<![CDATA[Effective machine maintenance is key to ensuring productivity and operational efficiency in the industrial sector, where although preventive maintenance has become the standard, technological developments are now introducing more advanced predictive maintenance strategies, but a comprehensive comparison of the effectiveness of these two approaches in improving machine performance is still limited. This study aims to conduct a systematic review and meta-analysis of the efficacy of preventive and predictive maintenance methods, especially in the manufacturing industry, through a literature search in Scopus, Web of Science, and IEEE Xplore databases with related keywords, where empirical studies comparing both methods and their impacts on machine performance, including availability, reliability, and maintenance costs, are included. Meta-analysis was used to measure the difference in effectiveness between the methods, with study quality assessed using the AMSTAR checklist. The results showed that of the 25 studies that met the inclusion criteria, predictive maintenance was shown to be more effective in improving availability than preventive maintenance (effect size = 0.75, 95% CI: 0.60-0.90, p < 0.01), where factors such as cost, technology level, and machine type influenced the selection of the optimal maintenance method. This systematic review indicates that predictive maintenance is more effective in improving machine performance than preventive methods. However, the choice of the optimal method must be tailored to the specific industry context, and these findings are essential for decision-making in industrial maintenance management.]]>
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