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Intelligent Manufacturing

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Book cover Industry 4.0

Part of the book series: SpringerBriefs in Applied Sciences and Technology ((BRIEFSMANUFACT))

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Abstract

Industry 4.0 is the next generation of the industry that promises to bring in flexibility in the manufacturing environment, improvising productivity and thereby resulting in customized products and goods with enhanced quality. The promising aspect of Industry 4.0 has encouraged industries to meet the different challenges associated with the production of customized products with enhanced quality and short lead-time to market. It is intelligent manufacturing that plays a crucial role in the success of Industry 4.0. With the framework of Industry 4.0, various resources are converted to intelligent objects that can sense and therefore act accordingly within the smart environment. The present chapter is, therefore, an attempt to illuminate the readers with the associated key concepts such as intelligent manufacturing, cloud manufacturing, and Industry 4.0. Key enabling technologies such as big data analytics, cyber-physical systems, Internet of things, information and communication technology and cloud computing have been discussed in this chapter. The chapter also provides an overview of platforms in intelligent manufacturing and on few emerging trends in intelligent manufacturing. The chapter finally concludes with future perspectives for intelligent manufacturing in the context of Industry 4.0.

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References

  • R. Agarwal, P. Weill, The benefits of combining data with empathy. MIT Sloan Manag. Rev. 54(1), 35 (2012)

    Google Scholar 

  • S. Ali, S. Qaisar, H. Saeed, M. Khan, M. Naeem, A. Anpalagan, Network challenges for cyber physical systems with tiny wireless devices: a case study on reliable pipeline condition monitoring. Sensors 15(4), 7172–7205 (2015)

    Article  Google Scholar 

  • M. Armbrust, A. Fox, R. Griffith, A.D. Joseph, R. Katz, A. Konwinski, G. Lee, D. Patterson, A. Rabkin, I. Stoica, M. Zaharia, A view of cloud computing. Commun. ACM 53(4), 50–58 (2010)

    Article  Google Scholar 

  • R.K. Banyal, P. Jain, V.K. Jain, Multi-factor authentication framework for cloud computing, in 2013 Fifth International Conference on Computational Intelligence, Modelling and Simulation (CIMSim) (IEEE, 2013), pp. 105–110

    Google Scholar 

  • D. Barton, D. Court, Making advanced analytics work for you. Harvard Bus. Rev. 90(10), 78–83 (2012)

    Google Scholar 

  • J. Barbosa, P. Leitão, E. Adam, D. Trentesaux, Dynamic self-organization in holonic multi-agent manufacturing systems: the ADACOR evolution. Comput. Ind. 66, 99–111 (2015)

    Article  Google Scholar 

  • N. Bloom, L. Garicano, R. Sadun, J. Van Reenen, The distinct effects of information technology and communication technology on firm organization. Manag. Sci. 60(12), 2859–2885 (2014)

    Article  Google Scholar 

  • Z. Bi, L. Da Xu, C. Wang, Internet of things for enterprise systems of modern manufacturing. IEEE Trans. Ind. Inf. 10(2), 1537–1546 (2014)

    Article  Google Scholar 

  • B. Brown, M. Chui, J. Manyika, Are you ready for the era of ‘big data’. McKinsey Q. 4(1), 24–35 (2011)

    Google Scholar 

  • R. Buyya, C.S. Yeo, S. Venugopal, J. Broberg, I. Brandic, Cloud computing and emerging IT platforms: vision, hype, and reality for delivering computing as the 5th utility. Future Gener. Comput. Syst. 25(6), 599–616 (2009)

    Article  Google Scholar 

  • T. Chen, Y.C. Wang, Z. Lin, Predictive distant operation and virtual control of computer numerical control machines. J Intell. Manuf. 28(5), 1061–1077 (2017)

    Article  Google Scholar 

  • M. Colin, R. Galindo, O. Hernández, Information and communication technology as a key strategy for efficient supply chain management in manufacturing SMEs. Procedia Comput. Sci. 55, 833–842 (2015)

    Article  Google Scholar 

  • L. Da Xu, W. He, S. Li, Internet of things in industries: a survey. IEEE Trans. Ind. Inf. 10(4), 2233–2243 (2014)

