What are the key determinants of maintenance performance?

Abstract

Paper aims: The main objective of the research is to present a combination of fuzzy decision-making techniques to measure the performance of preventive maintenance systems. Originality: This research is a timely response to studying the prominent role of preventive maintenance performance in reducing cost, profitability, and overall organization's output. Research method: This study considers the application of "fuzzy DEMATEL" and ANP techniques for measuring maintenance performance and determining the causal relationships between the criteria and sub-criteria. Main findings: It is conjectured that functional and technical criteria, along that with individual and the environmental are of great importance. Among the sub-criteria, employee satisfaction, growth and learning, availability of machinery and equipment, quality of maintenance by the skilled and highly-trained workforce, deem to be the most important ones. Implications for theory and practice: The application of the decision techniques and the proposed measurement model for continuous improvement and promotion of maintenance performance.

Designing synchronizer module in CMMS software based on lean smart maintenance and process mining

“…Reviewed papers provide a big picture of MPM, for instance, its definition and boundaries (Parida and Kumar, 2009;Kumar et al, 2013), challenges and issues (Parida and Kumar, 2006), development of maintenance performance indicators (MPI) and maintenance performance frameworks (Parida et al, 2015). In addition, several questionnaires have been designed to identify the most utilized indicators in their respective fields (Muchiri et al, 2010;Simões et al, 2011;Ku and Kim, 2019;Darestani et al, 2020).…”

High performance teams: an investigation of the effect on self-management towards performance

“…Recent research agenda have also proved human factors value in Industry 4.0 maintenance programs. Darestani et al (2020) applied fuzzy DEMATEL and ANP techniques for measuring performance factors and concluded employee satisfaction, growth and learning, availability of machinery and equipment, quality of maintenance by the skilled and highly-trained workforce were found the most important factors for a competitive predictive maintenance performance. Guedes et al (2021) have complementarily investigated the role of teamwork motivation and human factors influence on production lines in a Total Productive Maintenance implementation project and brought consistent evidence of work motivation positive influence on project performance.…”