The internet of things for smart manufacturing: A review

References

• Adamson, G., Wang, L. and Moore, P. (2017) Feature-based control and information framework for adaptive and distributed manufacturing in cyber physical systems. Journal of Manufacturing Systems, 43, 305–315.
   Web of Science ®Google Scholar
• Aitzhan, N.Z. and Svetinovic, D. (2016) Security and privacy in decentralized energy trading through multi-signatures, blockchain and anonymous messaging streams. IEEE Transactions on Dependable and Secure Computing, 99, 1–1.
   Google Scholar
• Akyildiz, I.F. Su, W., Sankarasubramaniam, Y. and Cayirci, E. (2002) Wireless sensor networks: A survey. Computer Networks, 38(4), 393–422.
   Web of Science ®Google Scholar
• Albert, R, and Barabási, A. (2002) Statistical mechanics of complex networks. Reviews of Modern Physics, 74(1), 47–97.
   Web of Science ®Google Scholar
• Amiri, A. (2016) Application placement and backup service in computer clustering in Software as a Service (SaaS) networks. Computers & Operations Research, 69, 48–55.
   Web of Science ®Google Scholar
• Ashton, K. (2009) That ‘Internet of Things’ thing, in the real world, things matter more than ideas. Available at http://www.rfidjournal.com/articles/view?4986.
   Google Scholar
• Babiceanu, B.F. and Seker, R. (2016) "Big Data and virtualization for manufacturing cyber-physical systems: A survey of the current status and future outlook. Computers in Industry, 81, 128–137.
   Web of Science ®Google Scholar
• Bahga, A. and Madisetti, V.K. (2016) Blockchain platform for industrial internet of things. Journal of Software Engineering and Applications, 9(10), 533–546.
   Google Scholar
• Bao, Y., Ren, L., Zhang, L., Zhang, X. and Luo, Y. (2012) Massive sensor data management framework in cloud manufacturing based on hadoop, in IEEE 10th International Conference on Industrial Informatics, IEEE Press, Piscataway, NJ, pp. 397–401.
   Google Scholar
• Beyca, O.F., Rao, P.K., Kong, Z., Bukkapatnam, STS. and Komanduri, R. (2016) Heterogeneous sensor data fusion approach for real-time monitoring in ultraprecision machining (UPM) process using non-parametric Bayesian clustering and evidence theory. IEEE Transactions on Automation Science and Engineering, 13(2), 1033–1044.
   Web of Science ®Google Scholar
• Bian, L., Gebraeel, N. and Kharoufeh, J.P. (2015) Degradation modeling for real-time estimation of residual lifetimes in dynamic environments. IIE Transactions, 4(5), 471–486.
   Google Scholar
• Boos, D., Guenter, H., Grote, G. and Kinder, K. (2013) Controllable accountabilities: the Internet of Things and its challenges for organisations. Behaviour & Information Technology, 32(5), 449–467.
   Web of Science ®Google Scholar
• Box, G.E.P. and Meyer, R.D. (1986) An analysis for unreplicated fractional factorials, Technometrics, 28(1), 11–18.
   Web of Science ®Google Scholar
• Braaksma, A.J.J., Meesters, A.J., Klingenberg, W. and Hicks, C. (2012) A quantitative method for failure mode and effects analysis. International Journal of Production Research, 5(23), 6904–6917.
   Google Scholar
• Bronstein, A.M., Bronstein, M.M. and Kimmel, R. (2006) Generalized multidimensional scaling: A framework for isometry-invariant partial surface matching. Proceedings of the National Academy of Sciences of the United States of America, 103(5),1168–1172.
   PubMed Web of Science ®Google Scholar
• Bukkapatnam, S., Kumara, S., Lakhtakia, A. and Srinivasan, P. (2002) Neighborhood method and its coupling with the wavelet method for nonlinear signal separation of contaminated chaotic time-series data. Signal Processing, 82, 1351–1374.
   Web of Science ®Google Scholar
• Bukkapatnam, S., Yang, H. and Modhavi, F. (2009) Towards prediction of nonlinear and nonstationary evolution of customer preferences using local Markov models, in The Art and Science Behind Successful Product Launches,. Springer, Dordrecht, pp. 271–287.
