, which is one of the most critical applications of industry 4.0 has been studied for examining new opportunities. Manufacturing facilities, 3D printing centers, warehouses, distribution centers have been taken into account in supply chain. Quantity of products, timing, technology to be used, assigned facility, investments and warehouse for product storage are considered as decision variables. The output of this study is to propose a mathematical model that minimizes the sum of production, distribution, and inventory holding costs. The main constraints of the model are the capacity of the manufacturing facilities & 3D printing centers, warehouse areas, and demands. Inventory holding cost, unit transportation cost, production time and cost, needed space, distances between facilities, transportation time, bill of materials, demand in periods, and investment cost parameters have been used in a mathematical model and reached the optimum solution with branch and bound algorithm. Because of the nature of the problem, solution time takes longer when the problem size is larger. Therefore, in this paper, a unique Single Side Priority Based Algorithm (SSPBA) has been developed in genetic algorithm approach to find near optimum results.

Keywords

• genetic algorithm
• industry 4.0
• spare part supply chain
• 3D printing