Skip to main content
Top

2016 | OriginalPaper | Chapter

Maintenance 4.0 in Railway Transportation Industry

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Transportation systems are complex with respect to technology and operations with involvement in a wide range of human actors, organisations and technical solutions. For the operations and control of such complex environments, a viable solution is to apply intelligent computerised systems, such as computerised traffic control systems for coordinating airline transportation, or advanced monitoring and diagnostic systems in vehicles. Moreover, transportation assets cannot compromise the safety of the passengers by applying operation and maintenance activities. Indeed safety becomes a more difficult goal to achieve using traditional maintenance strategies and computerised solutions come into the picture as the only option to deal with complex systems interacting among them trying to balance the growth in technical complexity together with stable and acceptable dependability indexes. Industry 4.0 is a term that describes the fourth generation of industrial activity which is enabled by smart systems and Internet-based solutions. Two of the characteristic features of Industry 4.0 are computerization by utilising cyber-physical systems and intelligent factories that are based on the concept of “internet of things”. Maintenance is one of the application areas, referred to as maintenance 4.0, in form of self-learning and smart systems that predicts failure, makes diagnosis and triggers maintenance by making use of “internet of things”. This paper discusses the possibilities that lie within applying the maintenance 4.0 concept in the railway transportation industry and the positive effects on technology, organisation and operations from a systems perspective.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Literature
go back to reference Alm, H., Gärling, A., Bonnevier, S. S. & Danielsson, M. (2012). How to increase safety in complex systems—An ongoing project. Work 41, 3234–3237. Alm, H., Gärling, A., Bonnevier, S. S. & Danielsson, M. (2012). How to increase safety in complex systems—An ongoing project. Work 41, 3234–3237.
go back to reference Ashton, K. (2009). That ‘internet of things’ thing. RFiD Journal, 22(7), 97–114. Ashton, K. (2009). That ‘internet of things’ thing. RFiD Journal, 22(7), 97–114.
go back to reference Baglee, D., Marttonen, S., & Galar, D. (2015). The need for big data collection and analyses to support the development of an advanced maintenance strategy.DMIN'15, The 11th International Conference on Data Mining (27–30 Jul 2015). Las Vegas, Nevada, USA. Baglee, D., Marttonen, S., & Galar, D. (2015).  The need for big data collection and analyses to support the development of an advanced maintenance strategy.DMIN'15, The 11th International Conference on Data Mining (27–30 Jul 2015). Las Vegas, Nevada, USA.
go back to reference Benbelkacem, S., Zenati‐Henda, N., Belhocine, M., & Malek, S. (2009, March). Augmented reality system for E‐maintenance application. In Intelligent Systems And Automation: 2nd Mediterranean Conference on Intelligent Systems and Automation (CISA’09) (Vol. 1107, No. 1, pp. 185–189). AIP Publishing. Benbelkacem, S., Zenati‐Henda, N., Belhocine, M., & Malek, S. (2009, March). Augmented reality system for E‐maintenance application. In Intelligent Systems And Automation: 2nd Mediterranean Conference on Intelligent Systems and Automation (CISA’09) (Vol. 1107, No. 1, pp. 185–189). AIP Publishing.
go back to reference Bugarinovic, M., & Boskovic, B. (2015). A systems approach to access charges in unbundling railways. European Journal of Operational Research, 240, 848–860.CrossRef Bugarinovic, M., & Boskovic, B. (2015). A systems approach to access charges in unbundling railways. European Journal of Operational Research, 240, 848–860.CrossRef
go back to reference Busby, J. S. (2006). Failure to mobilize in reliability-seeking organizations: Two cases from the UK railway. Journal of Management Studies, 43(6), 1375–1393.CrossRef Busby, J. S. (2006). Failure to mobilize in reliability-seeking organizations: Two cases from the UK railway. Journal of Management Studies, 43(6), 1375–1393.CrossRef
go back to reference Candell, O., Karim, R., & Soderholm, P. (2009). eMaintenance—Information logistics for maintenance support. Robotics and Computer-Integrated Manufacturing, 25(6), 937–944.CrossRef Candell, O., Karim, R., & Soderholm, P. (2009). eMaintenance—Information logistics for maintenance support. Robotics and Computer-Integrated Manufacturing, 25(6), 937–944.CrossRef
go back to reference Checkland, P., & Poulter, J. (2006). Learning for action: A short definite account of soft systems methodology and its uses for practitioners, teachers and students. Chichester, UK: Wiley. Checkland, P., & Poulter, J. (2006). Learning for action: A short definite account of soft systems methodology and its uses for practitioners, teachers and students. Chichester, UK: Wiley.
