Machine Learning in Production Scheduling: An Overview of the Academic Literature

Abstract

Production scheduling is an important tool for a manufacturing system, where it can have a significant impact on the productivity of a production process. In this sense, the application of machine learning can be very fruitful in this field, since it is an enabling computer programs to automatically make intelligent decisions based on data to improve performance at the manufacturing system. Therefore, this paper aims to explore the use of machine learning in production scheduling under the Industry 4.0 context. A systematic literature review was conducted to identify the main machine learning techniques currently employed to improve production scheduling. As a result, bibliometric analysis evidenced the continuous growth of this research area and identified the main machine learning techniques applied. Finally, the gaps leading to further research are highlighted.