   Google Scholar
• Bukkapatnam, S.T., Kumara, S.R. and Lakhtakia, A. (2000) Fractal estimation of flank wear in turning. Journal of Dynamic Systems, Measurement, and Control, 122(1), 89–94.
   Web of Science ®Google Scholar
• Bukkapatnam, S.T.S. and Cheng, C. (2010) Forecasting the evolution of nonlinear and nonstationary systems using recurrence-based local Gaussian process models. Physical Review E, 82(5), 056206.
   Web of Science ®Google Scholar
• Bukkapatnam, S.T.S., Kumara, S.R. and Lakhtakia, A. (1999a) Local eigenfunctions-based suboptimal wavelet packet representation of contaminated chaotic signals. IMA Journal of Applied Mathematics, 63, 149–160.
   Web of Science ®Google Scholar
• Bukkapatnam, S.T.S., Kumara, S.R. and Lakhtakia, A. (1999b) Analysis of acoustic emission signals in machining. ASME Transactions on Manufacturing Science and Engineering, 121, 568–573.
   Web of Science ®Google Scholar
• Bukkapatnam, S.T.S., Lakhtakia, A. and Kumara, S.R.T. (1995) Analysis of sensor signals shows turning on a lathe exhibits low-dimensional chaos. Physical Review E, 52(3), 2375–2387.
   Web of Science ®Google Scholar
• Chen, Y. and Yang, H. (2012a) Multiscale recurrence analysis of long-term nonlinear and nonstationary time series, Chaos, Solitons & Fractals, vol. 45, no. 7, pp. 978–987, 2012.
   Web of Science ®Google Scholar
• Chen, Y. and Yang, H. (2012b) Self-organized neural network for the quality control of 12-lead ECG signals. Physiological Measurement, 33(9), 1399.
   Web of Science ®Google Scholar
• Chen, Y. and Yang, H., (2016a) A novel information-theoretic approach for variable clustering and predictive modeling using Dirichlet process mixtures, Scientific Reports, 6, 1–13.
   PubMed Web of Science ®Google Scholar
• Chen, Y. and Yang, H. (2016b) Heterogeneous recurrence representation and quantification of dynamic transitions in continuous nonlinear processes. The European Physical Journal B, 89(6), pp. 155, 2016.
   Web of Science ®Google Scholar
• Chen, Y. and Yang, H. (2016c) Sparse modeling and recursive prediction of space–time dynamics in stochastic sensor networks. IEEE Transactions on Automation Science and Engineering, 13(1) 215–226.
   Web of Science ®Google Scholar
• Cheng, C., Kan C. and Yang, H. (2016) Heterogeneous recurrence analysis of heartbeat dynamics for the identification of sleep apnea events. Computers in Biology and Medicine, 75, 10–18.
   PubMed Web of Science ®Google Scholar
• Cheng, C., Sa-Ngasoongsong, A., Beyca, O., Le, T., Yang, H., Kong, Z. and Bukkapatnam, S.T.S. (2015) Time series forecasting for nonlinear and non-stationary processes: A review and comparative study. IIE Transactions, 47(10), 1053–1071.
   Web of Science ®Google Scholar
• Cheng, T., Migliaccio, G.C., Jochen, T. and Gatti, U.C. (2013) Data fusion of real-time location sensing and physiological status monitoring for ergonomics analysis of construction workers. Journal of Computing in Civil Engineering, 27(3), 320–335.
   Web of Science ®Google Scholar
• Cheng, Y., Tao, F., Xu, L. and Zhao, D. (2016) Advanced manufacturing systems: Supply–demand matching of manufacturing resource based on complex networks and internet of things, Enterprise Information Systems, 12(7), 1–18.
   Web of Science ®Google Scholar
• Christidis, K. and Devetsikiotis, M. (2016) Blockchains and smart contracts for the internet of things. IEEE Access, 4, 2292–2303.
   Google Scholar
• Clauset, A., Shalizi, C. and Newman, M. (2009) Power-law distributions in empirical data. SIAM Review, 51(4), 661–703.
   Web of Science ®Google Scholar
• Cui, L., Kumara, S. and Albert, R.N. (2010) Complex networks: An engineering view. IEEE Circuits and Systems Magazine, 10(3), 10–25.