go back to reference Conti, R., Galardi, E., Meli, E., Nocciolini, D., Pugi, L., & Rindi, A. (2015). Energy and wear optimisation of train longitudinal dynamics and of traction and braking systems. Vehicle System Dynamics, 53(5), 651–671.CrossRef Conti, R., Galardi, E., Meli, E., Nocciolini, D., Pugi, L., & Rindi, A. (2015). Energy and wear optimisation of train longitudinal dynamics and of traction and braking systems. Vehicle System Dynamics, 53(5), 651–671.CrossRef
go back to reference EC European Commission. (2011). WHITE PAPER roadmap to a single European transport area towards a competitive and resource efficient transport system. COM, 144. EC European Commission. (2011). WHITE PAPER roadmap to a single European transport area towards a competitive and resource efficient transport system. COM, 144.
go back to reference Galar, D., Kumar, U., Lee, J., & Zhao, W. (2012c, May). Remaining useful life estimation using time trajectory tracking and support vector machines. Journal of Physics: Conference Series, 364(1), 012063 (IOP Publishing). Galar, D., Kumar, U., Lee, J., & Zhao, W. (2012c, May). Remaining useful life estimation using time trajectory tracking and support vector machines. Journal of Physics: Conference Series, 364(1), 012063 (IOP Publishing).
go back to reference Galar, D., Palo, M., Van Horenbeek, A., & Pintelon, L. (2012a). Integration of disparate data sources to perform maintenance prognosis and optimal decision making. Insight-Non-Destructive Testing and Condition Monitoring, 54(8), 440–445.CrossRef Galar, D., Palo, M., Van Horenbeek, A., & Pintelon, L. (2012a). Integration of disparate data sources to perform maintenance prognosis and optimal decision making. Insight-Non-Destructive Testing and Condition Monitoring, 54(8), 440–445.CrossRef
go back to reference Galar, D., Wandt, K., Karim, R., & Berges, L. (2012b). The evolution from e (lectronic) Maintenance to i (ntelligent) Maintenance. Insight-Non-Destructive Testing and Condition Monitoring, 54(8), 446–455.CrossRef Galar, D., Wandt, K., Karim, R., & Berges, L. (2012b). The evolution from e (lectronic) Maintenance to i (ntelligent) Maintenance. Insight-Non-Destructive Testing and Condition Monitoring, 54(8), 446–455.CrossRef
go back to reference Granström, R. (2008). Management of condition information from railway punctuality perspectives (Ph.D. dissertation, Luleå University of Technology, 2008). Granström, R. (2008). Management of condition information from railway punctuality perspectives (Ph.D. dissertation, Luleå University of Technology, 2008).
go back to reference Gustafson, A., Schunnesson, H., Galar, D., & Kumar, U. (2013). Production and maintenance performance analysis: Manual versus semi-automatic LHDs. Journal of Quality in Maintenance Engineering, 19(1), 74–88.CrossRef Gustafson, A., Schunnesson, H., Galar, D., & Kumar, U. (2013). Production and maintenance performance analysis: Manual versus semi-automatic LHDs. Journal of Quality in Maintenance Engineering, 19(1), 74–88.CrossRef
go back to reference Ignesti, M., Malvezzi, M., Marini, L., Meli, E., & Rindi, A. (2012). Development of a wear model for the prediction of wheel and rail profile evolution in railway systems. Wear, 284–285, 1–17.CrossRef Ignesti, M., Malvezzi, M., Marini, L., Meli, E., & Rindi, A. (2012). Development of a wear model for the prediction of wheel and rail profile evolution in railway systems. Wear, 284–285, 1–17.CrossRef
go back to reference Johansson, J., & Hassel, H. (2010). An approach for modelling interdependent infrastructures in the context of vulnerability analysis. Reliability Engineering and System Safety, 95, 1335–1344.CrossRef Johansson, J., & Hassel, H. (2010). An approach for modelling interdependent infrastructures in the context of vulnerability analysis. Reliability Engineering and System Safety, 95, 1335–1344.CrossRef
go back to reference Kans, M. (2013). Knowledge asset management in the maintenance context. In International Congress of Condition Monitoring and Diagnostics Engineering Management (COMADEM 2013) (pp. 9–16). Kans, M. (2013). Knowledge asset management in the maintenance context. In International Congress of Condition Monitoring and Diagnostics Engineering Management (COMADEM 2013) (pp. 9–16).
