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A Roadmap to Industry 4.0: Smart Production, Sharp Business and Sustainable Development pp 1–21Cite as

si3-Industry: A Sustainable, Intelligent, Innovative, Internet-of-Things Industry

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Abstract

Industry 4.0 is a digital revolution being witnessed in the present generation whereby the aim is to digitize the entire manufacturing process with minimal human or manual intervention. The aim is to encompass as many industries as feasible and adapt and enhance the existing technologies to better suit the needs of digital manufacturing. Concepts like smart manufacturing, smart factories and Industrial Internet of Things (IIoT) are some of the key buzzwords of industry 4.0. The success of industry 4.0 lies to a large extent in successful integration and adaptation of various existing and emerging technologies with the present manufacturing process. This chapter aims to provide a comprehensive introduction to the basic concept of industry 4.0 including how it came up, the principles, building blocks and the key technologies and concepts around which it is built and is targeted to develop. To incorporate or upgrade to industry 4.0, any business or organization must undergo many complicated and time-consuming procedures to transit and incorporate the concepts and strategies of industry 4.0 into their current methodologies and techniques. The aspects of maturity and feasibility with respect to the business scenario are also discussed. Industry 4.0 incorporates technologies from a wide range of domains and in turn demands massive changes like those in innovation, production, logistics and service processes. These are also discussed. The chapter concludes with the concept of sustainability as applicable to industry 4.0.

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References

  1. H. Rauen, Industry 4.0 – The Technological Revolution Continues [Video], (2012) (Speaker) Retrieved January 12, 2016, from www.vdma.org/videoitem-display/videodetail/3019396www.vdma.org/video-item-display/-/videodetail/3019396

  2. Götz, M., & Jankowska, B. (2017). Clusters and Industry 4.0–do they fit together?. European Planning Studies, 25(9), 1633-1653.

    Google Scholar 

  3. Lasi, H., Fettke, P., Kemper, H. G., Feld, T., & Hoffmann, M. (2014). Industry 4.0. Business & information systems engineering, 6(4), 239-242.

    Google Scholar 

  4. Bauernhansl, T., Ten Hompel, M., & Vogel-Heuser, B. (Eds.). (2014). Industrie 4.0 in Produktion, Automatisierung und Logistik: Anwendung-Technologien-Migration (pp. 1-648). Wiesbaden: Springer Vieweg.

    Google Scholar 

  5. Brettel, M., Friederichsen, N., Keller, M., & Rosenberg, M. (2014). How virtualization, decentralization and network building change the manufacturing landscape: An Industry 4.0 Perspective. International journal of mechanical, industrial science and engineering, 8(1), 37-44.

    Google Scholar 

  6. Kagermann, H., Wahlster, W., Helbig, J., Hellinger, A., & Karger, R. (2012). Im Fokus: das Zukunftsprojekt Industrie 4.0: Handlungsempfehlungen zur Umsetzung. Bericht der Promotorengruppe Kommunikation. Forschungsunion.

    Google Scholar 

  7. Industrial Internet Consortium, Industrial Internet Reference Architecture, Version 1.7, 2015.

    Google Scholar 

  8. Presentation at the French Embassy in the Germany, “Industry of the future”, 2015. Available at. http://www.ambafrance-de.org/Vorstellung-des-neuen-franzosischen-Plans-Industrie-du-Futur-in-der-Botschaft. Last accessed: 24.11.2016

  9. The State Council of the People’s Republic of China, “Made in China 2025”, Available at: http://english.gov.cn/2016special/madeinchina2025/. Last accessed: 24.11.2016.

  10. Hermann, M., Pentek, T., & Otto, B. (2016, January). Design principles for industrie 4.0 scenarios. In 2016 49th Hawaii international conference on system sciences (HICSS) (pp. 3928-3937). IEEE.

    Google Scholar 

  11. Thomas Bauernhansl, Jörg Krüger, Gunther Reinhart, Günther Schuh: Wgp-Standpunkt Industrie4.0, Wissenschaftliche Gesellschaft für Produktionstechnik Wgp e. v., 2016.

