Modelling and Optimization of Reliability Functions for a Gas Compressing System

Abstract

This study entails the optimization of a gas compressing system to maximize its reliability and subsequently cut maintenance costs. In the course of the work, an improvement of Mean Time To Failure (MTTF technique was achieved by varying different failure cost of maintenance with targeted system reliability for a gas processing system and this was done using LINGO application programming bundles which was used to run a Nonlinear Mixed Integer Programing Model (NLMIP) to effectively enhance the processing plant and the reliability of five individual systems, including air compressing system: impeller, bearings, mechanical seals, valves and cooling fan within the gas compression system. The Excel solver was utilized to process the mean time to failure (MTTF) and the evaluated MTTF was additionally used to assess and understand the system failure history. From the study outcomes, it was ascertained that the MTTF of a system can be controlled through a maintenance planned support program The study outcomes also helped to determine that an alternative way to deal with the conventional maintenance practice is developing a support program through the execution of system reliability that reviews the system framework and sub-component and key parameter index, such as repair rate and failure rate.