Maintenance Strategies for Serial Production Lines Based on Grey Cluster Evaluation and Opportunity Maintenance

Abstract

To address the issues of “under-maintenance” and “over-maintenance” arising from uneven maintenance resource allocation and considering equipment variability for Serial production line in manufacturing, this study proposes an integrated maintenance strategy that combines grey clustering evaluation with opportunity maintenance. This approach aims to optimize the total system maintenance cost while ensuring equipment reliability. First, an Equipment importance Evaluation Index System is constructed. A Grey Clustering Model based on the Center-Point Mixed Possibility Functions is applied to classify production line equipment into three grey categories: “Secondary,” “Important,” and “Critical.” Subsequently, an opportunity maintenance model is established for critical equipment, targeting minimization of total cost rates while constraining equipment reliability. This model dynamically decides whether to perform synchronized opportunity maintenance on target equipment during repairs of other equipment by introducing an opportunity maintenance reliability calibration threshold, thereby integrating maintenance activities and reducing downtime. The model accounts for the impact of maintenance activities on equipment service life and failure rates, and employs a genetic algorithm for solution. Validation was conducted using an automated packaging line with 10 pieces of equipment from a company as a case study. Results demonstrate that the optimized maintenance strategy establishes differentiated reliability calibration thresholds for each critical piece of equipment. Compared to the original strategy, the total cost rate decreases by 25.7% compared to the original maintenance pattern.