go back to reference Ke, B. R., Lin, C. L., Chien, H. H., Chiu, H. W., & Chen, N. (2015). A new approach for improving the performance of freight train timetabling of a single-track railway system. Transportation Planning and Technology, 38(2), 238–264.CrossRef Ke, B. R., Lin, C. L., Chien, H. H., Chiu, H. W., & Chen, N. (2015). A new approach for improving the performance of freight train timetabling of a single-track railway system. Transportation Planning and Technology, 38(2), 238–264.CrossRef
go back to reference Khosrowshahi, F., Ghodous, P., & Sarshar, M. (2014). Visualization of the modeled degradation of building flooring systems in building maintenance. Computer-Aided Civil & Infrastructure Engineering, 29(1), 18–30.CrossRef Khosrowshahi, F., Ghodous, P., & Sarshar, M. (2014). Visualization of the modeled degradation of building flooring systems in building maintenance. Computer-Aided Civil & Infrastructure Engineering, 29(1), 18–30.CrossRef
go back to reference Kour, R., Karim, R., Parida, A., & Kumar, U. (2014a). Applications of radio frequency identification (RFID) technology with eMaintenance cloud for railway system. International Journal of System Assurance Engineering Management, 5(1), 99–106.CrossRef Kour, R., Karim, R., Parida, A., & Kumar, U. (2014a). Applications of radio frequency identification (RFID) technology with eMaintenance cloud for railway system. International Journal of System Assurance Engineering Management, 5(1), 99–106.CrossRef
go back to reference Kour, R., Karim, R., & Tretten, P. (2014b). eMaintenance solutions for railway maintenance decisions. In Proceedings of the World Congress on Engineering (Vol. 1). Kour, R., Karim, R., & Tretten, P. (2014b). eMaintenance solutions for railway maintenance decisions. In Proceedings of the World Congress on Engineering (Vol. 1).
go back to reference Kroll, B., Schaffranek, D., Schriegel, S., & Niggemann, O. (2014). System modeling based on machine learning for anomaly detection and predictive maintenance in industrial plants. IEEE Emerging Technology and Factory Automation (ETFA), 1–7 Kroll, B., Schaffranek, D., Schriegel, S., & Niggemann, O. (2014). System modeling based on machine learning for anomaly detection and predictive maintenance in industrial plants. IEEE Emerging Technology and Factory Automation (ETFA), 1–7
go back to reference Kyriakidis, M., Majumdar, A., & Ochieng, W. Y. (2015). Data based framework to identify the most significant performance shaping factors in railway operations. Safety Science, 78, 60–76.CrossRef Kyriakidis, M., Majumdar, A., & Ochieng, W. Y. (2015). Data based framework to identify the most significant performance shaping factors in railway operations. Safety Science, 78, 60–76.CrossRef
go back to reference Lasi, H., Fettke, P., Kemper, H.-G., Feld, T., & Hoffmann, M. (2014). Industry 4.0. Business & Information Systems Engineering, 6(4), 239–242. Lasi, H., Fettke, P., Kemper, H.-G., Feld, T., & Hoffmann, M. (2014). Industry 4.0. Business & Information Systems Engineering, 6(4), 239–242.
go back to reference Lee, E. (2008, May). Cyber physical systems: Design challenges. In 2008 11th IEEE International Symposium on Object Oriented Real-Time Distributed Computing (ISORC) (pp. 363–369). IEEE. Lee, E. (2008, May). Cyber physical systems: Design challenges. In 2008 11th IEEE International Symposium on Object Oriented Real-Time Distributed Computing (ISORC) (pp. 363–369). IEEE.
go back to reference Lee, J., Kao, H.-A., & Yang, S. (2014). Service innovation and smart analytics for Industry 4.0 and big data environment. Procedia CIRP, 16, 3–8. Lee, J., Kao, H.-A., & Yang, S. (2014). Service innovation and smart analytics for Industry 4.0 and big data environment. Procedia CIRP, 16, 3–8.
go back to reference Manca, D., Brambilla, S., & Colombo, S. (2013). Bridging between virtual reality and accident simulation for training of process-industry operators. Advances in Engineering Software, 55, 1–9.CrossRef Manca, D., Brambilla, S., & Colombo, S. (2013). Bridging between virtual reality and accident simulation for training of process-industry operators. Advances in Engineering Software, 55, 1–9.CrossRef
go back to reference Muller, A., Marquez, A. C., & Iung, B. (2008). On the concept of e-maintenance: Review and current research. Reliability Engineering & System Safety, 93(8), 1165–1187. Muller, A., Marquez, A. C., & Iung, B. (2008). On the concept of e-maintenance: Review and current research. Reliability Engineering & System Safety, 93(8), 1165–1187.
go back to reference Mussone, L., & Calvo, R. W. (2013). An analytical approach to calculate the capacity of a railway system. European Journal of Operational Research, 228, 11–23. Mussone, L., & Calvo, R. W. (2013). An analytical approach to calculate the capacity of a railway system. European Journal of Operational Research, 228, 11–23.