   Web of Science ®Google Scholar
• DeSmit, Z., Elhabashy, A.E., Wells, L.J. and Camelio, J.A. (2017) An approach to cyber-physical vulnerability assessment for intelligent manufacturing systems. Journal of Manufacturing Systems, 43, 339–351.
   Web of Science ®Google Scholar
• Ding, Y., Elsayed, E.A., Kumara, S., Lu, J.C., Niu, F. and Shi, J. (2006) distributed sensing for quality and productivity improvements. IEEE Transactions on Automation Science and Engineering, 3(4), 344–359.
   Web of Science ®Google Scholar
• Ding, Y., Kim, P., Ceglarek, D. and Jin, J. (2003) Optimal sensor distribution for variation diagnosis in multistation assembly processes. IEEE Transactions on Robotics and Automation, 19(4), 543–556.
   Google Scholar
• Ding, Y., Zeng, L. and Zhou, S. (2006) Phase I analysis for monitoring nonlinear profiles in manufacturing processes. Journal of Quality Technology, 38(3), 199–216.
   Web of Science ®Google Scholar
• Dower, G.E. and Machado, H.B. (1979) XYZ data interpreted by a 12-lead computer program using the derived electrocardiogram. Journal of Electrocardiology, 12(3), 249–261.
   Web of Science ®Google Scholar
• Duan, L. Liu, D., Zhang, Y., Chen, S., Liu, R.P., Cheng, B. and Chen, J. (2016) secure data-centric access control for smart grid services based on publish/subscribe systems. ACM Transactions on Internet Technology, 16(4), 23:1–23:17.
   Web of Science ®Google Scholar
• Edrington, B., Zhao, B., Hansel, A., Mori, M. and Fujishima, M. (2014) Machine monitoring system based on MTConnect technology. Procedia CIRP, 22, 92–97.
   Google Scholar
• Fan, T., Tao, F., Deng, S., and Li, S. (2015) Impact of RFID technology on supply chain decisions with inventory inaccuracies. International Journal of Production Economics, 159, 117–125.
   Web of Science ®Google Scholar
• Ferrer, A.J., Pérez, D.G. and González, R.S. (2016) Multi-cloud platform-as-a-service model, functionalities and approaches. Procedia Computer Science, 97, 63–72.
   Google Scholar
• Fu, M.C. (1994) Optimization via simulation: A review. Annals of Operations Research, 53(1), 199–247.
   Google Scholar
• Gebraeel, N. (2006) Sensory-updated residual life distributions for components with exponential degradation patterns. IEEE Transactions on Automation Science and Engineering, 3(4), 382–393.
   Web of Science ®Google Scholar
• Georgakopoulos, D., Jayaraman, P.P., Fazia, M., Villari, M. and Ranjan, R. (2016) Internet of things and edge cloud computing roadmap for manufacturing. IEEE Cloud Computing, 3(4), 66–73.
   Web of Science ®Google Scholar
• Ghuli, P., Kumar, U.P. and Shettar, R. (2017) A review on blockchain application for decentralized decision of ownership of IoT devices. Advances in Computational Sciences and Technology, 10(8), 2449–2456.
   Google Scholar
• Gomez, C. and Paradells, J. (2010) Wireless home automation networks: A survey of architectures and technologies. IEEE Communications Magazine, 48(6), 92–101.
   Web of Science ®Google Scholar
• Govardhan, J.M., Bukkapatnam, S.T.S., Bhamare, Y., Rao, P.K. and Rajamani, V. (2007) Statistical analysis and design of RFID systems for monitoring vehicle ingress/egress in warehouse environments. International Journal of Radio Frequency Identification Technology and Applications, 1(2), 123–146.
   Google Scholar
• Groenen, P. and van de Velden, M. (2016) Multidimensional scaling by majorization: A review. Journal of Statistical Software, 73(8), 1–26.
   Web of Science ®Google Scholar
• Guo, B., Zhang, D., Wang, Z., Yu, Z. and Zhou, X. (2013) Opportunistic IoT: Exploring the harmonious interaction between human and the internet of things. Journal of Network and Computer Applications, 36(6), 1531–1539.
