Areas of expertise
- Operational Analysis and Simulation
- Safety, Resilience, Risk & Reliability
Dr Ken McNaught is a Senior Lecturer in operational research, with expertise in probabilistic decision analysis, particularly Bayesian networks and decision network influence diagrams, and in simulation modelling.
Ken has a BSc (Hons.) in Physics and Astronomy from Glasgow University, an MSc in Operational Research from Strathclyde University and a PhD in Operational Research from Cranfield University. He spent almost three years in the automotive industry with Austin Rover before joining Cranfield in 1988.
Ken's research interests encompass:
- probabilistic approaches such as Bayesian networks, influence diagram decision networks, decision trees, Markovian models and probabilistic risk analysis
- simulation including system dynamics, hybrid simulation and statistical aspects of simulation modelling.
Ken works in application areas as diverse as:
- reliability, maintenance and risk
- fault diagnosis and prognostic modelling
- intelligence analysis and course of action assessment
- adversarial risk analysis
- deception detection
- information fusion
- value of information assessment
- emergency preparedness.
Recent EPSRC funded projects have included
- Making Sense - concerned with decision support in the intelligence analysis domain
- KT Box - where Ken's contribution was concerned with predictive maintenance modelling.
Ken currently supervises three PhD students and is the Postgraduate Research Coordinator for science and engineering students at Cranfield University at Shrivenham.
- Centre for Defence Enterprise (formerly the MOD's Research Acquisition Organisation)
- Defence Equipment and Support
- Optimized Systems and Solutions (OSyS)
- BAE Systems
- Royal Norwegian Navy
Articles In Journals
- Boutselis P & McNaught K (2019) Using Bayesian Networks to forecast spares demand from equipment failures in a changing service logistics context, International Journal of Production Economics, 209 (March) 325-333.
- Isaksen BG & McNaught KR (2019) Uncertainty handling in estimative intelligence–challenges and requirements from both analyst and consumer perspectives., Journal of Risk Research, 22 (5) 643-657.
- Swinerd C & McNaught KR (2015) Comparing a simulation model with various analytic models of the international diffusion of consumer technology, Technological Forecasting and Social Change, 100 330-343.
- Swinerd C & McNaught KR (2014) Simulating the diffusion of technological innovation with an integrated hybrid agent-based system dynamics model, Journal of Simulation, 8 (3) 231-240.
- Swinerd C & McNaught KR (2012) Design classes for hybrid simulations involving agent-based and system dynamics models, Simulation Modelling Practice and Theory, 25 118-133.
- Neal DJ, Ringrose TJ & McNaught KR (2012) The human dimension of change in the introduction of the Network Enabled Capability concept within the United Kingdom Ministry of Defence, International Journal of Defense Acquisition Management, 5 1-18.
- McNaught KR & Chan A (2011) Bayesian networks for manufacturing, Journal of Manufacturing Technology Management, 22 (6) 734-747.
- Mcnaught KR & Chan A (2007) Using Bayesian networks to improve fault diagnosis during manufacturing tests of mobile telephone infrastructure, Journal of the Operational Research Society, 59 (4) 423-430.
- Alam MF, McNaught KR & Ringrose TJ (2006) An artificial neural network based metamodel for analysing a stochastic combat simulation, International Journal of Enterprise Information Systems , 2 (4) 38-57.
- McNaught KR, Alam FM & Ringrose TJ (2004) A comparison of experimental designs in the development of a neural network simulation metamodel, Simulation Modelling Practice and Theory, 12 (7-8) 559-578.
- McNaught KR (2002) Markovian Models of Three-on-One Combat Involving a Hidden Defender, Naval Research Logistics, 49 (7) 627-646.
- McNaught KR (1999) The effects of splitting exponential stochastic Lanchester battles, Journal of the Operational Research Society 50, 244-254, Journal of the Operational Research Society, 50 (3) 244-254.
- McNaught KR (2014) Probabilistic influence diagrams for modelling influence operations. In: 20th Conference of the international federation of operational research societies (IFORS 2014), Barcelona, 13-18 July 2014.
- Boutselis P & McNaught K (2014) Finite-time horizon logistics decision making/Newsvendor’s problems: consideration of a wider set of factors. In: Innovative Methods in Logistics and Supply Chain Management, Hamburg, 18-19 September 2014.
- McNaught KR & Sutovsky P (2012) Representing variable source credibility in intelligence analysis with Bayesian networks. In: 5th Australian Security and Intelligence Conference, Perth, 3 December 2012.
- McNaught KR & Sutovsky P (2012) Evidence marshalling with inference networks: an application to homeland security.. In: 2nd International Defense and Homeland Security Simulation Workshop, Vienna, 19 September 2012.
- McNaught KR, Zagorecki A & Garcia Perez A (2011) Knowledge elicitation for predictive maintenance modelling with Bayesian networks. In: 7th IMA International Conference on Modelling in Industrial Maintenance and Reliability, Cambridge, 18 April 2011.
- McNaught KR (2011) Detecting deception within a probabilistic modelling framework.. In: 1st International Defense and Homeland Security Simulation Workshop, Rome, 12 September 2011.
- McNaught KR & Zagorecki A (2010) Developing a decision analytic framework based on influence diagrams in relation to mass evacuations. In: International Conference on Emergency Preparedness (InterCEPt), Birmingham, 21 September 2010.
