Professor John Quigley

Management Science

Personal statement

John is an Industrial Statistician with expertise in developing and applying statistical and stochastic methods to build decision support models. Much of his research has focused on working with engineers to inform design decisions.  Examples of the projects John has worked on include:   

NEXUS:  The Horizon 2020 funded project concerning vessel design to support offshore windfarm maintenance, where models were developed that link vessel design characteristics with windfarm productivity and so help identify optimal designs.  A collaborative project with academics from Management Science and Naval, Ocean and Marine Engineering as well as industrial partners Kongsberg, Gondan, Global Marine, DNV, Sintef and Arttic.

PCAD: The EPSRC funded project to create algorithms and identify statistical methods to enable a predictive Computer Aided Design (CAD) system which enhances the productivity of engineering designers.  A collaborative project with academics from Design, Manufacturing and Engineering Management.

Resilience and Robustness of Dynamic Manufacturing Supply Networks: The EPSRC funded project to develop methods for supplier risk analysis.  A collaborative project with academics from Management Science and the Universities of Bristol, Nottingham and Coventry as well as industrial partner Rolls Royce.  

REMM: The DTI/aerospace industry funded project, Reliability Enhancement Methodology and Modelling (REMM) which was concerned with developing models to anticipate in-service reliability during product development and as such inform decisions regarding reliability growth.  The model he developed as part of this project is included in the industry standard for reliability growth analysis methods, BS/IEC 61164 as well as contributing to the Strathclyde Business Schools impact cases for the Research Enhancement Framework.  This was a collaboration with a variety of partners.

Productivity and Sustainability Management in the Responsive Factory: The EPSRC funded project is concerned with the use of real time data during manufacturing to optimise operations, identify opportunities for improvements in efficiency, productivity and sustainability through the use of probabilistic networks.  This is a collaborative project with academics from the Universities of Edinburgh and Napier as well as the National Manufacturing Institure of Scotland.

John is committed to working with industry and has been involved in consultancy and applied research projects with a variety of organisations for example, Aero-Engine Controls, Rolls Royce, IrvingGQ, BAE SYSTEMS and the MOD.  Beyond defence, John has experience of developing decision support models for asset management for energy utilities (e.g. Scottish Power, SSE), water utilities (KTP with Scottish Water), critical infrastructure (e.g. anchorage condition assessment of Forth Road Bridge) and risk of train derailments with Railway Safety and Standards Board. 

John has worked with the European Food Safety Agency (EFSA) training staff for elicitation and quantification of expert uncertainty as well as leading the COST Working Group on Processes and Procedures for eliciting expert judgment.  The COST project resulted in the book Elicitation: The Science and Art of Structuring Judgement.

John is an Associate of the Society of Actuaries, a Chartered Statistician, and a member of the Safety and Reliability Society.  He has a Bachelor of Mathematics in Actuarial Science from the University of Waterloo, Canada and a PhD in Management Science from the University of Strathclyde. 

Publications

An elicitation process to quantify Bayesian networks for dam failure analysis
Verzobio Andrea, El-Awady Ahmed, Ponnambalam Kumaraswamy, Quigley John, Zonta Daniele
Canadian Journal of Civil Engineering Vol 48, pp. 1235-1244 (2021)
https://doi.org/10.1139/cjce-2020-0089
Design as a marked point process
Quigley John, Vasantha Gokula, Corney Jonathan, Purves David, Sherlock Andrew
Journal of Mechanical Design (2021)
Common design structures and substitutable feature discovery in CAD databases
Vasantha Gokula, Purves David, Quigley John, Corney Jonathan, Sherlock Andrew, Randika Geevin
Advanced Engineering Informatics Vol 48 (2021)
https://doi.org/10.1016/j.aei.2021.101261
Quantifying the benefit of structural health monitoring: can the value of information be negative?
Verzobio Andrea, Bolognani Denise, Quigley John, Zonta Daniele
Structure and Infrastructure Engineering (2021)
https://doi.org/10.1080/15732479.2021.1890139
Characteristics of a process for subjective probability elicitation
Quigley John, Walls Lesley
Expert Judgment in Risk and Decision Analysis (2021) (2021)
https://doi.org/10.1007/978-3-030-46474-5_13
Consequences of representativeness bias on SHM-based decision-making
Verzobio Andrea, Bolognini Denise, Quigley John, Zonta Daniele
Structure and Infrastructure Engineering (2020)
https://doi.org/10.1080/15732479.2021.1876740

More publications

Teaching

John provides specialist teaching for a number of programmes at various levels.  These have included teaching Management Science at all levels of undergraduate and postgraduate as well as Executive Education.  John has taught in 10 different international centres across Europe, the Middle East and South East Asia, as well as Executive Education in Canada. 

