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Engineering    2018, Vol. 4 Issue (5) : 722 -728
Research Intelligent Manufacturing—Perspective |
The Future of Manufacturing: A New Perspective
Ben Wangabc()
a Georgia Tech Manufacturing Institute, Georgia Institute of Technology, Atlanta, GA 30332, USA
b School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
c School of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
Abstract  Abstract

Many articles have been published on intelligent manufacturing, most of which focus on hardware, software, additive manufacturing, robotics, the Internet of Things, and Industry 4.0. This paper provides a different perspective by examining relevant challenges and providing examples of some less-talked-about yet essential topics, such as hybrid systems, redefining advanced manufacturing, basic building blocks of new manufacturing, ecosystem readiness, and technology scalability. The first major challenge is to (re-)define what the manufacturing of the future will be, if we wish to: ① raise public awareness of new manufacturing’s economic and societal impacts, and ② garner the unequivocal support of policy-makers. The second major challenge is to recognize that manufacturing in the future will consist of systems of hybrid systems of human and robotic operators; additive and subtractive processes; metal and composite materials; and cyber and physical systems. Therefore, studying the interfaces between constituencies and standards becomes important and essential. The third challenge is to develop a common framework in which the technology, manufacturing business case, and ecosystem readiness can be evaluated concurrently in order to shorten the time it takes for products to reach customers. Integral to this is having accepted measures of “scalability” of non-information technologies. The last, but not least, challenge is to examine successful modalities of industry–academia–government collaborations through public–private partnerships. This article discusses these challenges in detail.

Keywords Advanced Manufacturing Partnership      Ecosystem      Industry 4.0      Intelligent manufacturing      Internet of Things      Manufacturing innovation institutes      National Network for Manufacturing Innovation     
Just Accepted Date: 01 August 2018   Issue Date: 26 November 2018
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Ben Wang. The Future of Manufacturing: A New Perspective[J]. Engineering, 2018, 4(5): 722 -728 .
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[1]   R. Jardim-Goncalves, J. Sarraipa, C. Agostinho, H. Panetto. Knowledge framework for intelligent manufacturing systems. J Intell Manuf. 2011; 22(5): 725-735.
[2]   J. Lee, B. Bagheri, H.A. Kao. A cyber-physical systems architecture for Industry 4.0-based manufacturing systems. Manuf Lett. 2015; 3: 18-23.
[3]   B. Li, L. Zhang, L. Ren, X. Chai, F. Tao, Y. Luo, et al.. Further discussion on cloud manufacturing. Comput Integr Manuf Syst. 2011; 17(3): 449-457. Chinese
[4]   M. Peschl, N. Link, M. Hoffmeister, G. Gonçalves, F.L.F. Almeida. Designing and implementation of an intelligent manufacturing system. JIEM. 2011; 4(4): 718-745.
[5]   A. Radziwon, A. Bilberg, M. Bogers, E.S. Madsen. The smart factory: exploring adaptive and flexible manufacturing solutions. Proc Eng. 2014; 69: 1184-1190.
[6]   F. Tao, L. Zhang, V.C. Venkatesh, Y. Luo, Y. Cheng. Cloud manufacturing: a computing and service-oriented manufacturing model. Proc Inst Mech Eng B J Eng Manuf. 2011; 225(10): 1969-1976.
[7]   F. Tao, Y. Cheng, L. Zhang, A.Y.C. Nee. Advanced manufacturing systems: socialization characteristics and trends. J Intell Manuf. 2017; 28(5): 1079-1094.
[8]   L. Zhang, Y. Luo, W. Fan, F. Tao, L. Ren. Analyses of cloud manufacturing and related advanced manufacturing models. Comput Integr Manuf Syst. 2011; 17(3): 458-468. Chinese
[9]   X. Xu. From cloud computing to cloud manufacturing. Robot Comput-Integr Manuf. 2012; 28(1): 75-86.
[10]   B. Wang, W.C. Kessler, A. Dugenske. Engineering and manufacturing: concurrent maturation of xRL. In: editor. Handbook of manufacturing industries in the world economy. Cheltenham Glos: Edward Elgar; 2015. p. 109-120.
[11]   A.L. Nelson, E. Dhimolea, J.M. Reichert. Development trends for human monoclonal antibody therapeutics. Nat Rev Drug Discov. 2010; 9(10): 767-774.
[12]   National Cell Manufacturing Consortium. Achieving large-scale, cost-effective, reproducible manufacturing of high-quality cells: a technology roadmap to 2025. Report.
[13]   National Cell Manufacturing Consortium. Roadmap update to achieving large-scale, cost-effective, reproducible manufacturing of high-quality cells. Report.
[14]   K. Marchese, J. Crane, C. Haley. 3D opportunity for the supply chain: additive manufacturing delivers. Report.
[15]   M. Cotteleer, J. Holdowsky, M. Mahto. The 3D opportunity primer: the basics of additive manufacturing. Report.
[16]   J. Michalik, J. Joyce, R. Barney, G. McCune. 3D opportunity for product design: additive manufacturing and the early stage. Report.
[17]   T. Kellner. An epiphany of disruption: GE Additive Chief explains how 3D printing will upend manufacturing. Reports.
[18]   A. Giret, E. Garcia, V. Botti. An engineering framework for service-oriented intelligent manufacturing systems. Comput Ind. 2016; 81: 116-127.
[19]   B. Esmaeilian, S. Behdad, B. Wang. The evolution and future of manufacturing: a review. J Manuf Syst. 2016; 39: 79-100.
[20]   Leiva C. Demystifying the digital thread and digital twin concepts [Internet]. Cleveland: Informa USA, Inc; c2018 [updated 2016 Aug 1; cited 2018 Jan 29]. Available from:
[21]   J.P. Holdren, E. Lander, W. Press, M. Savitz, R. Bierbaum, S.J. GatesJr, et al.. Report to the president on capturing domestic competitive advantage in advanced manufacturing. Report.
[22]   Kim A. A shortage of skilled workers threatens manufacturing’s rebound [Internet]. Washington, DC: Center for Strategic and International Studies; c2016 [updated 2017 Aug 10; cited 2018 Jan 29]. Available from:
[23]   S.R. Sadin, F.P. Povinelli, R. Rosen. The NASA technology push towards future space mission systems, in space and humanity. Acta Astronaut. 1989; 20: 73-77.
[24]   OSD Manufacturing Technology Program. Manufacturing readiness level (MRL) deskbook. Report.
[25]   G.P. Pisano, W.C. Shih. Producing prosperity: why America needs a manufacturing renaissance.
[26]   Bondi AB. Characteristics of scalability and their impact on performance. In: Proceedings of the 2nd International Workshop on Software and Performance; 2000 Sep 17–20; Ottawa, ON, Canada. New York: ACM; 2000. p. 195–203.
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