- McNaught K & Zagorecki A (2009) Prognostic Modelling with Dynamic Bayesian Networks. In: 4th European Conference on Intelligent Management Systems in Operations, Salford, 7 July 2009.
- McNaught KR & Zagorecki A (2009) Using dynamic Bayesian networks for prognostic modelling to inform maintenance decision making. In: IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) 2009, Hong Kong, 8-11 December 2009.
- Chan A & McNaught KR (2008) Using Bayesian networks to improve fault diagnosis during manufacturing tests of mobile telephone infrastructure.. In: 3rd European Conference on Intelligent Management Systems in Operations, Salford, 28-29 June 2005.
- McNaught KR, Sastry VVSS & Ng B (2005) Investigating the use of Bayesian networks to provide decision support to military intelligence analysts.
- McNaught KR, Alam MF & Ringrose TJ (2004) 'Using Morris' Randomized OAT Design as a Factor Screening Method for Developing Simulation Metamodels. In: Procs Winter Simulation Conf, Washington DC, USA, 5 December 2004.
- Alam FM, McNaught KR & Ringrose TJ (2004) Using Morris' randomized OAT design as a factor screening method for developing simulation metamodels. In: 2004 Winter Simulation Conference (WSC 2004), Washington, DC, 5-8 December 2004.
- Ringrose TJ, Alam MF & McNaught KR (2002) Investigating Appropriate Experimental Designs for Neural Network Simulation Metamodels. In: Procs 1st Simulation Study Group, B'ham, 2002, 1 January 2002.
- McNaught KR, Clifford SL, Vaughn ML, Fogg AJB & Foy MA (2001) A Bayesian belief network for lower back pain diagnosis.. In: 8th Artificial Intelligence in Medicine (AIME) Conference, Cascais, 1 July 2001.
- McNaught KR & O’Brien S An experiment in subjective probability revision among military officers.. In: Conference on ‘Risk, Decision and Human Error’, Trento, 15 January 2004.
- Enderwick TC & McNaught KR Reasoning with incomplete information. In: Operational Research Society, Annual Conference (OR49), Edinburgh, 4 September 2007.
- McNaught KR What can system dynamics learn from decision analysis? Conference of the Operational Research Society, York, September 2008. In: Operational Research Society, Annual Conference, York, 9 September 2008.
- McNaught KR Bayesian belief networks and simulation modelling.. In: 12th European Simulation Symposium, Hamburg, 28 September 2000.
- McNaught KR Markov Process Models of Combat. In: INFORMS Conference on Information Systems and Technology, San Diego, 4 May 1997.
- Alam MF, McNaught KR & Ringrose TJ Developing simulation metamodels for a maintenance float system.. In: Operational Research Society 2nd Simulation Workshop, Birmingham, 23 March 2004.
- McNaught KR Markov Chain Models of One-on-One Tactical Duels. In: INFORMS National Meeting, Los Angeles, CA, 23 April 1995.
- Carr S & McNaught KR An experiment in likelihood elicitation in the context of intelligence analysis.. In: Operational Research Society, Annual Conference (OR49), Edinburgh, 4 September 2007.
- McNaught KR Influences and connections between system dynamics and decision analysis.. In: 21st International System Dynamics Conference, New York, 20 July 2003.
- McNaught KR An application of Bayesian networks to military decision support.. In: OR 46 : Operational Research Society Conference, York, 7 September 2004.
- McNaught KR & O'Brien S Investigating bias in subjective probability revision.. In: IFORS 2002 (International Federation of Operational Research Societies), Edinburgh, 8 July 2002.
- McNaught KR The Effects of Nodal Structure on Exponential Stochastic Lanchester Battles. In: Conference of the Operations Research Society of America and the Institute of Management Sciences, Boston, MA.
- McNaught KR Some Aspects of Aggregation in Stochastic Lanchester Models.. In: INFORMS/CORS, Montreal, 26 April 1998.
- McNaught KR An Examination of Engagement Activity During Exercise Battles, , Nashville, May 1991. In: Conference of the Operations Research Society of America and the Institute of Management Sciences, Nashville, TN.
- McNaught KR Modelling Stochastic Firefights. In: INFORMS, Seattle, WA, 25 October 1998.
- Hockley CJ, Zagorecki A, Duncan A, McNaught KR & Wand K Tools for HUMS Exploitation. In: 8th DSTO International Conference on Health & Usage Monitoring (HUMS2013), Melbourne Convention Centre, 25 February 2013.
- McNaught KR Markov chain models of one-on-one combat.. In: 15th European Simulation Multiconference, Prague, 6 June 2001.
- McNaught K, zagorecki a & Zagorecki A (2011) Modelling techniques to support the adoption of predictive maintenance in the context of service provision. In: Complex Engineering Service Systems: Concepts and Research, London: Springer-Verlag, p. 277-296.
- McNaught KR (2007) A review of Bayesian networks applied to reliability and maintenance modelling.. In: Tony Christer 1940-2006: An Incredible Man. Martins H, Wang W and Sharples S (ed.), Salford: University of Salford.
- McNaught KR (2001) An introduction to Bayesian belief networks. In: OR 43 Keynote Papers. Ranyard J (ed.), Operational Research Society, p. 39-61.
- Bowen KC & McNaught KR (1996) Mathematics in Warfare - Lanchester Theory. In: The Lanchester Legacy. Fletcher J (ed.), Coventry: Coventry University Press, p. 141-156.