John Quigley

Prof

  • United Kingdom

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Personal profile

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. 

Teaching Interests

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.    

Education/Academic qualification

Doctor of Philosophy, UNIVERSITY OF STRATHCLYDE

Award Date: 1 Jan 1998

Bachelor of Mathematics, University of Waterloo

Award Date: 1 Jan 1993

Keywords

  • Uncertainty
  • Statistics
  • big data analytics
  • decision making
  • Bayesian Networks
  • expert judgement

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