Algorithm for assignment of maintenance activities through knowledge management

Abstract

The present study focuses on generating a methodological proposal for the allocation of human resources in the execution of maintenance tasks. This considers the implementation of an algorithm that assumes a set of maintenance activities (tasks or resources), a set of maintenance personnel (agents), a plausibility relationship over resources, a hierarchical relationship over agents and the preference that Agents have about resources. These assumptions lead to a hierarchy of personnel and identification of critical tasks. These hierarchy of personnel takes the management of knowledge as a fundamental part since the maintenance function requires very specific technical knowledge, normally tacitly stored among the personnel operating in these areas. The methodology is complemented by a new hierarchy of tasks using the methodology of analysis of failure modes, effects and criticality (AMFE). The results applied to a fleet of vehicles show that other assumptions are needed to obtain reasonable and fair criteria in the allocation of maintenance tasks, which are considered as weightings in a knowledge management function that include: Professional experience criteria, experience in the company, talent, and self-training.