Top > IJAT > “Industrie 4.0” and Smart Manufacturing – A ...

single-au.php

IJAT Vol.11 No.1 pp. 4-16
doi: 10.20965/ijat.2017.p0004
(2017)

Review:

Views over last 60 days: 14,042

“Industrie 4.0” and Smart Manufacturing – A Review of Research Issues and Application Examples

Klaus-Dieter Thoben*,**, Stefan Wiesner*,†, and Thorsten Wuest***

*BIBA – Bremer Institut für Produktion und Logistik GmbH, the University of Bremen
Hochschulring 20, 28359 Bremen, Germany

†Corresponding author

**Faculty of Production Engineering, University of Bremen, Bremen, Germany

***Industrial and Management Systems Engineering,
Benjamin M. Statler College of Engineering and Mineral Resources, West Virginia University, Morgantown, USA

Received:
May 16, 2016
Accepted:
December 1, 2016
Published:
January 5, 2017
Creative Commons License
Keywords:
industry 4.0, smart manufacturing, cyber-physical systems, industrial internet, smart factory
Abstract
A fourth industrial revolution is occurring in global manufacturing. It is based on the introduction of Internet of things and servitization concepts into manufacturing companies, leading to vertically and horizontally integrated production systems. The resulting smart factories are able to fulfill dynamic customer demands with high variability in small lot sizes while integrating human ingenuity and automation. To support the manufacturing industry in this conversion process and enhance global competitiveness, policy makers in several countries have established research and technology transfer schemes. Most prominently, Germany has enacted its Industrie 4.0 program, which is increasingly affecting European policy, while the United States focuses on smart manufacturing. Other industrial nations have established their own programs on smart manufacturing, notably Japan and Korea. This shows that manufacturing intelligence has become a crucial topic for researchers and industries worldwide. The main object of these activities are the so-called cyber-physical systems (CPS): physical entities (e.g., machines, vehicles, and work pieces), which are equipped with technologies such as RFIDs, sensors, microprocessors, telematics or complete embedded systems. They are characterized by being able to collect data of themselves and their environment, process and evaluate these data, connect and communicate with other systems, and initiate actions. In addition, CPS enabled new services that can replace traditional business models based solely on product sales. The objective of this paper is to provide an overview of the Industrie 4.0 and smart manufacturing programs, analyze the application potential of CPS starting from product design through production and logistics up to maintenance and exploitation (e.g., recycling), and identify current and future research issues. Besides the technological perspective, the paper also takes into account the economic side considering the new business strategies and models available.
Cite this article as:
K. Thoben, S. Wiesner, and T. Wuest, ““Industrie 4.0” and Smart Manufacturing – A Review of Research Issues and Application Examples,” Int. J. Automation Technol., Vol.11 No.1, pp. 4-16, 2017.
Data files:
References
  1. [1] H. Kagermann, J. Helbig, A. Hellinger, and W. Wahlster, “Umsetzungsempfehlungen für das Zukunftsprojekt Industrie 4.0: Deutschlands Zukunft als Produktionsstandort sichern; Abschlussbericht des Arbeitskreises Industrie 4.0,” Forschungsunion; Geschäftsstelle der Plattform Industrie 4.0, Berlin, Frankfurt/Main, 2013.
  2. [2] L. Bochmann, L. Gehrke, A. Böckenkamp, F. Weichert, R. Albersmann, C. Prasse, C. Mertens, M. Motta, and K. Wegener, “Towards Decentralized Production: A Novel Method to Identify Flexibility Potentials in Production Sequences Based on Flexibility Graphs,” Int. J. Automation Technol., Vol.9, No.3, pp. 270–282, 2015.