   Web of Science ®Google Scholar
• Hutchins, M.J., Bhinge, R., Micali, M.K., Robinson, S.L., Sutherland, J.W. and Dornfeld, D. (2015) Framework for identifying cybersecurity risks in manufacturing. Procedia Manufacturing, 1, 47–63.
   Google Scholar
• Hwang, G., Lee, J., Park, J. and Chang, T. (2017) Developing performance measurement system for internet of things and smart factory environment. International Journal of Production Research, 55(9), 2590–2602.
   Web of Science ®Google Scholar
• International Data Corporation (2018) http://www.idc.com/.
   Google Scholar
• Jayaram, S., Connacher, H.I. and Lyons, K.W. (1997) Virtual assembly using virtual reality techniques. Computer-Aided Design, 29(8), 575–584.
   Web of Science ®Google Scholar
• Jin, J. and Shi, J. (1999) Feature-preserving data compression of stamping tonnage information using wavelets. Technometrics, 41(4), 327–339.
   Web of Science ®Google Scholar
• Jin, J. and Shi, J. (2000) Diagnostic feature extraction from stamping tonnage signals based on design of experiment. ASME Transactions, Journal of Manufacturing Science and Engineering, 122(2), 360–369.
   Web of Science ®Google Scholar
• Kamilaris, A. and Pitsillides, A. (2016) Mobile phone computing and the internet of things: A survey. IEEE Internet of Things Journal, 3(6), 885–898.
   Web of Science ®Google Scholar
• Kan, C., Cheng, C. and Yang, H. (2016) Heterogeneous recurrence monitoring of dynamic transients in ultraprecision machining processes. Journal of Manufacturing Systems, 41, 178–187.
   Web of Science ®Google Scholar
• Kan, C., Yang, H. and Kumara, S. (2018) Parallel computing and network analytics for fast internet-of-things (IOT) machine information processing and condition monitoring. Journal of Manufacturing Systems, 46, 282–293.
   Web of Science ®Google Scholar
• Koh, C., Shi, J. and Williams, W. (1995)Tonnage signature analysis using the orthogonal (HAAR) transforms. Transactions of NAMRI/SME, 23(1), 229–234.
   Google Scholar
• Kumar, A., Shankar, R., Choudhary, A. and Thakur, L.S. (2016) A big data MapReduce framework for fault diagnosis in cloud-based manufacturing. International Journal of Production Research, 54(23), 7060–7073.
   Web of Science ®Google Scholar
• Kumara S.R.T. and Bukkapatnam, S.T.S. (2007) Characterization and monitoring of nonlinear dynamics and chaos in manufacturing enterprise systems, in Network Science, Nonlinear Science and Infrastructure Systems, pp. 99–122, Springer, New York, NY.
   Google Scholar
• Kusiak, A. (2017a) Smart manufacturing. International Journal of Production Research, 56(1–2), 508–517.
   Web of Science ®Google Scholar
• Kusiak, A. (2017b) Smart manufacturing must embrace big data. Nature, 544(7648), 23–25.
   PubMed Web of Science ®Google Scholar
• Lee, J., Kao, H. and Yang, S. (2014) Service innovation and smart analytics for Industry 4.0 and big data environment. Procedia CIRP, 16, 3–8.
   Google Scholar
• Lei, P., Zheng, L., Li, C. and Li, X. (2016) MTConnect enabled interoperable monitoring system for finish machining assembly interfaces of large-scale components. Procedia CIRP, 56, 378–383.
   Google Scholar
• Levin, S.L. and Schmidt, S. (2014) IPv4 to IPv6: Challenges, solutions, and lessons. Telecommunications Policy, 38(11), 1059–1068.
   Web of Science ®Google Scholar
• Li, D., Ren, M. and Meng, G. (2017) Application of internet of things technology on predictive maintenance system of coal equipment. Procedia Engineering, 174, 885–889.
   Google Scholar
• Li J. and Shi, J. (2007) Knowledge discovery from observational data for process control using causal Bayesian networks. IIE Transactions, 39(6), 681–690.
   Web of Science ®Google Scholar
• Lin, Y.C., Hung, M.H., Huang, H.C., Chen, C.C., Yang, H.C., Hsieh, Y.S. and Cheng, F.T. (2017) Development of advanced manufacturing cloud of things (AMCoT)—a smart manufacturing platform. IEEE Robotics and Automation Letters, 2(3), 1809–1816.
