Design for maintenance: new algorithmic approach

Abstract

Purpose

This paper proposes a new simultaneous optimization model of the industrial systems design and maintenance. This model aims to help the designer in searching for technical solutions and the product architecture by integrating the maintenance issues from the design stage. The goal is to reduce the life-cycle cost (LCC) of the studied system.

Design/methodology/approach

Literature indicates that the different approaches used in the design for maintenance (DFM) methods are limited to the simultaneous characterization of the reliability and the maintainability of a multicomponent system as well as the modeling of the dynamic maintenance. This article proposes to go further in the optimization of the product, by simultaneously characterizing the design, in terms of reliability and maintainability, as well as the dynamic planning of the maintenance operations. This combinatorial characterization is performed by a two-level hybrid algorithm based on the genetic algorithms.

Findings

The proposed tool offers, depending on the life-cycle expectation, the desired availability, the desired business model (sales or rental), simulations in terms of the LCCs, and so an optimal product architecture.

Research limitations/implications

In this article, the term “design” is limited to reliability properties, possible redundancies, component accessibility (maintainability), and levels of monitoring information.

Originality/value

This work is distinguished by the use of a hybrid optimization algorithm (two-level computation) using genetic algorithms. The first level is to identify an optimal design configuration that takes into account the LCC criterion. The second level consists in proposing a dynamic and optimal maintenance plan based on the maintenance-free operating period (MFOP) concept that takes into account certain criteria, such as replacement costs or the reliability of the system.

Citation

Adjoul, O., Benfriha, K. and Aoussat, A. (2021), "Design for maintenance: new algorithmic approach", Journal of Quality in Maintenance Engineering, Vol. 27 No. 1, pp. 129-143. https://doi.org/10.1108/JQME-12-2018-0107