Towards an intelligent prioritization flow of interventions in CMMS systems: An MCDM-based approach

Abstract

The automation of processes within industries plays a crucial role, especially with recent technological advancements and the increasing availability of massive data from manufacturing processes. This creates new opportunities in maintenance. Often, within companies, intervention requests are generated through Computerized Maintenance Management Systems (CMMS), where users fill in predefined fields. However, the classification of these intervention requests is typically done manually. This manual prioritization process poses a significant risk of accumulating delays, resulting in additional costs, and increasing safety risks for users and equipment. This study proposes integrating the Analytic Hierarchy Process (AHP) into the CMMS tools to automate the prioritization process of maintenance intervention requests on machines. This process relies on several essential criteria to consider when making decisions, namely safety impact, failure criticality, equipment type, and incident declaration date, based on the data already recorded in the intervention recorded in the CMMS. This automated prioritization process will enhance decision-making analysis capacity, optimize maintenance resources, and ensure a timely and effective response. A case study was conducted in a Moroccan company specialized in steel manufacturing, equipped with a Computerized Maintenance Management System (CMMS), and the results demonstrate that the concept of an automated intervention request prioritization process is effective, practical, and improves maintenance resource management.