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2020 | OriginalPaper | Chapter

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

Authors : Akshi Kumar, Anand Nayyar

Published in: A Roadmap to Industry 4.0: Smart Production, Sharp Business and Sustainable Development

Publisher: Springer International Publishing

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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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next chapter Development of Industry 4.0
Literature
1.
2.
Götz, M., & Jankowska, B. (2017). Clusters and Industry 4.0–do they fit together?. European Planning Studies, 25(9), 1633-1653.
3.
Lasi, H., Fettke, P., Kemper, H. G., Feld, T., & Hoffmann, M. (2014). Industry 4.0. Business & information systems engineering, 6(4), 239-242.
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.
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.
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.
7.
Industrial Internet Consortium, Industrial Internet Reference Architecture, Version 1.7, 2015.
8.
9.
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.
11.
Thomas Bauernhansl, Jörg Krüger, Gunther Reinhart, Günther Schuh: Wgp-Standpunkt Industrie4.0, Wissenschaftliche Gesellschaft für Produktionstechnik Wgp e. v., 2016.
12.
Rojko, A. (2017). Industry 4.0 concept: background and overview. International Journal of Interactive Mobile Technologies (iJIM), 11(5), 77-90.CrossRef
13.
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.
15.
Gilchrist, A. (2016). Introducing Industry 4.0. In Industry 4.0 (pp. 195-215). Apress, Berkeley, CA.
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.
17.
18.
Gilchrist, A. (2016). Industry 4.0: the industrial internet of things. Apress.
19.
A. Gilchrist, “Middleware Industrial Internet of Things Platforms,” in Industry 4.0, Springer, 2016, pp. 153-160.
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
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.
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.CrossRef
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.
24.
Gilchrist, A. (2016). Introducing Industry 4.0. In Industry 4.0(pp. 195-215). Apress, Berkeley, CA.
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)
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.
27.
R. Drath, A. Horch, Industrie 4.0: Hit or Hype? [Industry Forum]. Industrial Electronics Magazine, IEEE 8 (2014) 56-58.CrossRef
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.
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.
30.
M. Ford, Industry 4.0: Who Benefits? SMT: Surface Mount Technology 30 (2015) 52-55.
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.
32.
C.a.R. Hilger, J, Auto-ID integration-a bridge between worlds. German Harting Magazine (2013) 14-15.
33.
H. Lasi, P. Fettke, H.-g. Kemper, T. Feld, M. Hoffmann, Industry 4.0. Business & Information Systems Engineering 6 (2014) 239-242.
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.
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.
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.
37.
38.
39.
40.
Gilchrist, A. (2016). Industry 4.0: the industrial internet of things. Apress.
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.CrossRef
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.
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.
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.
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.
46.
47.
IMPULS-Industrie 4.0-Readiness. Impuls-Stiftung des VDMA, Aachen-Köln.
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.
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.CrossRef
50.
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.
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.
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.
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
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.
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.
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.
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.
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.
60.
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.
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.
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.
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.
65.
Ranjan, R., & Sharma, A. (2019). Evaluation of Frequent Itemset Mining Platforms using Apriori and FP-Growth Algorithm. arXiv preprint arXiv:1902.10999e.
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).
67.
Kumar, A., Khorwal, R., & Chaudhary, S. (2016). A survey on sentiment analysis using swarm intelligence. Indian J Sci Technol, 9(39), 1-7.
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.
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.
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.
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.
72.
Kumar, A., Sharma, A., & Arora, A. (2019). Anxious Depression Prediction in Real-time Social Data. arXiv preprint arXiv:1903.10222.
73.
Kumar, A., & Sharma, A. (2017). Systematic literature review on opinion mining of big data for government intelligence. Webology, 14(2), 6-47
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.
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.
76.
Kumar, A., & Ahmad, N. (2012). ComEx miner: Expert mining in virtual communities. International Journal of Advanced Computer Science and Applications (IJACSA), 3(6).
77.
Kumar, A., & Sharma, A. (2019). (1706-3727) SYSTEMATIC LITERATURE REVIEW OF FUZZY LOGIC BASED TEXT SUMMARIZATION. Iranian Journal of Fuzzy Systems.
Metadata
Title
si3-Industry: A Sustainable, Intelligent, Innovative, Internet-of-Things Industry
Authors
Akshi Kumar
Anand Nayyar
Copyright Year
2020
Book
A Roadmap to Industry 4.0: Smart Production, Sharp Business and Sustainable Development

Print ISBN: 978-3-030-14543-9

Electronic ISBN: 978-3-030-14544-6

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-030-14544-6_1