   Web of Science ®Google Scholar
• Liu, G. and Yang, H. (2018) Self-organizing network for group variable selection and predictive modeling. Annals of Operation Research, 263(1–22), 119–140.
   Google Scholar
• Liu, J., Shi, J. and Hu, S.J. (2009) Quality assured setup planning based on the stream of variation model for multi-stage machining processes. IIE Transactions, Quality and Reliability Engineering, 41, 323–334.
   Web of Science ®Google Scholar
• Manvi, S.S. and Krishna Shyam, G. (2014) Resource management for Infrastructure as a Service (IaaS) in cloud computing: A survey. Journal of Network and Computer Applications, 41, 424–440.
   Web of Science ®Google Scholar
• Meller, R.D., Montreuil, B., Thivierge, C., and Montreuil, Z. (2012) Functional design of physical internet facilities: A road-based transit center. 12th IMHRC Proceedings (Gardanne, France – 2016). 26. Available at https://digitalcommons.georgiasouthern.edu/pmhr_2012/26.
   Google Scholar
• Monostori, L., Kádár, B., Bauernhansl, T., Kondoh, S., Kumara, S., Reinhart, G., Sauer, O., Schuh, G., Sihn, W. and Ueda, K. (2016) Cyber-physical systems in manufacturing. CIRP Annals - Manufacturing Technology, 65(2), 621–641.
   Web of Science ®Google Scholar
• Nazari Shirehjini, A.A. and Semsar, A. (2017) Human interaction with IoT-based smart environments. Multimedia Tools and Applications, 76(11), 13343–13365.
   Web of Science ®Google Scholar
• Nee, A.Y.C., Ong, S.K., Chryssolouris, G. and Mourtzis, D. (2012) Augmented reality applications in design and manufacturing. CIRP Annals - Manufacturing Technology, 61(2), 657–679.
   Web of Science ®Google Scholar
• Neul (2018) http://www.neul.com/neul/.
   Google Scholar
• NIST Cybersecurity Framework (2018) https://www.nist.gov/cyberframework
   Google Scholar
• Ok, C., Lee, S., Mitra, P. and Kumara, S. (2009) Distributed energy balanced routing for wireless sensor networks. Computers & Industrial Engineering, 57(1), 125–135.
   Web of Science ®Google Scholar
• Oliveira-Esquerre, K.P., Seborg, D.E., Mori, M. and Bruns, R.E. (2004) Application of steady-state and dynamic modeling for the prediction of the BOD of an aerated lagoon at a pulp and paper mill: Part II. Nonlinear approaches. Chemical Engineering Journal, 105(1–2), 61–69.
   Web of Science ®Google Scholar
• Pantelopoulos, A. and Bourbakis, N.G. (2010) A survey on wearable sensor-based systems for health monitoring and prognosis. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 40(1). 1–12.
   Web of Science ®Google Scholar
• Podgórski, D., Majchrzycka, K., Dąbrowska, A., Gralewicz, G. and Okrasa, M. (2017) Towards a conceptual framework of OSH risk management in smart working environments based on smart PPE, ambient intelligence and the internet of things technologies. International Journal of Occupational Safety and Ergonomics, 23(1), 1–20.
   PubMed Web of Science ®Google Scholar
• President’s Council of Advisors on Science and Technology (2012) Report to the president on ensuring American leadership in advanced manufacturing. Available at https://www.manufacturing.gov/reports
   Google Scholar
• Qin, J., Liu, Y. and Grosvenor, R. (2017) a framework of energy consumption modelling for additive manufacturing using internet of things. Procedia CIRP, 63, 307–312.
   Google Scholar
• Qu, T., Thürer, M., Wang, J.,Wang, Z., Fu, H., Li, C. and Huang, G.Q. (2017) System dynamics analysis for an internet-of-things-enabled production logistics system. International Journal of Production Research, 55(9), 2622–2649.
   Web of Science ®Google Scholar
• Quiescenti, M., Bruccoleri, M., La Commare, U., Diega, N.L. and Perrone, G. (2006) Business process-oriented design of enterprise resource planning (ERP) systems for small and medium enterprises. International Journal of Production Research, 44(18–19), 3797–3811.