    Google Scholar 

  12. Rojko, A. (2017). Industry 4.0 concept: background and overview. International Journal of Interactive Mobile Technologies (iJIM), 11(5), 77-90.

    Article  Google Scholar 

  13. Lee, H. Kao and S. Yang, “Service Innovation and Smart Analytics for Industry 4.0 and Big Data Environment”, Procedia CIRP, vol. 16, pp. 3-8, 2014. Available: https://doi.org/10.1016/j.procir.2014.02.001.

    Article  Google Scholar 

  14. K. Zhou, Taigang Liu and Lifeng Zhou, “Industry 4.0: Towards future industrial opportunities and challenges,” 2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), Zhangjiajie, 2015, pp. 2147-2152.

    Google Scholar 

  15. Gilchrist, A. (2016). Introducing Industry 4.0. In Industry 4.0 (pp. 195-215). Apress, Berkeley, CA.

    Google Scholar 

  16. Kumar, A., & Khorwal, R. (2017). Firefly algorithm for feature selection in sentiment analysis. In Computational Intelligence in Data Mining (pp. 693-703). Springer, Singapore.

    Google Scholar 

  17. Y, Lu, “Industry 4.0: A survey on technologies, applications and open research issues”, Journal of Industrial Information Integration, vol. 6, pp. 1-10, 2017. Available: https://doi.org/10.1016/j.jii.2017.04.005.

    Article  Google Scholar 

  18. Gilchrist, A. (2016). Industry 4.0: the industrial internet of things. Apress.

    Google Scholar 

  19. A. Gilchrist, “Middleware Industrial Internet of Things Platforms,” in Industry 4.0, Springer, 2016, pp. 153-160.

    Google Scholar 

  20. B. Yan and G. Huang, “Supply chain information transmission based on RFID and internet of things,” in 2009 ISECS International Colloquium on Computing, Communication, Control, and Management, 2009

    Google Scholar 

  21. R. Xu, L. Yang and S. H. Yang, “Architecture Design of Internet of Things in Logistics Management for Emergency Response,” in Green Computing and Communications (GreenCom), 2013 IEEE and Internet of Things (iThings/CPSCom), IEEE International Conference on and IEEE Cyber, Physical and Social Computing, 2013.

    Google Scholar 

  22. B. Karakostas, “A DNS architecture for the internet of things: A case study in transport logistics,” Procedia Computer Science, vol. 19, pp. 594-601, 2013.

    Article  Google Scholar 

  23. Jain, D. K., Kumar, A., Sangwan, S. R., Nguyen, G. N., & Tiwari, P. (2019). A Particle Swarm Optimized Learning Model of Fault Classification in Web-Apps. IEEE Access, 7, 18480-18489.

    Google Scholar 

  24. Gilchrist, A. (2016). Introducing Industry 4.0. In Industry 4.0(pp. 195-215). Apress, Berkeley, CA.

    Google Scholar 

  25. Gorecky, D., Schmitt, M., Loskyll, M., & Zühlke, D. (2014, July). Human-machine-interaction in the industry 4.0 era. In Industrial Informatics (INDIN), 2014 12th IEEE International Conference on (pp. 289)

    Google Scholar 

  26. Kumar, A., & Jaiswal, A. (2019). Systematic literature review of sentiment analysis on Twitter using soft computing techniques. Concurrency and Computation: Practice and Experience, e5107.

    Google Scholar 

  27. R. Drath, A. Horch, Industrie 4.0: Hit or Hype? [Industry Forum]. Industrial Electronics Magazine, IEEE 8 (2014) 56-58.

    Article  Google Scholar 

  28. Alzubi, J., Nayyar, A., & Kumar, A. (2018, November). Machine learning from theory to algorithms: an overview. In Journal of Physics: Conference Series (Vol. 1142, No. 1, p. 012012). IOP Publishing.

    Google Scholar 

  29. Kumar, A., & Sangwan, S. R. (2019). Rumor Detection Using Machine Learning Techniques on Social Media. In International Conference on Innovative Computing and Communications (pp. 213-221). Springer, Singapore.

