Article | REF: G7028 V1

Forecast of obsolescence

Authors: Imen TRABELSI, Mariem BESBES, Marc ZOLGHADRI, Besma ZEDDINI

Publication date: November 10, 2023

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ABSTRACT

Many studies have sought to determine the methods and techniques for effective obsolescence management. They have shown that obsolescence forecast is a promising approach leading to better decision making. In other words, it would allow a proactive management of obsolescence.

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AUTHORS

  • Imen TRABELSI: Doctor - ISAE-Supméca, Quartz, Saint-Ouen, France

  • Mariem BESBES: Senior Lecturer - ISAE-Supméca, Quartz, Saint-Ouen, France

  • Marc ZOLGHADRI: University Professor - ISAE-Supméca, Quartz, LAAS-CNRS, Saint-Ouen, France

  • Besma ZEDDINI: Senior Lecturer - SATIE Laboratory CNRS-UMR 8029, CYTeh ENS Paris-Saclay, Cergy, France

 INTRODUCTION

Obsolescence, as a phenomenon affecting both customers and suppliers, as well as end consumers, has always existed, but until about ten years ago, it remained little perceptible to the general public . Not all industrial sectors have the same knowledge or awareness of the impact of obsolescence and scarcity on product flow management or corporate cash flow, for example.

Obsolescence was initially widely studied by manufacturers in sectors such as aeronautics and space. But the "recent" penetration of new technologies (software and products) in sectors such as automotive or home automation is creating real commercial, technical and scientific challenges. Obsolescence can have consequences for the environment, society, product requirements (maintainability, testability, supportability...) and even the way companies operate, in terms of the obsolescence of their production tools. To reduce these impacts, obsolescence must be managed effectively. The management of equipment obsolescence is an important parameter for the profitability of industrial companies, enabling them to mitigate the various risks it may entail. The most common form of obsolescence management is reactive, because it's easier to implement. However, it is sometimes recommended to use it only if the cost associated with the obsolescence of a component is low . If the probability of obsolescence and the associated costs are high, proactive methods are recommended . This article focuses on proactive obsolescence management, and more specifically on obsolescence forecasting techniques, as they enable better anticipation and therefore effective risk management.

First, the concept of obsolescence will be briefly introduced, followed by a description of the methods and techniques used to predict obsolescence.

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KEYWORDS

machine learning   |   obsolescence   |   Forecast   |   Obsolescence management techniques   |   Mathematical model


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Predicting obsolescence