Strategies for Improving Maintenance Efficiency and Reliability Through Wrench Time Optimization
Journal Title: Journal of Industrial Intelligence - Year 2024, Vol 2, Issue 3
Abstract
This study investigates the optimization of wrench time to improve maintenance efficiency and reliability within a chemical processing plant. Wrench time, defined as the proportion of time spent directly performing maintenance tasks, was quantified through random observations of maintenance technicians. The findings revealed an average wrench time of 28% across the site, with variations between individual crew groups ranging from 20% to 35% and craft-specific wrench times varying from 13.3% to 45.5%. Several inefficiencies were identified, including prolonged wait times for equipment isolation, safety clearance, job planning, and parts procurement. Key contributing factors to these inefficiencies were found to include poor coordination between maintenance and production, insufficient work prioritization, inadequate adherence to schedules, a high volume of emergency tasks, and the absence of essential tools such as bills of materials (BOMs), equipment data, and troubleshooting checklists. To address these challenges, a range of improvement initiatives were implemented. These included enhancing coordination between maintenance and production by refining process steps, introducing additional planning tools for effective work prioritization, providing job aids, developing generic troubleshooting checklists, leveraging Industrial Internet of Things (IIoT) technologies, and establishing metrics to monitor progress. Early indications suggest that these initiatives have led to a reduction in maintenance backlog and gradual improvements in overall equipment effectiveness (OEE). It is anticipated that these changes will result in increased wrench time, enhanced maintenance quality and reliability, reduced downtime, and lower operational costs. For maintenance managers and engineers, the findings offer actionable insights into optimizing workflows and resource allocation, thereby contributing to the improvement of operational efficiency and reliability.
Authors and Affiliations
Mohammad Rahman
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