Optimization of Mass Customization Process using Quantum-inspired Evolutionary Algorithm in Industry 4.0

Abstract

Industry 4.0 makes the production process more flexible, which enables emerging of the Mass Customization production model. The technologies used in Industry 4.0 make allow us to optimize the processes in an easy way. In this study, it is aimed to achieve a more efficient production process for Industry 4.0 based Mass Customization. In a factory, incoming orders are produced by the sequence of arrival time. This study aims to achieve more energy-efficient production by optimizing the sequence of orders. Since obtaining the actual best solution is computationally complex, permutation-coded Quantuminspired Evolutionary Algorithm is used. Experimental results show that Quantum-inspired Evolutionary Algorithm has a good convergence rate and approximately 40% of energy gain is achieved in a reasonable time. By the studies done, Industry 4.0 become one step closer to more energy-efficient production which is one of the aims.