    Article  Google Scholar 

  • Q. Dai, R. Zhong, G.Q. Huang, T. Qu, T. Zhang, T.Y. Luo, Radio frequency identification-enabled real-time manufacturing execution system: a case study in an automotive part manufacturer. Int. J. Comput. Integr. Manuf. 25(1), 51–65 (2012)

    Article  Google Scholar 

  • J. Davis, T. Edgar, J. Porter, J. Bernaden, M. Sarli, Smart manufacturing, manufacturing intelligence and demand-dynamic performance. Comput. Chem. Eng. 47, 145–156 (2012)

    Article  Google Scholar 

  • P. Derler, E.A. Lee, A.S. Vincentelli, Modeling cyber–physical systems. Proc. IEEE 100(1), 13–28 (2012)

    Article  Google Scholar 

  • S.A. de Chaves, B. Carlos, C.M. Westphall, G.A. Gerônimo, Customer security concerns in cloud computing, in Proceedings of the Tenth International Conference on Networks (ICN) (2011), pp. 7–11

    Google Scholar 

  • M.U. Farooq, M. Waseem, S. Mazhar, A. Khairi, T. Kamal, A review on Internet of Things (IoT). Int. J. Comput. Appl. 113(1), 1–7 (2015)

    Google Scholar 

  • A.B. Feeney, S.P. Frechette, V. Srinivasan, A portrait of an ISO STEP tolerancing standard as an enabler of smart manufacturing systems. J. Comput. Inf. Sci. Eng. 15(2), 021001 (2015)

    Article  Google Scholar 

  • Z. Guo, E. Ngai, C. Yang, X. Liang, An RFID-based intelligent decision support system architecture for production monitoring and scheduling in a distributed manufacturing environment. Int. J. Prod. Econ. 159, 16–28 (2015)

    Article  Google Scholar 

  • J. Hashim, Information communication technology (ICT) adoption among SME owners in Malaysia. Int. J. Bus. Inf. 2(2) (2007)

    Google Scholar 

  • G.Q. Huang, Y.F. Zhang, X. Chen, S.T. Newman, RFID-enabled real-time wireless manufacturing for adaptive assembly planning and control. J. Intell. Manuf. 19(6), 701–713 (2008)

    Article  Google Scholar 

  • E. Ketteni, C. Kottaridi, T.P. Mamuneas, Information and communication technology and foreign direct investment: interactions and contributions to economic growth. Empir. Econ. 48(4), 1525–1539 (2015)

    Article  Google Scholar 

  • A. Khajeh-Hosseini, D. Greenwood, I. Sommerville, Cloud migration: a case study of migrating an enterprise it system to IAAS, in 2010 IEEE 3rd International Conference on Cloud Computing (CLOUD) (IEEE, 2010), pp. 450–457

    Google Scholar 

  • Y. Koren, W. Wang, X. Gu, Value creation through design for scalability of reconfigurable manufacturing systems. Int. J. Prod. Res. 55(5), 1227–1242 (2017)

    Article  Google Scholar 

  • A. Kusiak, Intelligent Manufacturing Systems (Prentice Hall Press, NJ, 1990), p. 448

    Google Scholar 

  • E.A. Lee, Cyber physical systems: design challenges, in 11th IEEE Symposium on Object Oriented Real-Time Distributed Computing (ISORC) (IEEE, 2008), pp. 363–369

    Google Scholar 

  • J. Lee, E. Lapira, B. Bagheri, H.A. Kao, Recent advances and trends in predictive manufacturing systems in big data environment. Manuf. Lett. 1(1), 38–41 (2013)

    Article  Google Scholar 

  • J. Lee, B. Bagheri, H.A. Kao, A cyber-physical systems architecture for industry 4.0-based manufacturing systems. Manuf. Lett. 3, 18–23 (2015)

    Article  Google Scholar 

  • W.N. Liu, L.J. Zheng, D.H. Sun, X.Y. Liao, M. Zhao, J.M. Su, Y.X. Liu, RFID-enabled real-time production management system for Loncin motorcycle assembly line. Int. J. Comput. Integr. Manuf. 25(1), 86–99 (2012)

    Article  Google Scholar 

  • B.H. Li, B.C. Hou, W.T. Yu, X.B. Lu, C.W. Yang, Applications of artificial intelligence in intelligent manufacturing: a review. Front. Inf. Technol. Electron. Eng. 18(1), 86–96 (2017)

