Development of an industrial Internet of things suite for smart factory towards re-industrialization

C. K. M. Lee , S. Z. Zhang , K. K. H. Ng

Advances in Manufacturing ›› 2017, Vol. 5 ›› Issue (4) : 335 -343.

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Advances in Manufacturing ›› 2017, Vol. 5 ›› Issue (4) : 335 -343. DOI: 10.1007/s40436-017-0197-2
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Development of an industrial Internet of things suite for smart factory towards re-industrialization

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Abstract

Re-industrialization, which supports industrial upgrading and transformation, promotes smart production and high value-added manufacturing processes, and helps to create new momentum for the economic. Under the current situation, industrialists encounter several challenges to achieve re-industrialization. Firstly, the cost and technical thresholds for industrialists to leverage emerging technologies are high. Secondly, there are huge quantities and numerous types of Internet of things (IoT) devices in smart factories, warehouses and offices. The enormous extents of data exchange and communication, management, monitoring and control of IoT devices as well as the establishment and maintenance of a reliable cloud platform hinder industrialists to implement an integrated smart production management. Therefore, to achieve re-industrialization, an industrial Internet of things (IIoT) suite consisting of a micro-services-based IIoT cloud platform and IIoT-based smart hub is proposed, which helps to materialize re-industrialization and to conduct industrial upgrading and transformation to achieve smart production and high value-added manufacturing processes.

Keywords

Industrial Internet of things (IIoTs) / Cloud platform / Micro-services-based / Industry 4.0 / Re-industrialization

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C. K. M. Lee, S. Z. Zhang, K. K. H. Ng. Development of an industrial Internet of things suite for smart factory towards re-industrialization. Advances in Manufacturing, 2017, 5(4): 335-343 DOI:10.1007/s40436-017-0197-2

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References

[1]

Kollmeyer C. Explaining deindustrialization: how affluence, productivity growth, and globalization diminish manufacturing employment. Am J Sociol, 2009, 114: 1644-1674.

[2]

Chen J. Macro-control and economic development in China, 2016, London: Routledge

[3]

Dixon M, Jonas S, McCaughan E, et al. Reindustrialization and the transnational labor force in the United States today. Contemp Marx, 1982, 5: 101-115.

[4]

Taplin I, Nguyen MTT (2016) 5 from recession to re-industrialization. In: Begley J, Coffey D, Donnelly T et al (eds) Global economic crisis and local economic development: international cases and policy responses. Routledge, New York, p 78

[5]

Chen M, Mao S, Liu Y, et al. Big data: a survey. Mobile Netw Appl, 2014, 19: 171-209.

[6]

Lee J, Bagheri B, Kao HA, et al. A cyber-physical systems architecture for Industry 4.0-based manufacturing systems. Manuf Lett, 2015, 3: 18-23.

[7]

Tao F, Zuo Y, Xu LD, et al. IoT-based intelligent perception and access of manufacturing resource toward cloud manufacturing. IEEE Trans Ind Inf, 2014, 10: 1547-1557.

[8]

Zhang S, Zhang S, Chen X et al (2010) Analysis and research of cloud computing system instance. In: The second international conference on future networks, pp 88–92

[9]

Qiu M, Xue C, Shao Z et al (2006) Efficient algorithm of energy minimization for heterogeneous wireless sensor network. In: International conference on embedded and ubiquitous computing, Seoul, Korea, pp 25–34

[10]

Lin CC, Deng DJ, Chen ZY, et al. Key design of driving Industry 4.0: joint energy-efficient deployment and scheduling in group-based industrial wireless sensor networks. IEEE Commun Mag, 2016, 54: 46-52.

[11]

Li X, Li D, Wan J, et al. A review of industrial wireless networks in the context of Industry 4.0. Wirel Netw, 2017, 23(1): 23-41.

[12]

Waibel M, Beetz M, Civera J, et al. A world wide web for robots. IEEE Robot Autom Mag, 2011, 18: 69-82.

[13]

Zhang Y, Qiu M, Tsai CW, et al. Health-CPS: healthcare cyber-physical system assisted by cloud and big data. IEEE Syst J, 2015, 11(1): 88-95.