    Google Scholar 

  30. M. Ford, Industry 4.0: Who Benefits? SMT: Surface Mount Technology 30 (2015) 52-55.

    Google Scholar 

  31. R. Schmidt, M. Möhring, R.-C. Härting, C. Reichstein, P. Neumaier, P. Jozinović, Industry 4.0 - Potentials for Creating Smart Products: Empirical Research Results, in: W. Abramowicz (Ed.), Business.

    Google Scholar 

  32. C.a.R. Hilger, J, Auto-ID integration-a bridge between worlds. German Harting Magazine (2013) 14-15.

    Google Scholar 

  33. H. Lasi, P. Fettke, H.-g. Kemper, T. Feld, M. Hoffmann, Industry 4.0. Business & Information Systems Engineering 6 (2014) 239-242.

    Google Scholar 

  34. J. A. Simpson, E.S. C. Weiner, and Oxford University Press, Eds., The Oxford English dictionary, 2nd ed. Oxford: Oxford; New York: Clar-endon Press; Oxford University Press, 1989.

    Google Scholar 

  35. Bhatia, M. P. S., & Kumar, A. (2010). Paradigm shifts: from pre-web information systems to recent web-based contextual information retrieval. Webology, 7(1), 1.

    Google Scholar 

  36. M. Kohlegger, R. Maier, and S. Thalmann, “Understanding Maturity Models Results of a structured Content Analysis,” presented at the I-KNOW ‘09 and I-SEMANTICS ‘09, Graz, Austria, 2009.

    Google Scholar 

  37. Industry 4.0: Definition, Design Principles, Challenges, and the Future of Employment, https://www.cleverism.com/industry-4-0/.

  38. https://www.forbes.com/sites/bernardmarr/2018/09/02/what-is-industry-4-0-heres-a-super-easy-explanation-for-anyone/#8105a7e9788a

  39. Geissbauer R, Vedso J, Schrauf S (2016) Industry 4.0: Building the digital enterprise. Retrieved from PwC Website: https://www.pwc.com/gx/en/industries/industries-4.0/landing-page/ industry-4.0-building-your-digital-enterprise-april-2016.pdf.

    Google Scholar 

  40. Gilchrist, A. (2016). Industry 4.0: the industrial internet of things. Apress.

    Google Scholar 

  41. Almada-Lobo, F. (2016). The Industry 4.0 revolution and the future of manufacturing execution systems (MES). Journal of innovation management, 3(4), 16-21.

    Article  Google Scholar 

  42. Bhatia, M. P. S., & Khalid, A. K. (2007, November). Contextual proximity based term-weighting for improved web information retrieval. In International Conference on Knowledge Science, Engineering and Management (pp. 267-278). Springer, Berlin, Heidelberg.

    Google Scholar 

  43. Schumacher, A., Erol, S., & Sihn, W. (2016). A maturity model for assessing industry 4.0 readiness and maturity of manufacturing enterprises. Procedia CIRP, 52, 161-166.

    Google Scholar 

  44. Kumar, A., & Goel, R. (2012, March). Event driven test case selection for regression testing web applications. In IEEE-International Conference On Advances In Engineering, Science And Management (ICAESM-2012) (pp. 121-127). IEEE.

    Google Scholar 

  45. K. Lichtblau, V. Stich, R. Bertenrath, M. Blum, M. Bleider, A. Millack, K. Schmitt, E. Schmitz, and M. Schröter, “IMPULS - Industrie 4.0-Readiness,” Impuls-Stiftung des VDMA, Aachen-Köln, 2015.

    Google Scholar 

  46. Rockwell Automation. (2016). The Connected Enterprise Maturity Model. Retrieved from Website:http://literature.rockwellautomation.com/idc/groups/literature/documents/wp/ciewp002_-en-p.pdf.

  47. IMPULS-Industrie 4.0-Readiness. Impuls-Stiftung des VDMA, Aachen-Köln.

    Google Scholar 

  48. A. Sharma, R. Ranjan, “Software Effort Estimation using Neuro Fuzzy Inference System: Past and Present” published in International Journal on Recent Innovation Trends in Computing and Communication (IJRITCC), ISSN: 2321-8169, Vol.5, Issue.8, Pp: 78-83.