John is committed to making effective use of technology to support teaching and learning.  He has been involved in managing, developing and teaching on pedagogically successful online and distance courses, as well as investigating the effectiveness of using virtual reality environments to support teaching.    

Professional activities

Workshops on Mathematical Methods in Reliability
Organiser
2011
Selex Gallileo
Visiting researcher
2011
Risk Governance
Organiser
2011
Consultancy with Doosan Babcock Power Systems
Advisor
2010
Canada School Contribution Agreement - Foundations of Risk
To be assigned
2010
International Conference on Reliability
Keynote/plenary speaker
2010

More professional activities

Projects

Working across Disciplines to Understand and Improve Mass Evacuations: Examining Different Types of Risk and Contextual Pressures
Quigley, Kevin (Principal Investigator) Quigley, John (Co-investigator)
People who are responsible for mass evacuations during natural disasters are confronted with significant challenges: they must allocate and coordinate limited resources in a dynamic context, often in degraded conditions, and their decisions are consequential, time-constrained and often irreversible. Despite the risks that underpin these decisions and the real-world experience that exists in this domain, there is a dearth of study and knowledge concerning how those responsible for mass evacuation carry out their jobs, and how it might be generalized and improved. These events happen rarely and are dispersed across the country; this, coupled with bureaucratic and market constraints, diminish incentives and opportunities to study such low probability events. Yet there is reason to be concerned. From a national perspective, these events are happening much more often, and at a growing and significant human, financial and environmental cost.

This research project brings together a group of practitioners and scholars with expertise and experience in risk and evacuation. Our partners come from a variety of sectors, including academe, emergency management, telecommunications, politics and the voluntary sector, such as the Red Cross and Salvation Army. The project will be structured according to two interdisciplinary risk frameworks to allow us to examine the interplay between social context and risk characterization to determine the combined impact the two have on government risk regulation regimes. Contextual factors include dynamics such as the role of law and insurance, media and popular opinion, and the role of organized interests. Risk characterization distinguishes between those events that are complex, uncertain and ambiguous.

Our specific objectives are as follows.
1. Partner leading risk scholars with those that are responsible for mass evacuation to develop a shared understanding of evacuation risks.
2. Examine what guides the thinking and actions of those responsible for evacuation, considering the knowledge we have of certain risks and the contextual pressures that are exerted on the regime.
3. Improve dialogue between researchers, practitioners and communities in this domain.
4. Contribute to training tools, such as online tests and a tactical decision game, that help to train emergency managers to address risks during mass evacuations.
01-Jan-2020 - 31-Jan-2023
Development of a decision support system for the management of infrastructure
Tubaldi, Enrico (Principal Investigator) Patelli, Edoardo (Co-investigator) Quigley, John (Co-investigator)
06-Jan-2020 - 05-Jan-2022
Global Environmental Monitoring and Policy (GEMaP) Centre for Doctoral Training: Quantifying the risks and impacts of climate change on water resources in Scotland.
Peters, Joshua (Principal Investigator) Roberts, Jen (Principal Investigator) Quigley, John (Co-investigator)
This is an exciting opportunity to engage in international research to reduce risks of climate change on water resources. The studentship will be developing innovative decision-making techniques as well as identifying potential policy interventions to enhance actions to mitigate and adapt to climate change, or to reduce the impacts of climate change.
01-Jan-2019
EFSA EKE Training
Quigley, John (Principal Investigator) Colson, Abigail (Co-investigator)
27-Jan-2018 - 10-Jan-2019
TIC LCPE Repowering Hydro Plants - a Decision Support Tool
Walls, Lesley (Principal Investigator) Howick, Susan (Co-investigator) Quigley, John (Co-investigator) Revie, Matthew (Co-investigator)
01-Jan-2017 - 31-Jan-2018
Towards Game-changer Service Operation Vessels for Offshore Windfarms (NEXUS) H2020-BG-2016-2017
Vassalos, Dracos (Principal Investigator) Bedford, Tim (Co-investigator) Boulougouris, Evangelos (Co-investigator) Bujorianu, Luminita (Co-investigator) Lazakis, Iraklis (Co-investigator) McMillan, David (Co-investigator) Puisa, Romanas (Co-investigator) Quigley, John (Co-investigator) Revie, Matthew (Co-investigator) Theotokatos, Gerasimos (Co-investigator) Walls, Lesley (Co-investigator)
01-Jan-2017 - 30-Jan-2021

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