go back to reference Nishikawa, K. (2014). Who leads change processes? From the case study of Japan railways Kyusyu. South Asian Journal of Business and Management Cases, 3(1), 53–64.CrossRef Nishikawa, K. (2014). Who leads change processes? From the case study of Japan railways Kyusyu. South Asian Journal of Business and Management Cases, 3(1), 53–64.CrossRef
go back to reference Parida, A., Galar, D., & Berges, L. (2011, June). Decision support systems in maintenance: Fusion of business data and physical data. In The 8th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, Cardiff, England (pp. 20–22). Parida, A., Galar, D., & Berges, L. (2011, June). Decision support systems in maintenance: Fusion of business data and physical data. In The 8th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, Cardiff, England (pp. 20–22).
go back to reference Penna, R., Amaral, M., Espíndola, D., Botelho, S., Duarte, N., Pereira, C. E. et al. (2014). Visualization tool for cyber-physical maintenance systems. In 2014 12th IEEE International Conference on Industrial Informatics (INDIN) (pp. 566–571). Penna, R., Amaral, M., Espíndola, D., Botelho, S., Duarte, N., Pereira, C. E. et al. (2014). Visualization tool for cyber-physical maintenance systems. In 2014 12th IEEE International Conference on Industrial Informatics (INDIN) (pp. 566–571).
go back to reference Riksrevisionen. (2010). Underhåll av järnväg, Riksrevisionen RiR 2010:16, Stockholm. Riksrevisionen. (2010). Underhåll av järnväg, Riksrevisionen RiR 2010:16, Stockholm.
go back to reference Sankavaram, C., Kodali, A., & Pattipati, K. (2013). An integrated health management process for automotive cyber-physical systems. In 2013 International Conference on Computing, Networking and Communications, Workshops Cyber Physical System (pp. 82–86). Sankavaram, C., Kodali, A., & Pattipati, K. (2013). An integrated health management process for automotive cyber-physical systems. In 2013 International Conference on Computing, Networking and Communications, Workshops Cyber Physical System (pp. 82–86).
go back to reference Skyttner, L. (2001). General systems theory—Ideas and applications. Singapore: World Scientific Publishing.CrossRefMATH Skyttner, L. (2001). General systems theory—Ideas and applications. Singapore: World Scientific Publishing.CrossRefMATH
go back to reference SOU. (2010). Förbättrad vinterberedskap inom järnvägen - Betänkande av Utredningen om störningar i järnvägstrafiken vintern 2009/2010. Statens offentliga utredningar SOU 2010:69, Stockholm. SOU. (2010). Förbättrad vinterberedskap inom järnvägen - Betänkande av Utredningen om störningar i järnvägstrafiken vintern 2009/2010. Statens offentliga utredningar SOU 2010:69, Stockholm.
go back to reference SOU. (2013). En enkel till framtiden? - Delbetänkande av Utredningen om järnvägens organisation. Statens offentliga utredningar SOU 2013:83, Stockholm. SOU. (2013). En enkel till framtiden? - Delbetänkande av Utredningen om järnvägens organisation. Statens offentliga utredningar SOU 2013:83, Stockholm.
go back to reference Syed, B., Pal, A., Srinivasarengan, K., & Balamuralidhar, P. (2012). A smart transport application of cyber-physical systems: Road surface monitoring with mobile devices. In 2012 Sixth International Conference on Sensing Technology (pp. 8–12). Syed, B., Pal, A., Srinivasarengan, K., & Balamuralidhar, P. (2012). A smart transport application of cyber-physical systems: Road surface monitoring with mobile devices. In 2012 Sixth International Conference on Sensing Technology (pp. 8–12).
go back to reference Thaduri, A., Kumar, U., & Verma, A. K. (2014). Computational intelligence framework for context-aware decision making. International Journal of System Assurance Engineering and Management, 1–12. Thaduri, A., Kumar, U., & Verma, A. K. (2014). Computational intelligence framework for context-aware decision making. International Journal of System Assurance Engineering and Management, 1–12.
go back to reference Trafikanalys. (2014). Rail traffic 2013 Statistik 2014:15, Stockholm. Trafikanalys. (2014). Rail traffic 2013 Statistik 2014:15, Stockholm.
go back to reference Trafikverket. (2014a). Att skapa tidtabeller för tåg – nu och i framtiden Från dialog och ansökan till samordnad tågplan, Borlänge. Trafikverket. (2014a). Att skapa tidtabeller för tåg – nu och i framtiden Från dialog och ansökan till samordnad tågplan, Borlänge.
go back to reference Trafikverket. (2014b). The Swedish Transport Administration Annual Report 2013, Borlänge. Trafikverket. (2014b). The Swedish Transport Administration Annual Report 2013, Borlänge.
Metadata
Title
Maintenance 4.0 in Railway Transportation Industry
Authors
Mirka Kans
Diego Galar
Adithya Thaduri
Copyright Year
2016
DOI
https://doi.org/10.1007/978-3-319-27064-7_30