A MFMEA Development for Centrifugal Pumps Based on AHP: A Case Study in Oil Industry

In order to develop an effective maintenance strategy for machines and equipment in oil, gas, and petrochemical industries, it is essential to conduct failure analysis that encompasses investigation into the root causes, modes, mechanism, and effects of failure. The failure mode and effect analysis technique in machines, equipment, and their components (MFMEA) as one of the common techniques for analyzing the priority risk of failure modes, has limitations such as neglecting the evaluation criteria weight and the impact of the root causes of failures. To overcome these limitations, this paper introduces a Developed Machine Failure Mode and Effect Analysis (DMFMEA) framework that integrates the Analytic Hierarchy Process (AHP) to systematically assign weights to failure root causes, leading to more accurate Risk Priority Number (RPN) calculations. This framework was employed for five BB۱-type between bearings centrifugal pumps at an oil processing complex. Failure data were collected from maintenance records, condition monitoring results and expert opinions from operations, maintenance and condition monitoring teams. Furthermore, the robustness of the proposed method was validated using Multi Criteria Decision Making (MCDM) technique: Simple Additive Weighting (SAW). The findings confirm that DMFMEA offers a structured and data-driven approach that addresses MFMEA's shortcomings, enhances predictive maintenance strategies and supports more effective risk management in industrial systems.

Keywords:

Centrifugal Pumps , MFMEA , AHP , RPN , SAW