Abstract
We consider necessary to discuss on a scientific article about the diagnosis of Internet of Things (IoT) for industry applications, e.g. controlled flexible manufacturing systems (FMS). In order to analyse and diagnose the main characteristics of these systems we focus on models realized with Markov chains of FMS with stochastic and not equal throughput rates. Discrete-event models assume that FMS is decomposed, and we study the following events: an Internet server fails, an Internet server is repaired, an Internet server memory buffer fills up, an Internet server memory buffer empties. The IoT diagnosis is performed with by calculating the time to absorption in Markov model of the IoT controlled FMS. Future developments of IoT diagnosis of FMS are also discussed in this work.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Viswandham, N., Narahari, J.: Performance Modeling of Automated Manufacturing System. Prentice Hall, Englewood Cliffs, NJ (1992)
Kemeny, J., Snell, W.: Finite Markov Chains. Van Nostrand, NJ (1960)
Buzacott, J.A., Shantikumar, J.G.: Stochastic Models of Manufacturing System. Prentice Hall, Englewood Cliffs, NJ (1993)
Narahari, J., Viswandham, N.: Transient analysis of manufacturing system performance. IEEE Trans. Rob. Autom. 10(2), 230–234 (1994)
Ciufudean, C., Satco, B.: Algebraic formalism for modelling the deadlock in flexible manufacturing systems. J. Appl. Math. 1(3), 157–165 (2008)
Viswandham, N., Ram, R.: Composite performance-dependability analysis of cellular manufacturing systems. IEEE. Rob. Autom. 10(2), 245–258 (1994)
Dallery, J., Gershwin, S.B.: Manufacturing flow line systems: A review of models and analytical results, Technical report 91−002. Laboratory for Manufacturing and Productivity, MIT (1992)
Martinelli, F., Shu, C., Perkins, J.R.: On the optimality of Myopic productions controls for single-server continuous-flow manufacturing systems. IEEE Trans. Autom. Contr. 46(8), 1269–1273 (2001)
di Benedetto, M.D., Vintecentelli, A.S., Villa, T.: Model matching for finite state machines. IEEE Trans. Autom. Contr. 46(11), 1726–1743 (2001)
Harrell, C.: The Internet of Things and control system architecture (2014). http://blog.aac.advantech.com/the-internet-of-things-and-control-system-architecture
Dolin, R.: Building an IoT for industrial control: Part 1 – What is Industrial IoT? (2015). http://www.embedded.com/design/real-world-applications/4426952/Building
Storey, H., Bullotta, R., Drolet, D.: The industrial internet of things (2014). http://www.controleng.com/industry-news/single-article/the-industrial-internet-of-things/c98837a0efec387df9fc14c2de0a3b2f.ht
Vermesan, O., Friess, P. (eds.): Internet of Things – From Research and Innovation to Market Deployment. River Publishers, Aalborg, Denmark (2014)
Ciufudean, C., Filote, C.: Safety discrete event models for holonic cyclic manufacturing systems. In: MaÅ™Ãk, V., Strasser, T., Zoitl, A. (eds.) HoloMAS 2009. LNCS, vol. 5696, pp. 225–233. Springer, Heidelberg (2009). doi:10.1007/978-3-642-03668-2_22
Ciufudean, C., Filote, C., Amarandei, D.: Measuring the performance of distributed systems with discrete event formalisms. In: Proceeding of the 2nd Seminar for Advanced Industrial Control Applications (SAICA), Madrid, Spain (2007)
Ciufudean, C., Graur, A., Filote, C., Turcu, C., Popa, V.: Diagnosis of complex systems using ant colony decision petri nets. In: The First International Conference on Availability, Reliability and Security (ARES 2006), Vienna, Austria (2006)
Ciufudean, C., Satco, B., Filote, C.: Reliability Markov chains for security data transmitter analysis. In: The Second International Conference on Availability, Reliability and Security (ARES 2007), pp. 886–894 (2007)
Taylor, G., McClean, S., Millard, P.: Continuous-time Markov models for Geriatric patient behavior. Appl. Stoch. Models Data Anal. 13, 315–323 (1998)
Kolmogorov, A.N.: Basic Concepts of Probability Theory. ONTI, Moscow (1936)
Kendall, D.G.: Some recent works and further problems in the theory of queue. Prob. Th. Appl. 9(1), 3–15 (1964)
Schrijner P.: Quasi-stationarity of discrete time markov chains, Thesis Universiteit Twente Enschede (1995). ISBN:90-9008502-5
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Ciufudean, C., Buzduga, C. (2017). Modelling the Diagnosis of Industry Internet of Things. In: Helfert, M., Klein, C., Donnellan, B., Gusikhin, O. (eds) Smart Cities, Green Technologies, and Intelligent Transport Systems. VEHITS SMARTGREENS 2016 2016. Communications in Computer and Information Science, vol 738. Springer, Cham. https://doi.org/10.1007/978-3-319-63712-9_7
Download citation
DOI: https://doi.org/10.1007/978-3-319-63712-9_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-63711-2
Online ISBN: 978-3-319-63712-9
eBook Packages: Computer ScienceComputer Science (R0)