Guest Editorial Special Section on Big Data Analytics in Intelligent Manufacturing

The nine papers in this special section focus on Big Data analytics in intelligent manufacturing systems. These systems can automatically adapt to changing environments and varying process requirements with minimal supervision and assistance from operators. It is essentially a cyber–physical production system that has enhanced intelligence due to learning, reasoning, adaptation, and decision making. The success of intelligent manufacturing relies on the timely acquisition, distribution, and utilization of various types of data from machines, manufacturing process, and products. The efficient use of big data can enhance the intelligence and automation of manufacturing process, provide high quality products and just-in-time production, and increase productivity and reduce costs. For example, by analyzing the factory floor data, equipment monitored data, and the enterprise manufacturing database, it could help to store, explore, and make complex decisions for the manufacturing system. While these big data topics have been widely discussed in the public media and the theory has been rigorously treated by statisticians and computer scientists from academia, little has been explored in the manufacturing research community from an engineering point of view. This special section aims to bridge the gap, and provides a platform for the communities to report recent findings and emerging research developments in the field.