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A service-oriented middleware framework for manufacturing industry 4.0

Published: 13 November 2018 Publication History

Abstract

The advantages of the Internet of things (IoT) initiated the vision of Industry 4.0 in Europe and smart manufacturing in USA. Both visions aim to implement the smart factory to achieve similar objectives by utilizing new technologies. These technologies include cloud computing, fog computing, cyber-physical systems (CPS), and data analytics. Together they help automate and autonomize the manufacturing processes and controls to optimize the productivity, reliability, quality, cost-effeteness, and safety of these processes. While both visions are promising, developing and operating Industry 4.0 applications are extremely challenging. This is due to the complexity of the manufacturing processes as well as their management, controls, and integration dynamics. This paper introduces Man4Ware, a service-oriented middleware for Industry 4.0. Man4Ware can help facilitate the development and operations of cloud and fog-integrated smart manufacturing applications. Man4Ware offers many advantages through service level interfaces to enable easy utilization of new technologies and integration of different services to relax many of the challenges facing the development and operations of such applications1.

References

[1]
H. Lasi, P. Fettke, H.G. Kemper, T. Feld, and M. Hoffmann. Industry 4.0. Business & Information Systems Engineering, 6(4), pp.239--242, 2014.
[2]
H.S. Kang et al. Smart manufacturing: Past research, present findings, and future directions. International Journal of Precision Engineering and Manufacturing-Green Technology 3, no. 1: 111--128, 2016.
[3]
C. Yang, W. Shen, and X. Wang. Applications of Internet of Things in manufacturing. In IEEE 20th International Conference on Computer Supported Cooperative Work in Design, pp. 670--675, IEEE, 2016.
[4]
F. Tao, et al. CCIoT-CMfg: Cloud computing and Internet of Things based cloud manufacturing service system. IEEE Transactions on Industrial Informatics, 10(2), 1435--1442, 2014.
[5]
R.F. Babiceanu and R. Seker. Manufacturing cyber-physical systems enabled by complex event processing and big data environments: a framework for development. In Service Orientation in Holonic and Multi-agent Manufacturing, pp. 165--173), Springer, Cham, 2015.
[6]
X. Xu. From cloud computing to cloud manufacturing. Robotics and computer-integrated manufacturing, 28(1), pp.75--86, 2012.
[7]
D. Wu, et al. A fog computing-based framework for process monitoring and prognosis in cyber-manufacturing. Journal of Manufacturing Systems, 43, pp.25--34, 2017.
[8]
S. Jain, G. Shao, and S.J. Shin. Manufacturing data analytics using a virtual factory representation. International Journal of Production Research, 55(18), pp.5450--5464, 2017.
[9]
J. Al-Jaroodi and N. Mohamed. Service-Oriented Middleware: A Survey. The Journal of Network and Computer Applications, Elsevier, Vol. 35, No. 1, pp. 211--220, Jan. 2012.
[10]
N. Mohamed and J. Al-Jaroodi. Service-Oriented Middleware Approaches for Wireless Sensor Networks. In proc. 44<sup>th</sup> Hawaii Int'l Conference on System Sciences (HICSS'44), IEEE Computer Society Press, 2011.
[11]
Web link. Industry 4.0. Wikipedia. Available at: https://en.wikipedia.org/wiki/Industry_4.0
[12]
B. Marr. What Everyone Must Know About Industry 4.0. In Forbes - Tech. June 20, 2016. Available at: https://www.forbes.com/sites/bernardmarr/2016/06/20/what-everyone-must-know-about-industry-4-0/#71791477795f
[13]
F. Almada-Lobo. The Industry 4.0 revolution and the future of manufacturing execution systems (MES). Journal of Innovation Management 3, no. 4: 16--21, 2016.
[14]
K. Zhou, T. Liu, and L. Zhou. Industry 4.0: Towards future industrial opportunities and challenges. In 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), pp. 2147--2152, IEEE, 2015.
[15]
J. Lee, et al. A cyber-physical systems architecture for industry 4.0-based manufacturing systems. Manufacturing Letters 3: 18--23, 2015.
[16]
G. Peralta, M. Iglesias-Urkia, M. Barcelo, R. Gomez, A. Moran, and J. Bilbao. Fog computing based efficient IoT scheme for the Industry 4.0. In IEEE International Workshop of Electronics, Control, Measurement, Signals and their Application to Mechatronics (ECMSM), IEEE, 2017.
[17]
Z. Yuan, W. Qin, and J. Zhao. Research: Smart Manufacturing for the Oil Refining and Petrochemical Industry. Engineering 3, 179--182. ScienceDirect, 2017.
[18]
