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THE UNIVERSITY OF CAMBRIDGE is a collegiate research university based in Cambridge, UK. The Asset Management Group based at the Institute for Manufacturing within the Department of Engineering of the university, studies innovative ways in which industrial assets and systems should be maintained and managed in order to deliver maximum performance while minimising costs and risks over their whole life. The group is led by Dr Ajith Kumar Parlikad and consists of two post-doctoral researchers and five PhD students. The Asset Management Group has received research funding from the Engineering and Physical Sciences Research Council, EU H2020, and a number of commercial organisations. The group has an industrial partner base spanning manufacturing, transportation, utilities and communications sectors. The Asset Management Group is part of a larger research centre – the Distributed Information and Automation Lab (DIAL) which consists of 22 academics, post-doctoral researchers and PhD students.

The Asset Management Group has expertise in reliability engineering, condition-based maintenance of complex engineering systems, criticality analysis, asset information management, and performance measurement.  In particular, the group has developed several models for optimal scheduling of inspection and maintenance plans based on the value and criticality of equipment in terms of system performance, cost and risk. Working with companies in the infrastructure sector, the group has developed expertise in developing opportunistic maintenance schedules for asset portfolios considering dependencies between assets. In addition, the group has also worked with companies in the infrastructure and manufacturing sectors on intelligent fault diagnosis and management of lifecycle information. The group’s recent research on value-based asset management has led to the development of a process and tool to optimise and prioritise maintenance activities based on its value to stakeholders and this has been successfully implemented in a number of organisations in the UK. The expertise of the group in working with a wide variety of industry sectors, understanding and distilling those industrial requirements and delivering solutions that are practically applied as well as generalizable is of particular relevance to this project. Furthermore, DIAL has proven expertise in Industrial information systems, Cyber-Physical systems, data analytics and optimisation.


Dr Ajith Kumar Parlikad (Male) is Senior Lecturer in Industrial ​Systems at Cambridge University Engineering Department (CUED) and a Co-Investigator of the Centre for Smart Infrastructure and Construction. He is based at the Institute for Manufacturing, where he is the head of the Asset Management Group and he will be the Principal Investigator at UCAM for the SAFEWAY project.  His research focuses on examining how asset information can effectively managed and used to improve asset investment and maintenance decision-making. He sits on the steering committee of the IFAC Working Group on Advanced Maintenance Engineering, Services and Technology. In addition, he has built a strong industry network for collaborative research in the manufacturing, petrochemicals, aerospace and infrastructure sectors. Over the last few years, he has developed a number of novel reliability and maintenance optimisation models for complex systems that specifically considers the impact of interaction between the system elements. Working with Hitachi Rail, he developed a fault-diagnosis system that exploited data analytics and neural network models to improve maintenance processes. His recent research on value-based asset management has led to the development of a process and tool to optimise and prioritise maintenance activities based on its value to stakeholders. The models, methodologies and tools produced through his research have been successfully deployed in several large manufacturing and infrastructure companies in the UK and Europe.

Dr Zhenglin Liang (Male) is a Post-Doctoral Research Associate at Cambridge University Engineering Department and is a member of the Asset Management Group. Dr Liang has expertise in reliability modelling of complex engineering systems, diagnosis and prognosis, and optimising condition-based maintenance. He has worked on condition-based maintenance of utilities (power transformers) and infrastructure assets (bridges). He is currently working on a research project that deals with developing fault diagnosis and maintenance scheduling algorithms for fleets of gas turbines.​

Dr Rengarajan Srinivasan (Male) a Post-Doctoral Research Associate at Cambridge University Engineering Department and is a member of the Asset Management Group. His expertise is on maintenance scheduling, agent-based manufacturing systems, and cyber-physical systems. He has worked on projects involving companies in the infrastructure, aerospace and manufacturing sectors.


Dr. Belén Riveiro
University of Vigo
School of Industrial Engineering, Universidade de Vigo
CP36310, Vigo, Spain
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This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement
No 769255. This website reflects only the views of the author(s). Neither the Innovation and Networks Executive Agency (INEA) nor the
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