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This paper demonstrates a multi-criteria analytic hierarchy process (AHP) framework for evaluating and benchmarking maintenance performance in the select agro-based industry.

Initially, 20 maintenance practices (criteria) have been identified after a detailed literature review and discussion with the agro-based industry (sugar, textile and dairy industry) executives. These are then grouped into six maintenance management areas referred to as group criteria. The multi-criteria methodology consists of three steps: criteria identification, hierarchical modeling and data collection and maintenance performance evaluation, and benchmarking. The multi-criteria methodology proposed in this work facilitates two ways of carrying out benchmarking: (1) within the agro-based industry and (2) between the agro-based industry. The methodology has been explained by taking a case example of 45 agro-based industries (18 dairy, 13 sugar and 14 textile) from the western region of India. The sensitivity analysis of the model has been performed to ascertain the robustness of the results.

There is a difference in the maintenance performance across the agro-based industries due to different maintenance practices perceived differently.

The outcome of the model is mainly given by the judgments of the agro-based industry executives. It is also sensitive to any change in the relative importance to the evaluation criteria or the perception about the maintenance performance.

The study contributes in identifying the weakness, if any, by comparing the agro-based industry under investigation with the benchmark factory at three levels, namely, overall performance (factory level), group criteria (maintenance management area level) and criteria (maintenance practice level) allowing further improvement.

The methodology assists in better decision-making and in improving maintenance performance.

The purpose of this paper is to present an empirical investigation of maintenance performance (MP) management practices from the sugar industry in India.

Empirical data for this study were collected through field visits, interviews and published reports. Statistical methods including correlation, multiple regression and cluster analysis are utilized to accomplish the objective of the study.

Explanation with multiple regression analysis showed that the sugar industry MP is significantly and positively related to maintenance approach (MA), continuous improvement (CI), financial approach and spare part management (SPM). Cluster analysis showed that sugar industries focusing on MA, CI and policy development and organization are having higher MP. The cluster analysis also pointed out that there is a substantial variation in MP due to the type of ownership (private and cooperative) while no variation has been observed due to installed capacity (low and high).

The generalization of the results obtained in this work for the sugar industry can be possible through a larger sample size.

The study contributes to the better understanding of maintenance measures in the sugar industry and provides insights on the role of maintenance managerial practices in enhancing the MP.

The findings provide empirical evidence that maintenance practices across the sugar industry are important to improve MP.