Abstract
The trend of future manufacturing requires manufacturers to sustainable optimize the utilization of resources (e.g. people, equipment, material, methods, and environment) to lean produce high quality product, and quickly adapts to changes of market demands and supply chain partners. German’s Industry 4.0 has attracted extensive attention in the world in recent years, which is believed to be a new paradigm to meet the ever changing requirements of future manufacturing. Industry 4.0 focuses on building cyber-physical systems (CPS) based product creation eco-system with highly flexible and reasonable cost with just-in-time reactivity. However, on the way to build such an eco-system is still need effort to investigate technological foundations of CPS and deeply cognitive understanding of key concepts with considering the context of implementation of industry 4.0 landscape. In the context, this chapter introduces the conceptual model and operation mechanism of decentralized cyber-physical systems (CPS), which enables manufacturers to utilize a cloud-based agent approach to create an intelligent collaborative environment for product creation. A brief introduction to the connotation of industry 4.0 and smart factory of industry 4.0 from the perspective of China’s industry and academic is given. The concept of decentralized cyber-physical systems agents is proposed and discussed, with the focus on conceptual model, operation mechanism and key technologies. After that, a cloud-based smart manufacturing paradigm is presented. The architecture and business process model of such a paradigm is developed. Finally, a case study of how a manufacturing enterprise uses the proposed paradigm to implement the smart factory of industry 4.0 in China. This study benefits both academic researchers and industrial engineers and decision makers with the proposed paradigm as well as case study.
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References
Baheti R, Gill H (2011) Cyber-physical systems. Impact Control Technol 12:161–166
Davis J, Edgar T, Porter J, Bernaden J, Sarli M (2012) Smart manufacturing, manufacturing intelligence and demand-dynamic performance. Comput Chem Eng 47:145–156
Dieter GE, Schmidt LC (2013) Engineering design, vol 3. McGraw-Hill, New York
Eccles JC (2013) The physiology of synapses. Academic Press
Edgar TF, Davis JF (2008) Smart process manufacturing–a vision of the future. Ind Eng Chem Res Dev Centen Issue
Ghonaim W, Ghenniwa H, Shen W (2011) June. Towards an agent oriented smart manufacturing system. In: 2011 15th international conference on computer supported cooperative work in design (CSCWD). IEEE, pp 636–642
Lee J, Bagheri B, Kao HA (2015) A cyber-physical systems architecture for industry 4.0-based manufacturing systems. Manuf Lett 3:18–23
Lohr S (2012) The age of big data. New York Times, p 11
Lucke D, Constantinescu C, Westkämper E (2008a) Smart factory-a step towards the next generation of manufacturing. In: Manufacturing systems and technologies for the new frontier. Springer London, pp 115–118
Lucke D, Constantinescu C, Westkämper E (2008b) Smart factory-a step towards the next generation of manufacturing. In: Manufacturing systems and technologies for the new frontier. Springer London, pp 115–118
Lukasiewycz M, Steinhorst S, Sagstetter F, Chang W, Waszecki P, Kauer M, Chakraborty S (2012) September. Cyber-physical systems design for electric vehicles. In: 2012 15th euromicro conference on digital system design (DSD). IEEE, pp 477–484
Munir S, Stankovic JA, Liang CJM, Lin S (2013) Cyber physical system challenges for human-in-the-loop control. In: Presented as part of the 8th international workshop on feedback computing
Paletta L, Santner K, Fritz G, Mayer H, Schrammel J (2013) April. 3D attention: measurement of visual saliency using eye tracking glasses. In: CHI’13 extended abstracts on human factors in computing systems. ACM, pp 199–204
Song H (ed) (2009) Handbook of research on human performance and instructional technology. IGI Global
Sridhar S, Hahn A, Govindarasu M (2012) Cyber–physical system security for the electric power grid. Proc IEEE 100(1):210–224
Stadtler H (2015) Supply chain management: an overview. In: Supply chain management and advanced planning. Springer Berlin, pp 3–28
Wang Y, Zhou T, Liu Z (2013) Study on lean management mode of production and operation of enterprise teams. In: Informatics and management science IV. Springer, London, pp 603–610
Xu X (2012) From cloud computing to cloud manufacturing. Robot Comput-integr Manuf. 28(1):75–86
Zhang Y, Xie F, Dong Y, Yang G, Zhou X (2013) High fidelity virtualization of cyber-physical systems. Int J Model Simul Sci Comput 4(02):1340005
Zhekun L, Gadh R, Prabhu BS (2004) January. Applications of RFID technology and smart parts in manufacturing. In: ASME 2004 international design engineering technical conferences and computers and information in engineering conference. American Society of Mechanical Engineers, pp 123–129
http://news.xinhuanet.com/politics/2015-05/28/c_1115441243.htm (Visit on July 1 2016)
Acknowledgements
The research presented in this paper was partially funded by the Ministry of Industry and Information Technology of the People’s Republic of China (2016ZXFM03002), and the Shanghai Academy of Space Technology-Shanghai Jiao Tong University Joint Research Center of Advanced Aerospace Technology (USCAST2016-16). Special thanks to Dr. Gang Liu and Mr. Zongkai Dai for the help of the case study.
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Zhang, Z., Li, X., Wang, X., Cheng, H. (2017). Decentralized Cyber-Physical Systems: A Paradigm for Cloud-Based Smart Factory of Industry 4.0. In: Thames, L., Schaefer, D. (eds) Cybersecurity for Industry 4.0. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-319-50660-9_6
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DOI: https://doi.org/10.1007/978-3-319-50660-9_6
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