  3. [3] Smart Manufacturing Leadership Coalition, Implementing 21st Century Smart Manufacturing: Workshop Summary Report, Washington D.C., 2011.
  4. [4] Y. Nishioka, “Industrial Value Chain Initiative for Smart Manufacturing,” Tokyo, Japan, 2015.
  5. [5] J. Park, “Korea smart factory program,” Tokyo, Japan, 2015.
  6. [6] K. Shirase and K. Nakamoto, “Simulation Technologies for the Development of an Autonomous and Intelligent Machine Tool,” Int. J. Automation Technol., Vol.7, No.1, pp. 6-15, 2013.
  7. [7] R. Baheti and H. Gill, “Cyber-physical systems,” The impact of control technology, pp. 161-166, 2011.
  8. [8] E. Geisberger and M. Broy, “agendaCPS: Integrierte Forschungsagenda Cyber-Physical Systems,” Springer, Berlin, Heidelberg, 2012.
  9. [9] T. S. Baines, H. W. Lightfoot, S. Evans, A. Neely, R. Greenough, J. Peppard, R. Roy, E. Shehab, A. Braganza, A. Tiwari, J. R. Alcock, J. P. Angus, M. Bastl, A. Cousens, P. Irving, M. Johnson, J. Kingston, H. Lockett, V. Martinez, P. Michele, D. Tranfield, I. M. Walton, and H. Wilson, “State-of-the-art in product-service systems,” Proc. of the Institution of Mechanical Engineers, Part B: J. of Engineering Manufacture Vol.221, No.10, pp. 1543-1552, 2007.
  10. [10] G. Dr. Schütte, Keynote Speech, Berlin, 2012.
  11. [11] F. Klocke, S. Kratz, T. Auerbach, S. Gierlings, G. Wirtz, and D. Veselovac, “Process Monitoring and Control of Machining Operations,” Int. J. Automation Technol., Vol.5, No.3, pp. 403-411, 2011.
  12. [12] German Federal Ministry of Education and Research, Zukunftsprojekt Industrie 4.0, available at https://www.bmbf.de/de/zukunftsprojekt-industrie-4-0-848.html [accessed May 15, 2016]
  13. [13] E. Wallace and F. Riddick, “Panel on Enabling Smart Manufacturing,” State College, USA, 2013.
  14. [14] S. Chand and J. F. Davis, “What is smart manufacturing,” Time Magazine Wrapper, pp. 28-33, 2010.
  15. [15] Y. Lu, K. C. Morris, and S. Frechette, “Current Standards Landscape for Smart Manufacturing Systems,” National Institute of Standards and Technology, 2016.
  16. [16] S. Choi, B. H. Kim, and S. Do Noh, “A diagnosis and evaluation method for strategic planning and systematic design of a virtual factory in smart manufacturing systems,” Int. J. Precis. Eng. Manuf., Vol.16, No.6, pp. 1107–1115, 2015.
  17. [17] J. Davis, T. Edgar, R. Graybill, P. Korambath, B. Schott, D. Swink, J. Wang, and J. Wetzel, “Smart Manufacturing, Annual review of chemical and biomolecular engineering,” Vol.6, pp. 141–160, 2015.
  18. [18] N. Ivezic, B. Kulvatunyou, and V. Srinivasan, “On Architecting and Composing Through-life Engineering Information Services to Enable Smart Manufacturing,” Procedia CIRP, Vol.22, pp. 45-52, 2014.
  19. [19] S. Kumar, “Intelligent manufacturing systems,” available at http://pchats.tripod.com/int_manu.pdf [accessed May 14, 2016]
  20. [20] A. Fedorov, E. Goloschchapov, O. Ipatov, V. Potekhin, V. Shkodyrev, and S. Zobnin, “Aspects of Smart Manufacturing Via Agent-based Approach,” Procedia Engineering, Vol.100, pp. 1572-1581, 2015.
  21. [21] S. Mittal, M. Kahn, J. Davis, and T. Wuest, “Smart Manufacturing: Characteristics and Technologies,” Columbia, SC, USA, 2016.
  22. [22] Department of Energy, Energy Department Announces $70 Million for Innovation Institute on Smart Manufacturing, available at http://www.energy.gov/articles/energy-department-announces-70-million-innovation-institute-smart-manufacturing [accessed April 26, 2016]
  23. [23] C. Piddington and M. Pegram, “An IMS test case-global manufacturing,” in: Proceedings of the IFIP TC5/WG5. 7 Fifth International Conference on Advances in Production Management Systems, pp. 11-20, 1993.