    Article  Google Scholar 

  • B.H. Li, L. Zhang, S.L. Wang, F. Tao, J.W. Cao, X.D. Jiang, X. Song, X.D. Chai, Cloud manufacturing: a new service-oriented networked manufacturing model. Comput. Integr. Manuf. Syst. 16(1), 1–7 (2010)

    Google Scholar 

  • Y. Liu, X. Xu, L. Zhang, L. Wang, R.Y. Zhong, Workload-based multi-task scheduling in cloud manufacturing. Robot. Comput.-Integr. Manuf. 45, 3–20 (2017)

    Article  Google Scholar 

  • B.H. Lu, R.J. Bateman, K. Cheng, RFID enabled manufacturing: fundamentals, methodology and applications. Int. J. Agile Syst. Manag. 1(1), 73–92 (2006)

    Article  Google Scholar 

  • D. Lund, C. MacGillivray, V. Turner, M. Morales, Worldwide and regional Internet of Things (IoT) 2014–2020 forecast: a virtuous circle of proven value and demand. International Data Corporation (IDC), Technical Report, 1 (2014)

    Google Scholar 

  • J. Manyika, M. Chui, B. Brown, J. Bughin, R. Dobbs, C. Roxburgh, A.H. Byers, Big data: the next frontier for innovation, competition, and productivity (2011)

    Google Scholar 

  • S.T. Maguluri, R. Srikant, L. Ying, March. Stochastic models of load balancing and scheduling in cloud computing clusters, in 2012 Proceedings IEEE INFOCOM (IEEE, 2012), pp. 702–710

    Google Scholar 

  • P. Mell, T. Grance, The NIST definition of cloud computing. Natl. Inst. Stand. Technol. 53(6), 50 (2009)

    Google Scholar 

  • D. McFarlane, S. Sarma, J.L. Chirn, C. Wong, K. Ashton, Auto ID systems and intelligent manufacturing control. Eng. Appl. Artif. Intell. 16(4), 365–376 (2003)

    Article  Google Scholar 

  • R. Moreno-Vozmediano, R.S. Montero, I.M. Llorente, Key challenges in cloud computing: enabling the future internet of services. IEEE Internet Comput. 17(4), 18–25 (2013)

    Article  Google Scholar 

  • D. Petcu, Portability and interoperability between clouds: challenges and case study, in European Conference on a Service-Based Internet (Springer, Berlin, Heidelberg, 2011), pp. 62–74

    Chapter  Google Scholar 

  • S. Rich, Big data is a ‘new natural resource’. Retrieved, 17 (2012), p. 2016

    Google Scholar 

  • T. Qu, H.D. Yang, G.Q. Huang, Y.F. Zhang, H. Luo, W. Qin, A case of implementing RFID-based real-time shop-floor material management for household electrical appliance manufacturers. J. Intell. Manuf. 23(6), 2343–2356 (2012)

    Article  Google Scholar 

  • M.A. Sharkh, M. Jammal, A. Shami, A. Ouda, Resource allocation in a network-based cloud computing environment: design challenges. IEEE Commun. Mag. 51(11), 46–52 (2013)

    Article  Google Scholar 

  • W. Shen, D.H. Norrie, Agent-based systems for intelligent manufacturing: a state-of-the-art survey. Knowl. Inf. Syst. 1(2), 129–156 (1999)

    Article  Google Scholar 

  • F. Tao, Y. Zuo, L. Da Xu, L. Zhang, IoT-based intelligent perception and access of manufacturing resource toward cloud manufacturing. IEEE Trans. Industrial Informatics 10(2), 1547–1557 (2014a)

    Article  Google Scholar 

  • F. Tao, Y. Cheng, L. Da Xu, L. Zhang, B.H. Li, CCIoT-CMfg: cloud computing and internet of things-based cloud manufacturing service system. IEEE Trans. Ind. Inf. 10(2), 1435–1442 (2014b)

    Article  Google Scholar 

  • X. Tan, B. Ai, The issues of cloud computing security in high-speed railway, in 2011 International Conference on Electronic and Mechanical Engineering and Information Technology (EMEIT), vol. 8 (IEEE, 2011), pp. 4358–4363

    Google Scholar 

  • Y. Tan, S. Goddard, L.C. Perez, A prototype architecture for cyber-physical systems. ACM Sigbed Rev. 5(1), 26 (2008)