Y. Zhang and J. Wen. The IoT electric business model: Using blockchain technology for the internet of things. Peer-to-Peer Networking and Applications, 10(4), pp.983--994, 2017.
[19]
S.A. Abeyratne and R.P. Monfared. Blockchain ready manufacturing supply chain using distributed ledger. International Journal of Research in Engineering and Technology, 05(09), pp. 1--10, 2016.
[20]
S. Weyer, et al. Towards Industry 4.0-Standardization as the crucial challenge for highly modular, multi-vendor production systems. Ifac-Papersonline 48, no. 3: 579--584, 2015.
[21]
Y. Lu, K. C. Morris, and S. Frechette. Current standards landscape for smart manufacturing systems. National Institute of Standards and Technology, NISTIR 8107: 22--28, 2016.
[22]
SMLC, 2010, June. Implementing 21st century smart manufacturing. Workshop summary report. Available at: https://smartmanufacturingcoalition.org/sites/default/files/implementing_21st_century_smart_manufacturing_report_2011_0.pdf
[23]
P. Lalanda, D. Morand, and S. Chollet. Autonomic mediation middleware for smart manufacturing. IEEE Internet Computing 21, no. 1: 32--39, 2017.
[24]
I. Ungurean, N.C. Gaitan, and V.G. Gaitan. A Middleware Based Architecture for the Industrial Internet of Things. KSII Transactions on Internet & Information Systems 10, no. 7, 2016.
[25]
S. Wang, et al. Towards smart factory for industry 4.0: a self-organized multi-agent system with big data based feedback and coordination. Computer Networks 101: 158--168, 2016.
[26]
I. Grangel-González, et al. Towards a semantic administrative shell for industry 4.0 components. In IEEE Tenth International Conference on Semantic Computing (ICSC), pp. 230--237. IEEE, 2016.
[27]
M.A. Pisching, F. Junqueira, D.D. Santos Filho, D.D. and P.E. Miyagi. An Architecture for Organizing and Locating Services to the Industry 4.0. In ABCM International Congress of Mechanical Engineering. 2015.
[28]
D.F. Sadok, L.L. Gomes, M. Eisenhauer, and J. Kelner. A middleware for industry. Computers in Industry 71: 58--76, 2015.
[29]
A. Cannata, M. Gerosa, and M. Taisch. A Technology Roadmap on SOA for smart embedded devices: Towards intelligent systems in manufacturing. In IEEE International Conference on Industrial Engineering and Engineering Management, pp. 762--767, IEEE, 2008.
[30]
L. Gurgen, C. Roncancio, C. Labbé, A. Bottaro, and V. Olive. SStreaMWare: a service oriented middleware for heterogeneous sensor data management. In Proc. of the 5th international conference on Pervasive services, pp. 121--130. ACM, 2008.
[31]
Z. Song, Y. Sun, J. Wan, and P. Liang. Data quality management for service-oriented manufacturing cyber-physical systems. Computers & Electrical Engineering 64: 34--44, 2017.
[32]
J. Lee, H.A. Kao, and S. Yang. Service innovation and smart analytics for industry 4.0 and big data environment. Procedia Cirp 16: 3--8, 2014.
[33]
P. O'Donovan, K. Leahy, K Bruton, and D. T. J. O'Sullivan. An industrial big data pipeline for data-driven analytics maintenance applications in large-scale smart manufacturing facilities. Journal of Big Data 2, no. 1: 25, 2015.
[34]
S. Wang, J. Wan, D. Li, and C. Zhang. Implementing smart factory of industrie 4.0: an outlook. International Journal of Distributed Sensor Networks 12, no. 1, 2016.
[35]
F. Tao, et al. "CCIoT-CMfg: cloud computing and internet of things-based cloud manufacturing service system. IEEE Transactions on Industrial Informatics 10, no. 2: 1435--1442, 2014.
[36]
A. Juan-Verdejo and B. Surajbali. Xaas Multi-Cloud marketplace architecture enacting the industry 4.0 concepts. In Doctoral Conference on Computing, Electrical and Industrial Systems, pp. 11--23. Springer, 2016.
[37]
D. Brito, et al. Towards programmable fog nodes in smart factories. In IEEE International Workshops on Foundations and Applications of Self* Systems, pp. 236--241. IEEE, 2016.

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Published In

cover image ACM SIGBED Review
ACM SIGBED Review  Volume 15, Issue 5
October 2018
30 pages
EISSN:1551-3688
DOI:10.1145/3292384
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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 November 2018
Published in SIGBED Volume 15, Issue 5

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Author Tags

  1. IoT
  2. cloud computing
  3. cyber-physical systems
  4. fog computing
  5. industry 4.0
  6. middleware
  7. smart manufacturing

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  • (2024)Component integration manufacturing middleware for customized productionAdvanced Engineering Informatics10.1016/j.aei.2023.10231759:COnline publication date: 1-Jan-2024
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