Smart maintenance and inspection of linear assets: An Industry 4.0 approach

Authors

  • Dammika Seneviratne Tecnalia Research and Innovation
  • Lorenzo Ciani Department of Information Engineering, University of Florence
  • Marcantonio Catelani Department of Information Engineering, University of Florence
  • Diego Galar Luleå University of Technology

DOI:

https://doi.org/10.21014/acta_imeko.v7i1.519

Abstract

Linear assets have linear properties, for instance, similar underlying geometry and characteristics, over a distance. They show specific patterns of continuous inherent deteriorations and failures. Therefore, remedial inspection and maintenance actions will be similar along the length of a linear asset, but because as the asset is distributed over a large area, the execution costs are greater.

Autonomous robots, for instance, unmanned aerial vehicles, pipe inspection gauges, and remotely operated vehicles, are used in different industrial settings in an ad-hoc manner for inspection and maintenance. Autonomous robots can be programmed for repetitive and specific tasks; this is useful for the inspection and maintenance of linear assets.

This paper reviews the challenges of maintaining the linear assets, focusing on inspections. It also provides a conceptual framework for the use of autonomous inspection and maintenance practices for linear assets to reduce maintenance costs, human involvement, etc., whilst improving the availability of linear assets by effective use of autonomous robots and data from different sources.

Author Biographies

Dammika Seneviratne, Tecnalia Research and Innovation

Dammika Seneviratne currently works as a Senior Researcher, Tecnalia Research and Innovation, Industry and Transport Division, Miñano (Araba) 01510, Spain. He holds a B.Sc. degree in Mechanical Engineering from University of Peradeniya, Srilanka. He received his M.Sc. degree in Mechatronics Engineering from the Asian Institute of Technology, Thailand. After working as a maintenance engineer in various organizations, he attained a PhD degree in Offshore Technology from the University of Stavanger. His research interests include condition monitoring, operation and maintenance engineering in railway systems; risk based inspection planning in offshore oil and gas facilities; reliability and risk analysis and management, and risk based maintenance.

Lorenzo Ciani, Department of Information Engineering, University of Florence

Lorenzo Ciani (S’08–M’10-SM'16) received the M.S. degree in electronic engineering and the Ph.D. degree in Industrial and Reliability Engineering from the University of Florence, Italy, in 2005 and 2009, respectively. He is currently a Post-Doctoral Research Fellow with the Department of Information Engineering, University of Florence. From June, 2012 he is a TÜV Rheinland Industrie Service GmbH – Functional Safety Engineer – ID 5062/12. He is a Teaching assistant for “Reliability and Quality control” and “Diagnostic and systems’ safety” courses.

Diego Galar, Luleå University of Technology

Dr. Diego Galar is Professor of Condition Monitoring in the Division of Operation and Maintenance Engineering at LTU, Luleå University of Technology where he is coordinating several H2020 projects related to different aspects of cyber physical systems, Industry 4.0, IoT or industrial Big Data. He was also involved in the SKF UTC centre located in Lulea focused on SMART bearings. He is also actively involved in national projects with the Swedish industry and also funded by Swedish national agencies like Vinnova.

He is also principal researcher in Tecnalia (Spain), heading the Maintenance and Reliability research group.

He has authored more than three hundred journal and conference papers, books and technical reports in the field of maintenance, working also as member of editorial boards, scientific committees and chairing international journals and conferences.

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Published

2018-04-01

Issue

Vol. 7 No. 1 (2018)

Section

Research Papers

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