LAUSR

Abstract Poor maintenance practices lead to significant economic, environmental, and social problems and affect the sustainable manufacturing paradigm. The predictive maintenance (PdM) technique helps to minimise problems by forecasting the conditions of the machines. Hence, it is essential for industrial managers to have sustainable predictive maintenance (SPM) practices in place to achieve economic, environmental, and social objectives in their manufacturing environments. However, industrial managers face numerous barriers that may prevent the adoption of SPM practices, and this study aims to identify and evaluate barriers to SPM practices. Initially, by literature review, thirty barriers were identified, and then, using the Pareto analysis, twenty barriers were finalized for evaluation. This study uses an integrated Interpretive Structural Modeling (ISM) and Grey-Decision-making trial and evaluation laboratory (DEMATEL) technique to understand the hierarchies and interrelationships among the barriers to SPM practices. A sensitivity analysis was conducted to examine the robustness of the result. The study reveals that no independent barriers are present in the course of study. Results indicate that poor commitment from top management, lack of a standard performance analysis system, no synchronization among technologies, a lack of awareness on sustainable maintenance practice among stakeholders, and the organization's reluctance to change are the primary causal barriers to SPM practices. This study implies that SPM practices can be productive for industrial communities when industries enhance their technological capability and show interest in maintenance activity. The findings of this study help industrial managers and policymakers to better understand the nature of the barriers towards implementing SPM practices in a manufacturing environment.