   Web of Science ®Google Scholar
• Raghavan, U.N., Albert, R. and Kumara, S. (2007) Near linear time algorithm to detect community structures in large-scale networks. Physical Review E, 76(3), 036106.
   Web of Science ®Google Scholar
• Rao, P., Bukkapatnam, S., Beyca, O., Kong, Z. and Komanduri, R. (2014) Real-time identification of incipient surface morphology variations in ultraprecision machining process. Journal of Manufacturing Science and Engineering, 136(2), 021008-021008–11.
   Web of Science ®Google Scholar
• Reaidy, P.J., Gunasekaran, A. and Spalanzani, A. (2015) Bottom-up approach based on internet of things for order fulfillment in a collaborative warehousing environment. International Journal of Production Economics, 159, 29–40.
   Web of Science ®Google Scholar
• Ren, H., Long, J., Gao, Z. and Orenstein, P. (2012) Passenger assignment model based on common route in congested transit networks. Journal of Transportation Engineering, 138(12), 1484–1494.
   Web of Science ®Google Scholar
• Rymaszewska, A., Helo, P. and Gunasekaran, A. (2017) IoT powered servitization of manufacturing – an exploratory case study. International Journal of Production Economics, in press.
   Web of Science ®Google Scholar
• Saeed, A., Ahmadinia, A., Javed, A. and Larijani, H. (2016) Random neural network based intelligent intrusion detection for wireless sensor networks. Procedia Computer Science, 80, 2372–2376.
   Google Scholar
• Saenz, D.U. Artiba, A. and Pellerin, R. (2009) Manufacturing execution system – a literature review. Production Planning & Control, 20(6), pp. 525–539.
   Web of Science ®Google Scholar
• Sa-ngasoongsong, A., Kunthong, J., Sarangan, V., Cai, X. and Bukkapatnam, S.T.S. (2012) A low-cost, portable, high-throughput wireless sensor system for phonocardiography applications. Sensors, 12(8), 10851–10870.
   Web of Science ®Google Scholar
• Sanchez-Iborra, R. and Cano,M. (2016) State of the art in LP-WAN solutions for industrial IoT services. Sensors, 16(5), 708–721.
   Web of Science ®Google Scholar
• Saxena, N., Grijalva, S. and Chaudhari, N.S. (2016) Authentication protocol for an IoT-enabled LTE network, ACM Transactions on Internet Technology, 16(4), 25:1–25:20.
   Web of Science ®Google Scholar
• Seo, S., Won, J. and Bertino, E. (2016) pCLSC-TKEM: A pairing-free certificateless signcryption-tag key encapsulation mechanism for a privacy-preserving IoT. Transactions on Data Privacy, 9(2), 101–130.
   Web of Science ®Google Scholar
• Shaikh, F.K., Zeadally, S. and Exposito, E. (2017) Enabling technologies for green internet of things. IEEE Systems Journal, 11(2), 983–994.
   Web of Science ®Google Scholar
• Shi, J. (2006) Stream of Variation Modeling and Analysis for Multistage Manufacturing Processes, CRC Press, Boca Raton, FL.
   Google Scholar
• Siboni, S., Shabtai, A., Tippenhauer, N.O., Lee, J. and Elovici, Y. (2016) advanced security testbed framework for wearable IoT devices. ACM Transactions on Internet Technology, 16(4), 26:1-26:25.
   Web of Science ®Google Scholar
• Sinha, R.S., Wei, Y. and Hwang, S. (2017) A survey on LPWA technology: LoRa and NB-IoT. ICT Express, 3(1), 14–21.
   Web of Science ®Google Scholar
• Sturm, L.D., Williams, C.B., Camelio, J.A., White, J. and Parker, R. (2017) Cyber-physical vulnerabilities in additive manufacturing systems: A case study attack on the .STL file with human subjects. Journal of Manufacturing Systems, 44, 154–164.
   Web of Science ®Google Scholar
• Smart Manufacturing Leadership Coalition (2018) https://smartmanufacturingcoalition.org/.