    Article  Google Scholar 

  • J. Wan, S. Tang, D. Li, S. Wang, C. Liu, H. Abbas, A.V. Vasilakos, A manufacturing big data solution for active preventive maintenance. IEEE Trans. Ind. Inf. 13(4), 2039–2047 (2017)

    Article  Google Scholar 

  • X.V. Wang, X.W. Xu, An interoperable solution for cloud manufacturing. Robot. Comput.-Integr. Manuf. 29(4), 232–247 (2013)

    Google Scholar 

  • S. Wang, J. Wan, D. Zhang, D. Li, C. Zhang, Towards smart factory for industry 4.0: a self-organized multi-agent system with big data based feedback and coordination. Comput. Netw. 101, 158–168 (2016a)

    Article  Google Scholar 

  • S. Wang, J. Wan, D. Li, C. Zhang, Implementing smart factory of industrie 4.0: an outlook. Int. J. Distrib. Sensor Netw. 12(1), 3159805 (2016b)

    Article  Google Scholar 

  • S.F. Wamba, S. Akter, A. Edwards, G. Chopin, D. Gnanzou, How ‘big data’ can make big impact: findings from a systematic review and a longitudinal case study. Int. J. Prod. Econ. 165, 234–246 (2015)

    Article  Google Scholar 

  • D. Wu, M.J. Greer, D.W. Rosen, D. Schaefer, Cloud manufacturing: strategic vision and state-of-the-art. J. Manuf. Syst. 32(4), 564–579 (2013)

    Article  Google Scholar 

  • F. Xia, L.T. Yang, L. Wang, A. Vinel, Internet of Things. Int. J. Commun Syst 25(9), 1101–1102 (2012)

    Article  Google Scholar 

  • X. Xu, From cloud computing to cloud manufacturing. Robot. Comput.-Integr. Manuf. 28(1), 75–86 (2012)

    Article  Google Scholar 

  • H. Yang, M. Tate, Where are we at with cloud computing?: a descriptive literature review, in 20th Australasian Conference on Information Systems (2009), pp. 2–4

    Google Scholar 

  • L. Zhang, Y. Luo, F. Tao, B.H. Li, L. Ren, X. Zhang, H. Guo, Y. Cheng, A. Hu, Y. Liu, Cloud manufacturing: a new manufacturing paradigm. Enterp. Inf. Syst. 8(2), 167–187 (2014)

    Article  Google Scholar 

  • R.Y. Zhong, Q.Y. Dai, T. Qu, G.J. Hu, G.Q. Huang, RFID-enabled real-time manufacturing execution system for mass-customization production. Robot. Comput.-Integr. Manuf. 29(2), 283–292 (2013a)

    Article  Google Scholar 

  • R.Y. Zhong, Z. Li, L.Y. Pang, Y. Pan, T. Qu, G.Q. Huang, RFID-enabled real-time advanced planning and scheduling shell for production decision making. Int. J. Comput. Integr. Manuf. 26(7), 649–662 (2013b)

    Article  Google Scholar 

  • Q. Zhang, L. Cheng, R. Boutaba, Cloud computing: state-of-the-art and research challenges. J. Internet Serv. Appl. 1(1), 7–18 (2010)

    Article  Google Scholar 

  • R.Y. Zhong, X. Xu, E. Klotz, S.T. Newman, Intelligent manufacturing in the context of industry 4.0: a review. Engineering 3(5), 616–630 (2017)

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Mechanical Engineering, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, India

    Kaushik Kumar

  2. Department of Mechanical Engineering, National Institute of Technology Silchar, Silchar, Cachar, Assam, India

    Divya Zindani

  3. Department of Mechanical Engineering, University of Aveiro, Aveiro, Portugal

    J. Paulo Davim

Authors
  1. Kaushik Kumar
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  2. Divya Zindani
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  3. J. Paulo Davim
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Correspondence to Kaushik Kumar .

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Kumar, K., Zindani, D., Davim, J.P. (2019). Intelligent Manufacturing. In: Industry 4.0. SpringerBriefs in Applied Sciences and Technology(). Springer, Singapore. https://doi.org/10.1007/978-981-13-8165-2_1

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  • DOI: https://doi.org/10.1007/978-981-13-8165-2_1

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