Modelling Techniques to Support the Adoption of Predictive Maintenance

  • Ken R. McNaught
  • Adam T. Zagorecki
Part of the Decision Engineering book series (DECENGIN)


Contracting for availability and contracting for capability are becoming increasingly common practices in the defence world. With these new service-oriented contracts, the responsibility for through-life support, including maintenance, has been shifted from the user to the service provider. In this new environment, innovative approaches to improving maintenance and reliability are necessary and create new, unique opportunities for value co-creation between stakeholders. This chapter focuses on investigating the applicability and implementation of an approach to predictive maintenance which combines prognostic modelling with Condition Based Maintenance (CBM) and its role in providing improved service provision for the repair and maintenance of complex systems. The role of prognostic modelling and Health and Usage Monitoring Systems as the emerging technologies that enable a value-oriented approach to maintenance are discussed. Bayesian networks are discussed as a modelling framework that is appropriate to capture uncertainties related to predictive maintenance. Special focus is placed on reviewing practical challenges and proposing solutions to them. The discussion is summarised in the form of a practitioner’s guide to implementing prognostic modelling and CBM.


Bayesian Network Fault Diagnosis Domain Expert Prognostic Model Maintenance Policy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag London Limited  2011

Authors and Affiliations

  1. 1.Department of Engineering Systems and Management, Defence Academy of the UKCranfield UniversityShrivenhamUK

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