The adoption of prognostic technologies in maintenance decision making: a multiple case study

W.W. Tiddens, A.J.J. Braaksma, T. Tinga

Research output: Contribution to journalConference articleAcademicpeer-review

13 Citations (Scopus)
1 Downloads (Pure)


Progresses in prognostic maintenance technologies offer opportunities to aid the asset owner in optimal maintenance and life cycle decision making, e.g. replacement or life-time extension of physical assets. Using accurate lifetime predictions is critical for ensuring just-in-time maintenance. Although there is considerable literature on specific techniques, reports on the adoption and usage of these methods show that only a small amount of companies have applied these techniques. This study therefore investigates why and how asset owners adopted and selected specific prognostic techniques and compares this with the literature. Based on the literature, a framework on generalized routes to implement prognostic technologies for maintenance decision making will be presented. Therefore, the main assumptions and descriptions in literature on the use of prognostic technologies are expressed in several postulates. These postulates are confronted with industrial practice by a multiple-case study conducted in different industries in the Netherlands. Results show issues and challenges companies experience in applying the right prognostic techniques. Among these are the identification of the correct parameters to measure, the translation of the gathered data into useful maintenance decision support and the need for guidance in prognostic technology route determination.
Original languageEnglish
Pages (from-to)171-176
JournalProcedia CIRP
Publication statusPublished - 2015
Event4th International Through-life Engineering Services Conference, TESConf 2015 - Cranfield, United Kingdom
Duration: 3 Nov 20154 Nov 2015
Conference number: 4


Dive into the research topics of 'The adoption of prognostic technologies in maintenance decision making: a multiple case study'. Together they form a unique fingerprint.

Cite this