   Google Scholar
• Sun, E., Zhang, X. and Li, Z. (2012) The internet of things (IOT) and cloud computing (CC) based tailings dam monitoring and pre-alarm system in mines. Safety Science, 50(4), 811–815.
   Web of Science ®Google Scholar
• Tan, G.W., Ooi, K., Chong, S. and Hew, T. (2014) NFC mobile credit card: The next frontier of mobile payment? Telematics and Informatics, 31(2), 292–307.
   Web of Science ®Google Scholar
• Tan, Y.S., Ng, Y.T. and Low, J.S.C. (2017) Internet-of-things enabled real-time monitoring of energy efficiency on manufacturing shop floors. Procedia CIRP, 61, 376–381.
   Google Scholar
• Tao, F., Cheng, J. and Qi, Q. (2017) IIHub: An industrial internet-of-things hub towards smart manufacturing based on cyber-physical system. IEEE Transactions on Industrial Informatics, 99, 1–1.
   Google Scholar
• Tao, F., Cheng, Y., Xu, L.D., Zhang, L. and Li,B.H. (2014) CCIoT-CMfg: Cloud computing and internet of things-based cloud manufacturing service system. IEEE Transactions on Industrial Informatics, 10(2), 1435–1442.
   Web of Science ®Google Scholar
• Tao, F. and Qi, Q. (2017) New IT driven service-oriented smart manufacturing: Framework and characteristics. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 99, 1–11.
   Google Scholar
• Tao, F., Qi, Q., Liu, A. and Kusiak, A. (2018) Data-driven smart manufacturing. Journal of Manufacturing Systems, 48(Part C), 157–169.
   Web of Science ®Google Scholar
• Tao, F., Zhao, D., Hu Y. and Zhou, Z. (2008) Resource service composition and its optimal-selection based on particle swarm optimization in manufacturing grid system. IEEE Transactions on Industrial Informatics, 4(4), 315–327.
   Web of Science ®Google Scholar
• Tao, F., Zuo, Y., Xu, L.D., Lv, L. and Zhang, L. (2014) Internet of things and BOM-based life cycle assessment of energy-saving and emission-reduction of products. IEEE Transactions on Industrial Informatics, 10(2), 1252–1261.
   Web of Science ®Google Scholar
• Telecommunication Development Bureau, International Telecommunication Union (ITU) ICT Facts and Figures 2017. Available at http://www.itu.int/en/ITU-D/Statistics/Pages/facts/default.aspx
   Google Scholar
• Thames L. and Schaefer, D. (2017) Cybersecurity for industry 4.0 and advanced manufacturing environments with ensemble intelligence, in Cybersecurity for Industry 4.0: Analysis for Design and Manufacturing, Springer Cham, Switzerland, pp.243–265.
   Google Scholar
• Thramboulidis K. and Christoulakis, F. (2016) UML4IoT—A UML-based approach to exploit IoT in cyber-physical manufacturing systems. Computers in Industry, 82, 259–272.
   Web of Science ®Google Scholar
• Tokognon, C.A., Gao, B., Tian, G.Y. and Yan, Y. (2017) Structural health monitoring framework based on internet of things: A survey. IEEE Internet of Things Journal, 4(3), 619–635.
   Web of Science ®Google Scholar
• U.S. Department of Commerce Bureau of Economic Analysis. Available at http://www.bea.gov/industry/gdpbyind_data.htm
   Google Scholar
• Vincent, H., Wells, L., Tarazaga, P. and Camelio, J. (2015) Trojan detection and side-channel analyses for cyber-security in cyber-physical manufacturing systems. Procedia Manufacturing, 1, 77–85.
   Google Scholar
• Wang, X., Chen, H. and Le, D. (2016) A novel IPv6 address configuration for a 6LoWPAN-based WBAN. Journal of Network and Computer Applications, 61, 33–45.
   Web of Science ®Google Scholar
• Xu, L.D., He, W. and Li, S. (2014) Internet of things in industries: A survey. IEEE Transactions on Industrial Informatics, 10(4), 2233–2243.
   Web of Science ®Google Scholar
• Xu Y. and Chen, M. (2016) Improving just-in-time manufacturing operations by using internet of things based solutions. Procedia CIRP, 56, 326–331.
