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Maintenance is a critical business function with a great impact on economic, environmental and social aspects. However, maintenance decisions' planning has been driven by merely economic and technical measures with inadequate consideration of environmental and social dimensions. This paper presents a review of the literature pertaining to sustainable maintenance decision-making models supported by a bibliometric analysis that seeks to establish the evolution of this research over time and identify the main research clusters.

A systematic literature review, supported with a bibliometric and network analysis, of the extant studies is conducted. The relevant literature is categorized based on which sustainability pillar, or possibly multiple ones, is being considered with further classification outlining the application area, modeling approach and the specific peculiarities characterizing each area.

The review revealed that maintenance and sustainability modeling is an emerging area of research that has intensified in the last few years. This fertile area can be developed further in several directions. In particular, there is room for devising models that are implementable, based on reliable and timely data with proven tangible practical results. While the environmental aspect has been considered, there is a clear scarcity of works addressing the social dimension. One of the identified barriers to developing applicable models is the lack of the required, accurate and timely data.

This work contributes to the maintenance and sustainability modeling research area, provides insights not previously addressed and highlights several avenues for future research. To the best of the authors' knowledge, this is the first review that looks at the integration of sustainability issues in maintenance modeling and optimization.

Deploying an effective maintenance strategy across an organization stands out as an essential risk mitigation measure that plays a critical role toward improving the reliability and availability of production facilities. The purpose of this paper is to propose a simple, yet well-structured approach toward prioritizing maintenance actions as part of a reliability centered maintenance (RCM) implementation plan, and selecting the most important subset of those actions subject to time and budget constraints.

A comprehensive RCM actions prioritization methodology is proposed using four criteria: severity, benefit to cost ratio, customer satisfaction, and easiness of action implementation. The method utilizes fuzzy inference system (FIS) to incorporate subject matter experts’ feedback into the decision-making process. The output of the FIS, which takes the form of a numerical weight that assesses the relative importance of each criterion, is then fed into a binary integer program that selects the optimal maintenance actions out of a set of possible actions.

The implementation of the developed methodology is demonstrated using a real-life example of a hydraulic brake system circuit that is used in construction equipment. The computational results illustrate the validity of the proposed approach and indicate that the selection of which maintenance actions to carry out is impacted by the relative importance (i.e. weight) of the considered criteria.

The work presented in this paper provides the decision makers with a systematic procedure that helps in selecting the most relevant maintenance actions instead of making the selection in a complete ad hoc manner or based merely on subjective opinions.