Motors are one of the vital equipment and generally the higher in numbers in oil and gas processing facilities. The primary function is to drive the process equipment such as compressors, fans, pumps, etc. Unreliability of the motors is a threat to safety but also to production loss and high operating expenditure. Motors experience higher failure rates and maintenance costs with age due to lower focus during useful life periods. In order to properly address the long-term reliability and maintainability of the motors and associated subsystems, this paper aims to propose a structured methodology and set of tools to ensure effective assessment. The proposed model mainly consists of data collection, analysis, assessment, financial analysis, and later developed actions to properly address the concerns. Equipment failure and repair data is a challenge to any reliability assessment; hence, the proposed methodology was introduced to collect, verify, and validate the data. Later, multiple tools such as Pareto Analysis, Failure Mode and Effect Analysis, and Root Cause Analysis were used to perform a detailed assessment. Weibull analysis was also explored to understand the failure modes, which ultimately helped in improving the availability of the motors. The proposed methodology has been applied to high-voltage motors to observe the effectiveness of the tools and proposed model in addressing reliability and maintainability. The results show significant reliability improvements of 12% (from 58% to 70%) and prove that the structured method can be effectively used in complex process facilities with significant benefits.