   Google Scholar
• Yang, H. (2011) Multiscale recurrence quantification analysis of spatial cardiac vectorcardiogram (VCG) signals. IEEE Transactions on Biomedical Engineering, 58(2), 339–347.
   PubMed Web of Science ®Google Scholar
• Yang, H., Bukkapatnam, S.T.S. and Barajas, L.G. (2011) Local recurrence based performance prediction and prognostics in the nonlinear and nonstationary systems. Pattern Recognition, 44(8),1834–1840.
   Web of Science ®Google Scholar
• Yang, H., Bukkapatnam, S.T.S. and Barajas, L.G. (2013) Continuous flow modelling of multistage assembly line system dynamics. International Journal of Computer Integrated Manufacturing, 26(5), 401–411.
   Web of Science ®Google Scholar
• Yang, H., Bukkapatnam, S.T.S. and Komanduri, R. (2007) Nonlinear adaptive wavelet analysis of electrocardiogram signals. Physical Review E, 76(2), 026214.
   Web of Science ®Google Scholar
• Yang, H. and Chen, Y. (2014) Heterogeneous recurrence monitoring and control of nonlinear stochastic processes. Chaos, 24(1), 013138.
   Web of Science ®Google Scholar
• Yang, H., Kan, C., Chen, Y. and Liu, G. (2013) Spatiotemporal differentiation of myocardial infarctions. IEEE Transactions on Automation Science and Engineering, 10(4), 938–947.
   Web of Science ®Google Scholar
• Yang, H. and Leonelli, F. (2016) Self-organizing visualization and pattern matching of vectorcardiographic QRS waveforms. Computers in Biology and Medicine, 79, 1–9.
   Web of Science ®Google Scholar
• Yang, H. and Liu, G. (2013) Self-organized topology of recurrence-based complex networks. Chaos, 23(4), 043116.
   Web of Science ®Google Scholar
• Yang, X. and Chen, L. (2010) Using multi-temporal remote sensor imagery to detect earthquake-triggered landslides. International Journal of Applied Earth Observation and Geoinformation, 12(6), 487–495.
   Web of Science ®Google Scholar
• Zhang, X. and Huang, Q. (2010) Analysis of interaction structure among multiple functional process variables for process control in semiconductor manufacturing. IEEE Transactions on Semiconductor Manufacturing, 23(2), 263–272.
   Web of Science ®Google Scholar
• Zhang, Y., Xiang, Y. and Huang, X. (2016) Password-authenticated group key exchange: A cross-layer design. ACM Transactions on Internet Technology, 16(4), 24:1–24:20.
   Web of Science ®Google Scholar
• Zhang, Y., Zhang, G., Wang, J., Sun, S., Si, S., and Yang, T. (2015) Real-time information capturing and integration framework of the internet of manufacturing things. Int. International Journal of Computer integrated Manufacturing, 28(8), 811–822.
   Web of Science ®Google Scholar
• Zhong, R.Y., Wang, L. and Xu, X. (2017) An IoT-enabled real-time machine status monitoring approach for cloud manufacturing. Procedia CIRP, 63, 709–714.
   Google Scholar
• Zhong, R.Y., Xu, C., Chen, C. and Huang, G.Q. (2017) Big data analytics for physical internet-based intelligent manufacturing shop floors. International Journal of Production Research, 55(9),2610–2621.
   Web of Science ®Google Scholar
• Zhou, J. and Shi, J. (2008) RFID localization algorithms and applications-a review. Journal of Intelligent Manufacturing, 20(6), 695.
   Web of Science ®Google Scholar
• Zhou, L., Chong, A.Y.L. and. Ngai, E.W.T. (2015) Supply chain management in the era of the internet of things. International Journal of Production Economics, 159, 1–3.
   Web of Science ®Google Scholar
• Zhou, S., Sun, B. and Shi, J. (2006) An SPC monitoring system for cycle-based waveform signals using haar transform. IEEE Transactions on Automation Science and Engineering, 3(1), 60–72.
   Web of Science ®Google Scholar
• Zimmermann, H. (1980) OSI reference model-The ISO model of architecture for open systems interconnection., IEEE Transactions on Communications, 28(4), 425–432.
   Web of Science ®Google Scholar