Maintenance management improvement based on reliability centered maintenance II in energy generating industries

Abstract

The X power plant is one of an electric company subsidiaries. Engaged in providing electricity for the certain regions. In general, the type of treatment from X power plant is short and long term maintenance. The application of these two systems helps X power plant to maintain the machines. The author argues that the type of maintenance from X power plant is not or is not yet optimal, the author wants to test whether reliability centered maintenance II treatment method can be applied in X power plant so that the efficiency and maintenance of the machine is in accordance with their individual needs. After implementing the RCM II information worksheet and RCM II decision worksheet, it is found that the existing maintenance management system in X power plant can be. Several incompatibility are detected, and should be matched with the corresponding maintenance method. For further research, the author recommend that the object of research are broadened so that the RCM II method can be used on other energy generating industries.

Data-based decision-making in maintenance service delivery: the D3M framework

“…Such should be addressed not only in terms of PSS design (Meier et al, 2011) but also in terms of methods and tools for data exploitation (Tang and Liao, 2021) and decision-making (Roy et al, 2013), which should be selected and developed in accordance with the characteristics of PSS (Pirola et al, 2020). The interviews contributed to understanding how companies currently manage decisions and deliver maintenance and shed light on how data from various sources are collected, managed and processed, confirming, in many cases, the problems highlighted in the literature (Brundage et al, 2019;Mahlam€ aki et al, 2016;Singgih et al, 2019). The D3M framework was used during the interview to map these aspects and picture the current situation in the companies.…”

“…The literature analysis further shows that only a few contributions consider the whole process perspective and combine information from different sources (e.g. service provider and customer characteristics) to support the selection of the maintenance typology, for example, through the use of simulation (Fargnoli et al, 2019), association rules (Xiao et al, 2016) or previous knowledge (Singgih et al, 2019).…”

“…The review spotlights the lack of structured approaches, methods and tools to support decision-making in maintenance (Liang, 2020;Passath and Mertens, 2019) by integrating past knowledge with information extracted from data (Brundage et al, 2019;Singgih et al, 2019) and jointly considering the machine and maintenance perspectives. Based on these findings, this research contribution proposes a framework addressing the gaps identified above from the perspective of the (1) phases composing the process, (2) the actors involved and (3) methods and tools supporting decision-making.…”