Self-organizing tool for smart design with predictive customer needs and wants to realize Industry 4.0

Alfredo Alan Flores Saldivar, Cindy Goh, Wei Neng Chen, Yun Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

5 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publication2016 IEEE Congress on Evolutionary Computation, CEC 2016
Pages5317-5324
Number of pages8
DOIs
Publication statusPublished - 14 Nov 2016
Event2016 IEEE Congress on Evolutionary Computation, CEC 2016 - Vancouver, Vancouver, Canada
Duration: 24 Jul 201629 Jul 2016
http://www.wcci2016.org/

Conference

Conference2016 IEEE Congress on Evolutionary Computation, CEC 2016
Abbreviated titleIEEE CEC 2016
CountryCanada
CityVancouver
Period24/07/1629/07/16
Internet address

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Keywords

  • big data analytics
  • industry 4.0
  • self-organizing map
  • smart design
  • smart manufacturing

Cite this

Saldivar, A. A. F., Goh, C., Chen, W. N., & Li, Y. (2016). Self-organizing tool for smart design with predictive customer needs and wants to realize Industry 4.0. In 2016 IEEE Congress on Evolutionary Computation, CEC 2016 (pp. 5317-5324). [7748366] https://doi.org/10.1109/CEC.2016.7748366