Industrial big data-based scheduling modeling framework for complex manufacturing system

Abstract

Scheduling modeling for manufacturing system has always been a great challenge in both industrial and academic community. With the growing complexity of the manufacturing system, traditional scheduling modeling and optimization methods cannot satisfy all the demands of current manufacturing environment, so data-based methods are brought into practice. Since the popularity of the concept of cyber physical system and Industry 4.0, more information and interaction systems are applied into the manufacturing system, and more industrial big data produced during the production process can be acquired; the knowledge within these data needs to be uncovered to better schedule the system. In this article, the research progress of scheduling modeling methods for complex manufacturing system are systemically reviewed and evaluated with the semiconductor wafer fabrication environment. Then, we propose the industrial big data-based scheduling modeling framework in cyber physical system condition and discuss how to implement it for the semiconductor manufacturing system, also our demonstration unit of an intelligent semiconductor manufacturing system based on this framework is introduced. Finally, the future work of our application case is discussed.