    Google Scholar 

  49. Schumacher A, Erol S, Sihn W (2016) A maturity model for assessing industry 4.0 readiness and maturity of manufacturing enterprises. Procedia CIRP 52:161–166.

    Article  Google Scholar 

  50. http://www.apics.org/apics-for-individuals/apics-magazine-home/magazine-detail-page/2017/09/20/industry-1.0-to-4.0-the-evolution-of-smart-factories

  51. Kumar, A., & Joshi, A. (2017, March). SentIndiGov-O: an Ontology-based Tool for Sentiment Analysis to Empower Digital Governance. In Proceedings of the 10th International Conference on Theory and Practice of Electronic Governance(pp. 576-577). ACM.

    Google Scholar 

  52. Kumar, A., & Sharma, A. (2013). Alleviating sparsity and scalability issues in collaborative filtering based recommender systems. In Proceedings of the International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA) (pp. 103-112). Springer, Berlin, Heidelberg.

    Google Scholar 

  53. Batth, R. S., Nayyar, A., & Nagpal, A. (2018, August). Internet of Robotic Things: Driving Intelligent Robotics of Future-Concept, Architecture, Applications and Technologies. In 2018 4th International Conference on Computing Sciences (ICCS)(pp. 151-160). IEEE.

    Google Scholar 

  54. Nayyar, A., Puri, V., & Le, D. N. (2017). Internet of nano things (IoNT): Next evolutionary step in nanotechnology. Nanoscience and Nanotechnology, 7(1), 4-8

    Google Scholar 

  55. Nayyar, A., Jain, R., Mahapatra, B., & Singh, A. (2019). Cyber Security Challenges for Smart Cities. In Driving the Development, Management, and Sustainability of Cognitive Cities (pp. 27-54). IGI Global.

    Google Scholar 

  56. Gorecky, D., Schmitt, M., Loskyll, M., & Zühlke, D. (2014, July). Human-machine-interaction in the industry 4.0 era. In Industrial Informatics (INDIN), 2014 12th IEEE International Conference on (pp. 289-294). IEEE.

    Google Scholar 

  57. Robert, K. W., Parris, T. M., & Leiserowitz, A. A. (2005). What is sustainable development? Goals, indicators, values, and practice. Environment: science and policy for sustainable development, 47(3), 8-21.

    Google Scholar 

  58. Labuschagne, C., Brent, A. C., & Van Erck, R. P. (2005). Assessing the sustainability performances of industries. Journal of cleaner production, 13(4), 373-385.

    Google Scholar 

  59. Kumar, A., Sharma, A., Sharma, S., & Kashyap, S. (2017, July). Performance analysis of keyword extraction algorithms assessing extractive text summarization. In 2017 International Conference on Computer, Communications and Electronics (Comptelix) (pp. 408-414). IEEE.

    Google Scholar 

  60. Rokon Zaman, Industry 4.0 Drives the Sustainable Development Goals, Waves, https://techpolicyviews.com/review-updates/2018/11/18/industry-4-0-drives-the-sustainable-development-goals/

  61. Kumar, A., & Bhatia, M. P. S. (2012). Community expert based recommendation for solving first rater problem. International Journal of Computer Applications, 37(10), 7-13.

    Google Scholar 

  62. Lukman, R. K., Glavič, P., Carpenter, A., & Virtič, P. (2016). Sustainable consumption and production–Research, experience, and development–The Europe we want. Journal of cleaner production, 138, 139-147.

    Google Scholar 

  63. Kumar, A., & Joshi, A. (2017, March). Ontology driven sentiment analysis on social web for government intelligence. In Proceedings of the Special Collection on eGovernment Innovations in India (pp. 134-139). ACM.

    Google Scholar 

  64. Das, S., & Nayyar, A. (2019). Innovative Ideas to Manage Urban Traffic Congestion in Cognitive Cities. In Driving the Development, Management, and Sustainability of Cognitive Cities (pp. 139-162). IGI Global.

