Optimization of Water Injection Pump (WIP) Maintenance at PT. Z
DOI:
https://doi.org/10.59188/eduvest.v6i1.51982Keywords:
Reliability, MTTF, Optimization, Monte Carlo Simulation, Distribution Test, WIPAbstract
In the competitive oil and gas industry, equipment reliability and operational efficiency are critical success factors. The availability of effective spare parts presents a significant challenge that must be addressed to prevent downtime and financial losses. The current problem involves a loss of approximately 100 barrels of oil per day (bopd) due to the failure of one water injection pump (WIP) unit. Therefore, an optimal WIP spare parts planning method is required to maintain operational reliability. This study addresses this issue by determining the reliability condition of WIP units, optimizing maintenance schedules, and selecting appropriate failure data distribution tests using time-to-failure (TTF) analysis. Maintenance optimization for WIP at PT. Z was conducted using Monte Carlo simulation with distribution selection methods, specifically the Bayesian Information Criterion (BIC) and Akaike Information Criterion (AIC). The simulation results revealed that WIP A is in the wear-out phase, whereas WIP B, C, D, and E are in the useful-life phase (WIP D and E with extended operational periods). Based on Monte Carlo simulation results for five WIP types operated over 15 years, optimal maintenance intervals were determined: day 1691 for WIP A, day 1729 for WIP B, day 2160 for WIP C, day 3629 for WIP D, and day 3629 for WIP E from initial operation. Implementing planned maintenance has the potential to significantly reduce costs associated with each WIP unit failure. These research findings can be applied to other equipment to achieve potential cost savings from unplanned maintenance.
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