  24. [24] D. Lucke, C. Constantinescu, and E. Westkämper, “Smart Factory – A Step towards the Next Generation of Manufacturing,” in: M. Mitsuishi, K. Ueda, and F. Kimura (Eds.), “Manufacturing Systems and Technologies for the New Frontier,” Springer London, London, pp. 115–118, 2008.
  25. [25] D. Zuehlke, “SmartFactory – from Vision to Reality in Factory Technologies,” IFAC Proc., Vol.41, No.2, pp. 14101-14108, 2008.
  26. [26] S. Wang, J. Wan, D. Li, and C. Zhang, “Implementing Smart Factory of Industrie 4.0: An Outlook,” Int. J. of Distributed Sensor Networks, No.4, pp. 1-10, 2016.
  27. [27] J.-M. Park, “Technology and Issue on Embodiment of Smart Factory in Small-Medium Manufacturing Business,” J. of Korean Institute of Communications and Information Sciences, Vol.40, No.12, pp. 2491-2502, 2015.
  28. [28] Y.-J. Cho, “The Future of manufacturing is with smart factory (Industry 4.0),” Busan, South Korea, 2015.
  29. [29] L. Atzori, A. Iera, and G. Morabito, “The Internet of Things: A survey, Computer Networks,” Vol.54, No.15, pp. 2787-2805, 2010.
  30. [30] L. Tan and N. Wang, “Future internet: The Internet of Things,” in: 2010 3rd Int. Conf. on Advanced Computer Theory and Engineering (ICACTE 2010), Chengdu, China, V5-376-V5-380.
  31. [31] D. Miorandi, S. Sicari, F. de Pellegrini, and I. Chlamtac, “Internet of things: Vision, applications and research challenges,” Ad Hoc Networks, Vol.10, No.7, pp. 1497–1516, 2012.
  32. [32] J. Gubbi, R. Buyya, S. Marusic, and M. Palaniswami, “Internet of Things (IoT): A vision, architectural elements, and future directions, Future Generation Computer Systems,” Vol.29, No.7, pp. 1645-1660, 2013.
  33. [33] L. D. Xu, W. He, and S. Li, “Internet of Things in Industries: A Survey,” IEEE Trans. Ind. Inf., Vol.10, No.4, pp. 2233-2243, 2014.
  34. [34] M. Helu, K. Morris, K. Jung, K. Lyons, and S. Leong, “Identifying Performance Assurance Challenges For Smart Manufacturing,” Manufacturing letters, Vol.6, pp. 1-4, 2015.
  35. [35] H. S. Kang, J. Y. Lee, S. Choi, H. Kim, J. H. Park, J. Y. Son, B. H. Kim, and S. D. Noh, “Smart manufacturing: Past research, present findings, and future directions,” Int. J. of Precis. Eng. and Manuf.-Green Tech., Vol.3, No.1, pp. 111–128, 2016.
  36. [36] J. Bruner, “Industrial Internet: The machines are talking,” O’Reilly Media, Sebastopol, USA, 2013.
  37. [37] L. Wang, M. Törngren, and M. Onori, “Current status and advancement of cyber-physical systems in manufacturing,” Journal of Manufacturing Systems, Vol.37, pp. 517–527, 2015.
  38. [38] M. Rüßmann, M. Lorenz, P. Gerbert, M. Waldner, J. Justus, P. Engel, and M. Harnisch, “Industry 4.0: The Future of Productivity and Growth in Manufacturing Industries,” Boston Consulting Group 2015.
  39. [39] K.-D. Thoben, M. Veigt, D. Lappe, M. Franke, M. Kück, R. Zimmerling, J. Schlick, P. Stephan, and P. Guth, “Towards Networking Logistics Resources to enable a Demand-Driven Material Supply for Lean Production Systems – Basic Concept and Potential of a Cyber-Physical Logistics System,” in: Proceedings of the 7. BVL Scientific Symposium on Logistics, BVL Int. Bundesvereinigung Logistik (BVL) e.V, pp. 42-69, 2014.
  40. [40] A. Khalid, P. Kirisci, Z. Ghrairi, J. Pannek, Klaus, and D. Thoben, “Safety Requirements in Collaborative Human Robot Cyber Physical System,” Proc. of the 5th Int. Conf. on Dynamics in Logistics LDIC, 2016.
  41. [41] PSYMBIOSYS, Product-Service sYMBIOtic SYStems, available at http://www.psymbiosys.eu/ [accessed April 19, 2016]
  42. [42] G. Reinhart, P. Engelhardt, F. Geiger, T. Philipp, W. Wahlster, D. Zühlke, J. Schlick, T. Becker, M. Löckelt, and B. Pirvu, “Cyber-physische Produktionssysteme: Produktivitäts-und Flexibilitätssteigerung durch die Vernetzung intelligenter Systeme in der Fabrik,” wt Werkstattstechnik online, Vol.103, No.2, pp. 84–89, 2013.
