Simulation optimization applied to production scheduling in the era of industry 4.0: A review and future roadmap
Amir Ghasemi, Fatemeh Farajzadeh, Cathal Heavey, John Fowler, Chrissoleon T. Papadopoulos
Abstract
Production Scheduling (PS) is an essential paradigm within supply and manufacturing systems and an important element of sustainable development. PS, mainly known for its horizontal effects within the operational decision level, directly impacts both tactical and strategical levels of decision-making. In other words, an optimally designed and utilized PS module could bring efficiency towards the whole supply chain network of many manufacturing systems. Simulation Optimization (SO), as a growing Decision Support Tool (DST), provides a methodology required to drastically improve the efficiency of industrial systems. Thus, in this article, we review the existing research on SO Applied to PS (SOAPS), within the context of wider adaption of Industry 4.0 (known as the fourth industrial revolution). Firstly, relevant articles are examined and reviewed to position the research and develop research questions that enable the highlighting of research gaps. Then, a methodology was created based on: the studied PS problem features, proposed optimization frameworks, executed simulation tools, the SO architectures and the experimentation and validation strategies used. Finally, we investigate how Industry 4.0 could enhance the existing research on SOAPS to provide real-time and efficient SO-based DSTs for PS modules within modern manufacturing systems.