Self organizing tool for smart design with predictive customer needs and wants to realize Industry 4.0
Following the first three industrial revolutions, Industry 4.0 (I4) aims at realizing mass customization at a mass production cost. Currently, however, there is a lack of smart analytics tools for achieving such a goal. This paper investigates this issues and then develops a predictive analytics framework integrating cloud computing, big data analysis, business informatics, communication technologies, and digital industrial production systems. Computational intelligence in the form of a self organizing map (SOM) is used to manage relevant big data for feeding potential customer needs and wants to smart designs for targeted productivity and customized mass production. The selection of patterns from big data with SOM helps with clustering and with the selection of optimal attributes. A car customization case study shows that the SOM is able to assign new clusters when growing knowledge of customer needs and wants. The self organizing tool offers a number of features suitable to smart design that is required in realizing Industry 4.0.
2016 IEEE Congress on Evolutionary Computation (CEC)