Integrating lean tools in maintenance process optimization: a multicriteria analysis considering Brazilian companies

Purpose Maintenance activities directly impact equipment availability, operational costs and product quality. Moreover, the application of lean tools in this context has demonstrated significant potential for enhancing process efficiency. Therefore, this paper aims to explore the degree of integration of lean tools in the optimization of maintenance processes within Brazilian companies. Design/methodology/approach Initially, 11 critical factors (CF) for the effective integration of lean tools in maintenance management were identified in the literature. Based on these CFs, the authors carried out a survey with 64 experts to evaluate how effective is the application of lean tools in the Brazilian industrial context. Furthermore, the data collected from the experts was analyzed using a multicriteria decision analysis approach, the Fuzzy TOPSIS Class and a scenario-based sensitivity analysis. This methodology categorized each CF into one of three levels of application: excellent, moderate or unacceptable. Findings The survey was applied to professionals from different sectors, including general manufacturing, services, logistics, agroindustry and others. The study shows that 4 of the 11 CFs were classified as “excellent,” reflecting the high application intensity of traditional maintenance practices in Brazilian industries. On the other hand, most lean-related CFs were rated “unacceptable,” including Kansei Engineering, Heijunka, Andon and Jidoka. Sensitivity analysis confirmed these findings’ robustness, as classifications remained consistent despite varying respondent experiences. Originality/value The key contribution of this study lies in identifying specific lean tools that are underused, providing a clear direction for future research and industry improvement. This research integrates expert opinion and fuzzy methods to extract key information about the integration of lean tools in maintenance process optimization in Brazilian industries.