Abstract
Maintenance productivity improvement is significant to manufacturing companies that seek to be-come leaders in their industries and remain competitive. This forces many organizations to consider different ways of working to increase production throughput, product quality, and customer satisfac-tion while considering costs. Equipment downtime remains a challenge in the gas processing plant, resulting in high maintenance costs, and negatively influencing maintenance productivity. Equip-ment downtime has never been an option for maintenance managers since it always results in pro-duction loss. A plant's maintenance strategies and processes can eliminate unnecessary equipment downtime and produce acceptable results if correctly implemented.
Gas processing plants are consistently confronted with plant downtime from equipment failure, which remains a tremendous challenge. The equipment performance depends primarily on the quality of maintenance execution. Therefore, dealing with breakdowns before occurrence is essential for the maintenance department to select the appropriate maintenance strategy. The study explores different categories of maintenance strategies, namely Corrective Maintenance (CM), Preventive Maintenance (PM), Predictive Maintenance (PdM), and Reliability Centred Maintenance (RCM). This category includes conventional Failure Mode and Effects Analysis (FMEA), Failure Mode, Effects and Criti-cality Analysis (FMECA), and Root Cause Analysis (RCA) to investigate the most basic causes of equipment or process disruption. The importance of Maintenance Performance Measurement (MPM) at the strategic level is discussed in detail. The focus is on ensuring the good working condition of equipment to prevent breakdowns. The study further develops a research methodology to measure Mean Time Between Failure (MTBF), Mean Time to Repair (MTTR), and plant availability. This research methodology will, in turn, improve the company's overall plant performance.
The data collected are from the breakdowns and failure records for the equipment under considera-tion. Critical equipment such as pumps, compressors, vessels, reactors, strainers, heat exchangers, valves, and flow transmitters are isolated to determine which contributes the most to plant downtime. The data collection process starts by analysing the data from historical records, which are customarily recorded into the Computerized Maintenance Management System (CMMS) by the maintenance de-partment. A statistical technique called Pareto is utilized to select a partial number of critical equip-ment to substantiate the adequate areas for continued development to minimize downtime and in-crease equipment availability.
The results obtained find that the current maintenance strategy fulfils the minimum requirements. However, the fact that many different types of equipment are grouped into one strategy causes chal-lenges concerning the tracking of maintenance execution. Some equipment experiences repetitive...