John Andrews: is Professor of Infrastructure Asset Management in the Faculty of Engineering at the University of Nottingham and a member of the Resilience Engineering Research Group. Prior to this he worked for 20 years at Loughborough University where his final post was Professor of Systems Risk and Reliability
The prime focus of his research has been on methods for predicting system availability and reliability. Much of his early work was concentrated on the Fault Tree analysis technique and the use of Binary Decision Diagrams (BDDs) as an efficient and accurate solution method. Recently attention has turned more to degradation modelling and the effects of maintenance, inspection and renewal on asset performance.
John received an Honorary Doctorate in Engineering from Örebro University, Sweden in February 2018 and was recently appointed as a Resilience Engineering Ambassador for the 4TU.RE Centre (Resilience Engineering Centre for the Technical Universities of Delft, Eindhoven, Twente and Wageningen, the Netherlands). Prior to these in Spring 2013 he was the Mack Blackwell Lecturer at the University of Arkansas, USA.
In 2005, John founded the Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability (JRR) of which he was the Editor-in-chief for 10 years. He remains on the Editorial Board of JRR and is also a member of the Editorial Boards for: Reliability Engineering and System Safety, Quality and Reliability Engineering International and the Proceedings of the Institution of Mechanical Engineers Part F: Rail and Rapid Transit. He is a joint author, along with the late Bob Moss, of the text 'Reliability and Risk Assessment', the second edition of which was published in 2002 by Professional Engineering Publications Limited (IMechE). More recently he, along with Christophe Berenguer and Lisa Jackson, were Editors of 'Maintenance Modelling and Applications', published by ESReDA (European Safety Reliability and Data Association).
In 1999 John was the recipient of theMoss Prize from the Institution of Mechanical Engineers for "Optimal Safety System Design Using Fault Tree Analysis" published in the Proceedings, Vol. 208, No E2. In 2004 he, with Lisa Bartlett, was awarded the Ludwig Mond Prize again by the Institution of Mechanical Engineers for "Using Statistically Designed Experiments for Safety System Optimization", published in the Proceedings, Vol 218, pp53-63. At the 26th International System Safety Conference in Vancouver 2008 he and Rasa Remenyte-Prescott received the Best paper award for "Reliability Analysis in Responsive Mission Planning for Autonomous Vehicles". In 2009 these same authors received the Donald Julius Groen Prize for the ''Analysis of Non-coherent Fault Trees Using Ternary Decision Diagrams'', In the same year "Multiplatform Phased Mission Reliability Modelling for Mission Planning" authored with Darren Prescott was given the PE Publishers Award.
Other awards received include: the 2012 Alan O. Plait Tutorial Excellence Award from the annual RAMS conference, USA, the IMechE's Charles Sharpe Beecher Prize 2013 (with Prof Chen and Dr Liu from Loughborough University), the John Jarrett Davis Prize 2014 and theDonald Julius Groen Prize 2017 (with Bryant le and Claudia Fecarotti) for the following papers:
- C Liu, W-H Chen and J. D. Andrews, (2012), Explicit Nonlinear Model Predictive Control for Autonomous Helicopters, Journal of Aerospace Engineering, Vol 226, No 9, pp1171-1182, 2012
- Andrews, J., (2013), A Modelling Approach to Railway Track Asset Management, Journal of Rail and Rapid Transit, Vol 227, pp56-73.
- Le, B., Andrews, J. and Fecarotti, C., (2017), Petri net Model for Railway Bridge Maintenance, Journal or Risk and Reliability, vol 231, No 3, pp306-323.
John has over 300 publications in the field of Risk, Reliability and Maintainability Engineering.
The prime focus of his research has been on developing models to evaluate system risk, resilience, unavailability and unreliability. Through the application of the models, the most effective ways to… read more