| Autor: |
Simon Didriksen, Kasper B. Hansen, Kristoffer V. Sigsgaard, Niels Henrik Mortensen, Julie K. Agergaard, Jingrui Ge |
| Přispěvatelé: |
Mortensen, N.H., Hansen, C.T, Deininger, M. |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
Didriksen, S, Hansen, K B, Sigsgaard, K V, Mortensen, N H, Agergaard, J K & Ge, J 2022, Utilising failure history to improve maintenance planning . in N H Mortensen, C T Hansen & M Deininger (eds), Proceedings of NordDesign 2022 . vol. DS 118, Cambridge University Press, NordDesign 2022, Copenhagen, Denmark, 16/08/2022 . https://doi.org/10.35199/NORDDESIGN2022.42 |
| DOI: |
10.35199/norddesign2022.42 |
| Popis: |
In the literature, improving decision support by utilisation of failure history maintenance data is considered to hold a great potential for enhancing the maintenance planning process, as de-cisions are based on experience and available information. Five principles were identified to structure maintenance failure history data to support decisions in the maintenance planning pro-cess, when having high frequency observations of failures. However, the possibility of utilising the full extent of the available failure history data for all occurring failures and the usefulness of failure history data for decision support in low-frequency observations of failures have not been addressed in the literature. Proposals often tend to present data structures that rely on high-frequency observations of failures on individual equipment with a limited possibility of failure history comparison across the entire system. This paper proposes a principle for linking failure history to a multi-classification model of existing physical systems for supporting key decisions in corrective maintenance when having low-frequency observations of failures. The proposal is a fundamental linkage principle indicated to precede those described in the current literature. It also expands the principles identified from the literature by enabling a comparison of failure history data across the entire system to support decisions when having both high- and low fre-quency observations of failures. Through a case study, the principle proved useful for support-ing key decisions in routine-based maintenance work, complex failures with low frequency observations, and identifying recurrent failures that may require new maintenance plan designs. Its potential benefits were the acceleration of knowledge gathering, improved consistency and quality of maintenance plan designs, comparison of all failures across the entire system when having low frequency observations, and indication and prevention of recurrent failures. How-ever, further studies must be conducted to assess the extent of the identified benefits and the effect of the proposed principle. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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