Articles

Industry 4.0: a way from mass customization to mass personalization production

  • Yi Wang ,
  • Hai-Shu Ma ,
  • Jing-Hui Yang ,
  • Ke-Sheng Wang
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  • 1 School of Business, Plymouth University, Plymouth, UK;
    2 Department of Production and Quality Engineering, Norwegian University of Science and Technology, S. P. Andersens Veg 5, 7031 Trondheim, Norway;
    3 School of Business Management, Shanghai Polytechnic University, Shanghai 201209, People's Republic of China

Received date: 2017-05-03

  Revised date: 2017-05-03

  Online published: 2017-12-25

Abstract

Although mass customization, which utilizes modularization to simultaneously increase product variety and maintain mass production (MP) efficiency, has become a trend in recent times, there are some limitations to mass customization. Firstly, customers do not participate wholeheartedly in the design phase. Secondly, potential combinations are predetermined by designers. Thirdly, the concept of mass customization is not necessary to satisfy individual requirements and is not capable of providing personalized services and goods. Industry 4.0 is a collective term for technologies and concepts of value chain organization. Based on the technological concepts of radio frequency identification, cyber-physical system, the Internet of things, Internet of service, and data mining, Industry 4.0 will enable novel forms of personalization. Direct customer input to design will enable companies to increasingly produce customized products with shorter cycle-times and lower costs than those associated with standardization and MP. The producer and the customer will share in the new value created. To overcome the gaps between mass customization and mass personalization, this paper presents a framework for mass personalization production based on the concepts of Industry 4.0. Several industrial practices and a lab demonstration show how we can realize mass personalization.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-017-0204-7/fulltext.html

Cite this article

Yi Wang , Hai-Shu Ma , Jing-Hui Yang , Ke-Sheng Wang . Industry 4.0: a way from mass customization to mass personalization production[J]. Advances in Manufacturing, 2017 , 5(4) : 311 -320 . DOI: 10.1007/s40436-017-0204-7

References

1. Ford H, Crowther S (1926) Today and tomorrow. Doubleday Page & Company, New York
2. Wang KS (2016) Intelligent predictive maintenance (IPdM) system-Industry 4.0 scenario. WIT Trans Eng Sci 113(1):259-268
3. Pine BJ (1993) Mass customization:the new frontier in business competition. Harvard Business Press, New York
4. Martin R (2010) The age of customer capitalism. Harvard Business Review, New York
5. Zamfirescu CB, Pirvu CT, Schlick J et al (2013) Preliminary insides for an anthropocentric cyber-physical reference architecture of the smart factory. Stud Inf Control 22(2):269-278
6. Hermann M, Pentek T, Otto B (2016) Design principles for Industrie 4.0 scenarios. In:Hawaii international conference on system sciences, IEEE, pp 3928-3937
7. Coalition S (2011) Coalition SML implementing 21st century smart manufacturing. In:workshop summary report, Washington, DC
8. Gibson M (2014) Bringing manufacturing back. http://www.civitas.org.uk/pdf/BringingManufacturingBack.pdf. Accessed Oct 2014
9. China to boost "Made in China 2025" strategy (2015) http://news.xinhuanet.com/english/2015-03/25/c_134097374.htm. Accessed 25 Mar 2015
10. Intelligent manufacturing systems (2016) http://www.ims.org. Accessed 7 Sep 2016
11. Centre for research-based innovation (2016) http://www.sfinorman.no/. Accessed 13 Nov 2016
12. Suh SH, Shin SJ, Yoon JS et al (2008) UbiDM:a new paradigm for product design and manufacturing via ubiquitous computing technology. Int J Comput Integr Manuf 21(5):540-549
13. Wang KS (2014) Intelligent and integrated RFID (Ⅱ-RFID) system for improving traceability in manufacturing. Adv Manuf 2(2):106-120
14. Wang KS, Wang Y (2012) Towards a next generation of manufacturing:zero-defect manufacturing (ZDM) using data mining approaches. Tapir Academic Press, New York
15. Gorecky D, Schmitt M, Loskyll M et al (2014) Human-machineinteraction in the Industry 4.0 era. In:IEEE international conference on industrial informatics, IEEE, pp 289-294
16. Wang KS (2013) Towards zero-defect manufacturing (ZDM)-a data mining approach. Adv Manuf 1(1):62-74
17. Drath R, Horch A (2014) Industrie 4.0:hit or hype? IEEE Ind Electron Mag 8(2):56-58
18. Sogetilabs (2014) Mass personalization 2025. http://labs.sogeti.com/mass-personalization-2025-internet-things-mobile-wearablecomputing-big-data-analytics-intelligent-robots/. Accessed 20 Nov 2014
19. Hu SJ (2013) Evolving paradigms of manufacturing:from mass production to mass customization and personalization. Proced CIRP 7:3-8
20. Tseng M, Jiao R, Wang C (2010) Design for mass personalization. CIRP Ann Manuf Technol 59(1):175-178
21. Zhou F, Ji Y, Jiao RJ (2013) Affective and cognitive design for mass personalization:status and prospect. J Intell Manuf 24(5):1047-1069
22. Wang J, Lu G, Chen L et al (2011) Customer participating 3D garment design for mass personalization. Text Res J 81(2):187-204
23. Zhong RY, Dai Q, Qu T et al (2013) RFID-enabled real-time manufacturing execution system for mass-customization production. Robot Comput Integr Manuf 29(2):283-292
24. Moon J, Chadee D, Tikoo S (2008) Culture, product type, and price influences on consumer purchase intention to buy personalized products online. J Bus Res 61(1):31-39
25. Red collar (2016) http://www.redcollar.com.cn. Accessed 13 Oct 2016
26. Harley davidson (2016) http://www.harley-drivson.com. Accessed 2 May 2016
27. Madshus (2017) http://www.madshus.com. Accessed 13 Feb 2017

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