[14]

Pirvu BC, Zamfirescu CB, Gorecky D, et al. Engineering insights from an anthropocentric cyber-physical system: a case study for an assembly station. Mechatronics, 2016, 34: 147-159.

[15]

Chen F, Deng P, Wan J, et al. Data mining for the internet of things: literature review and challenges. Int J Distrib Sens Netw, 2015, 9: 12

[16]

Xu LD, He W, Li S, et al. Internet of things in industries: a survey. IEEE Trans Industr Inf, 2014, 10: 2233-2243.

[17]

Weyrich M, Ebert C. Reference architectures for the internet of things. IEEE Softw, 2016, 33: 112-116.

[18]

Wang S, Wan J, Zhang D, et al. Towards smart factory for Industry 4.0: a self-organized multi-agent system with big data based feedback and coordination. Comput Netw, 2016, 101: 158-168.

[19]

Palattella MR, Accettura N, Grieco LA, et al. On optimal scheduling in duty-cycled industrial IoT applications using IEEE802.15.4e TSCH. IEEE Sens J, 2013, 13(10): 3655-3666.

[20]

Gorecky D, Schmitt M, Loskyll M et al (2014) Human-machine-interaction in the Industry 4.0 era. In: The 12th IEEE international conference on industrial informatics (INDIN), Porto Alegre, Brazil, pp 289–294

[21]

Lee EA (2008) Cyber physical systems: design challenges. In: The 11th IEEE international symposium on object oriented real-time distributed computing (ISORC), Orlando, Florida, p 363–369

[22]

Kang W, Kapitanova K, Son SH, et al. RDDS: a real-time data distribution service for cyber-physical systems. IEEE Trans Ind Inf, 2012, 8(2): 393-405.

[23]

Gossman WE, Hartmaier PJ (2001) System and method for providing data to a wireless device upon detection of activity of the device on a wireless network. US Patent 6317594 B1, 13 Nov 2001

[24]

Santos A, Nunes G, Gil P, et al. Multi-agent platform in wsan applications: a time synchronization perspective. IFAC Proc Vol, 2010, 43: 367-374.

[25]

Colombo AW, Bangemann T, Karnouskos S, et al. Industrial cloud-based cyber-physical systems, 2014, Berlin: Springer 15-16.

[26]

Trappey AJ, Trappey CV, Govindarajan UH, et al. A review of essential standards and patent landscapes for the Internet of things: a key enabler for Industry 4.0. Adv Eng Inform, 2016

[27]

Kagermann H, Helbig J, Hellinger A et al (2013) Recommendations for Implementing the strategic initiative Industrie 4.0: securing the future of German manufacturing industry. Final report of the Industrie 4.0 working group, Forschungsunion

[28]

Qin J, Liu Y, Grosvenor R, et al. A categorical framework of manufacturing for Industry 4.0 and beyond. Proc CIRP, 2016, 52: 173-178.

[29]

Lee CKM, Yi C, Ng KH (2017) Big data analytics for predictive maintenance strategis. In: Chan HK, Subramanian N, Abdulrahman MDA (eds) Supply chain management in the big data era. IGI Global, Hershey, PA, pp 50–74

[30]

Mikusz M. Towards an understanding of cyber-physical systems as industrial software-product-service systems. Proc CIRP, 2014, 16: 385-389.

[31]

Monostori L. Cyber-physical production systems: roots, expectations and R&D challenges. Proc CIRP, 2014, 17: 9-13.

[32]

Lee J, Bagheri B, Kao HA, et al. A cyber-physical systems architecture for Industry 4.0-based manufacturing systems. Manuf Lett, 2015, 3: 18-23.

[33]

Pang Z, Chen Q, Tian J et al (2013) Ecosystem analysis in the design of open platform-based in-home healthcare terminals towards the internet-of-things. In: The 15th international conference on advanced communication technology (ICACT), pp 529–534

[34]

Wei QP, Zhu SB, Du CQ, et al. Study on key technologies of Internet of things perceiving mine. Proc Eng, 2011, 26(4): 2326-2333.

Funding

Industrial Collaborative Research(H-ZDAR)

Department of Industrial and Systems Engineering, Hong Kong Polytechnic University http://dx.doi.org/10.13039/501100006066(R-U8H)

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