Abstract
It is fair to assume that the main challenge in maintenance decision making is the existence of a gap between theory and sustainable practice which is attributable to complexity, too much emphasis on development of new models that only serve to criticise earlier ones, underrepresentation of case study-based researches and lack of adequate incorporation of industry-based knowledge into most theoretical studies. In this paper, we revisited the application of the decision making grid (DMG) for maintenance optimisation but the main novelty here is to harmonise the strengths of the two most popular DMG approaches as opposed to the previous trends of advocating one over the other. Additionally, the current initiative limits assumptions associated with the process, since both DMG approaches depend on the main objective and nature of data involved. The data required for implementation are frequency of breakdown events and downtime for each event, which is readily available in all computerized maintenance management systems. This implies that we rely on just having access to some sort of a counter of faults and a timer for each event.
| Original language | English |
|---|---|
| Pages (from-to) | 397-414 |
| Journal | Production Planning and Control |
| Volume | 32 |
| Issue number | 5 |
| Early online date | 26 Mar 2020 |
| DOIs | |
| Publication status | Early online - 26 Mar 2020 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
Keywords
- Manufacturing systems
- industrial maintenance
- decision analysis
- decision making grid
- maintenance strategies
- case study
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