    Google Scholar 

  65. Ranjan, R., & Sharma, A. (2019). Evaluation of Frequent Itemset Mining Platforms using Apriori and FP-Growth Algorithm. arXiv preprint arXiv:1902.10999e.

    Google Scholar 

  66. Kumar, A., & Sebastian, T. M. (2012). Machine learning assisted sentiment analysis. In Proceedings of International Conference on Computer Science & Engineering (ICCSE’2012) (pp. 123-130).

    Google Scholar 

  67. Kumar, A., Khorwal, R., & Chaudhary, S. (2016). A survey on sentiment analysis using swarm intelligence. Indian J Sci Technol, 9(39), 1-7.

    Google Scholar 

  68. Singh, S. P., Nayyar, A., Kaur, H., & Singla, A. (2019). Dynamic Task Scheduling using Balanced VM Allocation Policy for Fog Computing Platforms. Scalable Computing: Practice and Experience, 20(2), 433-456.

    Google Scholar 

  69. Singh, S. P., Nayyar, A., Kumar, R., & Sharma, A. (2019). Fog computing: from architecture to edge computing and big data processing. The Journal of Supercomputing, 75(4), 2070-2105.

    Google Scholar 

  70. Solanki, A., & Nayyar, A. (2019). Green Internet of Things (G-IoT): ICT Technologies, Principles, Applications, Projects, and Challenges. In Handbook of Research on Big Data and the IoT (pp. 379-405). IGI Global.

    Google Scholar 

  71. Bhatia, M. P. S., & Kumar, A. (2009). Contextual paradigm for ad hoc retrieval of user-centric web data. IET software, 3(4), 264-275.

    Google Scholar 

  72. Kumar, A., Sharma, A., & Arora, A. (2019). Anxious Depression Prediction in Real-time Social Data. arXiv preprint arXiv:1903.10222.

    Google Scholar 

  73. Kumar, A., & Sharma, A. (2017). Systematic literature review on opinion mining of big data for government intelligence. Webology, 14(2), 6-47

    Google Scholar 

  74. Singh, P., Gupta, P., Jyoti, K., & Nayyar, A. (2019). Research on Auto-Scaling of Web Applications in Cloud: Survey, Trends and Future Directions. Scalable Computing: Practice and Experience, 20(2), 399-432.

    Google Scholar 

  75. Kaur, A., Gupta, P., Singh, M., & Nayyar, A. (2019). Data Placement in Era of Cloud Computing: a Survey, Taxonomy and Open Research Issues. Scalable Computing: Practice and Experience, 20(2), 377-398.

    Google Scholar 

  76. Kumar, A., & Ahmad, N. (2012). ComEx miner: Expert mining in virtual communities. International Journal of Advanced Computer Science and Applications (IJACSA), 3(6).

    Google Scholar 

  77. Kumar, A., & Sharma, A. (2019). (1706-3727) SYSTEMATIC LITERATURE REVIEW OF FUZZY LOGIC BASED TEXT SUMMARIZATION. Iranian Journal of Fuzzy Systems.

    Google Scholar 

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Delhi Technological University, New Delhi, India

    Akshi Kumar

  2. Graduate School, Duy Tan University, Da Nang, Vietnam

    Anand Nayyar

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  1. Akshi Kumar
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Correspondence to Anand Nayyar .

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Editors and Affiliations

  1. Graduate School, Duy Tan University, Da Nang, Vietnam

    Anand Nayyar

  2. Department of Computer Science and Engineering, Delhi Technological University, New Delhi, India

    Akshi Kumar

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Kumar, A., Nayyar, A. (2020). si3-Industry: A Sustainable, Intelligent, Innovative, Internet-of-Things Industry. In: Nayyar, A., Kumar, A. (eds) A Roadmap to Industry 4.0: Smart Production, Sharp Business and Sustainable Development. Advances in Science, Technology & Innovation. Springer, Cham. https://doi.org/10.1007/978-3-030-14544-6_1

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