  43. [43] D. Surdilovic, G. Schreck, and U. Schmidt, “Development of Collaborative Robots (COBOTS) for Flexible Human-Integrated Assembly Automation,” in: Robotics (ISR), 2010 41st Int. Symposium on and 2010 6th German Conf. on Robotics (ROBOTIK): Date, pp. 7-9 June 2010, [VDE Verlag], [Berlin], pp. 1-8, 2010.
  44. [44] Y. Zhang, S. Ren, Y. Liu, and S. Si, “A big data analytics architecture for cleaner manufacturing and maintenance processes of complex products,” J. of Cleaner Production, 2016.
  45. [45] I. A. T. Hashem, I. Yaqoob, N. B. Anuar, S. Mokhtar, A. Gani, and S. Ullah Khan, “The rise of “big data” on cloud computing: Review and open research issues,” Information Systems Vol.47, pp. 98-115, 2015.
  46. [46] G. Wang, A. Gunasekaran, E. W. Ngai, and T. Papadopoulos, “Big data analytics in logistics and supply chain management: Certain investigations for research and applications,” Int. J. of Production Economics, Vol.176, pp. 98-110, 2016.
  47. [47] T. Wuest, D. Weimer, C. Irgens, and K.-D. Thoben, “Machine learning in manufacturing: Advantages, challenges, and applications,” Production & Manufacturing Research, Vol.4, No.1, pp. 23-45, 2016.
  48. [48] C. Loebbecke and A. Picot, “Reflections on societal and business model transformation arising from digitization and big data analytics: A research agenda,” The J. of Strategic Information Systems, Vol.24, No.3, pp. 149–157, 2015.
  49. [49] M. E. Porter and J. E. Heppelmann, “How Smart, Connected Products Are Transforming Companies, Harvard Business Review,” Vol.93, No.10, pp. 96-114, 2015.
  50. [50] F. J. Riggins and S. F. Wamba, “Research Directions on the Adoption, Usage, and Impact of the Internet of Things through the Use of Big Data Analytics,” in: 2015 48th Hawaii Int. Conf. on System Sciences (HICSS), HI, USA, pp. 1531-1540.
  51. [51] T. Wuest, S. Wellsandt, and K.-D. Thoben, “Information Quality in PLM: A Production Process Perspective,” in: A. Bouras, B. Eynard, S. Foufou, K.-D. Thoben (Eds.), “Product Lifecycle Management in the Era of Internet of Things,” Springer Int. Publishing, Cham, pp. 826–834, 2016.
  52. [52] K. A. Hribernik, C. Kramer, C. Hans, and K.-D. Thoben, “A Semantic Mediator for Data Integration in Autonomous Logistics Processes,” in: K. Popplewell, J. Harding, R. Poler, and R. Chalmeta (Eds.), “Enterprise Interoperability IV,” Springer London, London, pp. 157-167, 2010.
  53. [53] VDI/VDE, ZVEI, “Reference Architecture Model Industrie 4.0 (RAMI4.0): Status Report,” 2015.
  54. [54] J.-Y. Ho and E. O’Sullivan, “Strategic standardisation of smart systems: A roadmapping process in support of innovation,” Technological Forecasting and Social Change, 2016.
  55. [55] M. P. Papazoglou, W.-J. van den Heuvel, and J. E. Mascolo, “A Reference Architecture and Knowledge-Based Structures for Smart Manufacturing Networks,” IEEE Softw. Vol.32, No.3, pp. 61–69, 2015.
  56. [56] DIN/DKE, “German Standardization Roadmap – Industry 4.0,” Version 2, 2016.
  57. [57] F. Ameri, B. Kulvatunyou, and N. Ivezic, “A Formal Process for Community-Based Reference Model Evolution for Smart Manufacturing Systems,” in: S. Umeda, M. Nakano, H. Mizuyama, H. Hibino, D. Kiritsis, G. von Cieminski (Eds.), “Advances in Production Management Systems: Innovative Production Management Towards Sustainable Growth,” Springer Int. Publishing, Cham, pp. 30-38, 2015.
  58. [58] J. Davis, T. Edgar, J. Porter, J. Bernaden, and M. Sarli, “Smart manufacturing, manufacturing intelligence and demand-dynamic performance,” Computers & Chemical Engineering, Vol.47, pp. 145–156, 2012.
  59. [59] R. Y. Zhong, S. Lan, C. Xu, Q. Dai, and G. Q. Huang, “Visualization of RFID-enabled shopfloor logistics Big Data in Cloud Manufacturing,” Int J Adv Manuf Technol, Vol.84, No.1-4, pp. 5-16, 2016.
