Maintenance alternative integration to prognosis process engineering
Résumé
Studies over the last 20 years have indicated that around Europe, the direct cost of maintenance is equivalent to between 4% and 8% of total sales turnover. The indirect cost of maintenance is likely to be a similar amount (Pinjala et al., 2006). Thus, in the countries where modern maintenance practices have yet to be well adopted by industry, the potential savings from modern maintenance are massive (Alsyouf, 2006). These modern and efficient maintenances imply to identify the root-cause of component failures, to reduce the failures of production systems, to eliminate costly unscheduled shutdown maintenances, and to improve productivity as well as quality. It means, for the companies, to migrate from their traditional reactive approach, which is “Fail and Fix” to “Predict and Prevent” (Lee et al., 2003). The advantage of the latter is that maintenance is performed only when a certain level of equipment deterioration occurs. This “Proactive” maintenance is mainly based on prognosis process often considered as the Achilles heel while its goal is fundamental for implementing anticipation capabilities. This paper looks into this issue by proposing the development of an innovative prognosis process integrating the modelling of maintenance actions and their impacts on system performances. It leads to offer a maintenance aided decision-making tool able of assisting the decision-maker in selecting the best maintenance plan to be carried out.