  60. [60] A. Brodsky, G. Shao, M. Krishnamoorthy, A. Narayanan, D. Menasce, and R. Ak, “Analysis and optimization in smart manufacturing based on a reusable knowledge base for process performance models,” in: 2015 IEEE Int. Conf. on Big Data (Big Data), Santa Clara, CA, USA, pp. 1418-1427.
  61. [61] T. Wuest, K. Hribernik, and K.-D. Thoben, “Accessing servitisation potential of PLM data by applying the product avatar concept,” Production Planning & Control, Vol.26, No.14-15, pp. 1198-1218, 2015.
  62. [62] B.S. Kulvatunyou, N. Ivezic, and V. Srinivasan, “On architecting and composing engineering information services to enable smart manufacturing,” J. of computing and information science in engineering, Vol.16, No.3, 2016.
  63. [63] B. Kulvatunyou, N. Ivezic, K. C. Morris, and S. Frechette, “Drilling down on Smart Manufacturing-enabling composable apps,” Manufacturing letters, Vol.10, pp. 14-17, 2016.
  64. [64] D. Hauksdóttir, N. H. Mortensen, and P. E. Nielsen, “Identification of a reusable requirements structure for embedded products in a dynamic market environment,” Computers in Industry, Vol.64, No.4, pp. 351-362, 2013.
  65. [65] C. Ncube, “On the engineering of systems of systems: Key challenges for the Requirements Engineering community,” in: 2011 Workshop on Requirements Engineering for Systems, Services and Systems-of-Systems (RESˆ4), Trento, Italy, pp. 70–73, 2011.
  66. [66] B. Penzenstadler and J. Eckhardt, “A Requirements Engineering content model for Cyber-Physical Systems,” in: 2012 IEEE Second Workshop on Requirements Engineering for Systems, Services and Systems-of-Systems (RES4), Chicago, IL, USA, pp. 20–29, 2012.
  67. [67] S. Wiesner, C. Gorldt, M. Soeken, K.-D. Thoben, and R. Drechsler, “Requirements Engineering for Cyber-Physical Systems,” in: B. Grabot, B. Vallespir, S. Gomes, A. Bouras, D. Kiritsis (Eds.), “Advances in Production Management Systems. Innovative and Knowledge-Based Production Management in a Global-Local World,” Springer Berlin Heidelberg, Berlin, Heidelberg, pp. 281-288, 2014.
  68. [68] T. Wuest, “Identifying Product and Process State Drivers in Manufacturing Systems Using Supervised Machine Learning,” Springer International Publishing, Cham, 2015.
  69. [69] R. Boyer and M. Freyssenet, The emergence of new industrial models, Actes du GERPISA, No.15, pp. 75-144, 1995.
  70. [70] S. Vandermerwe, and J. Rada, “Servitization of business: Adding value by adding services,” European Management J., Vol.6, No.4, pp. 314-324, 1998.
  71. [71] K.-D. Thoben, J. Eschenbächer, and H. Jagdev, “Extended Products: Evolving Traditional Product Concepts,” in: K.-D. Thoben, F. Weber, K. S. Pawar (Eds.), Engineering the knowledge economy through co-operation: ICE 2001, the 7th International Conference on Concurrent Enterprising ; Bremen, Germany, 27 – 29th June 2001 ; [proceedings], Centre for Concurrent Enterprising, Univ. of Nottingham, Nottingham, pp. 429-440, 2001.
  72. [72] A. Neely, O. Benedettini, and I. Visnjic, “The servitization of manufacturing: Further evidence,” in: 18th European operations management association conference, Cambridge, pp. 3–6, 2011.
  73. [73] C. Gorldt, S. Wiesner, and I. Westphal, “Product-Service Systems im Kontext von Industrie 4.0: Auf dem Weg zu CPSS,” in: N. Gronau (Ed.), “Industrie 4.0 Management 1/2016: Product-Service Design,” 2016.
  74. [74] A. Osterwalder and Y. Pigneur, “Business model generation: A handbook for visionaries, game changers, and challengers,” Wiley, Hoboken, N.J., 2013.
  75. [75] S. Wiesner, P. Padrock, and K.-D. Thoben, “Extended Product Business Model Development in Four Manufacturing Case Studies,” Procedia CIRP, Vol.16, pp. 110-115, 2014.
  76. [76] R. Mauborgne and W. C. Kim, “Blue Ocean Strategy: How to Create Uncontested Market Space and Make the Competition Irrelevant,” Harvard Business School Press, 2005.

Creative Commons License  This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Apr. 22, 2024