3. Obsolescence forecasting techniques
A prerequisite for any proactive obsolescence management approach is to predict when the system elements of interest will become obsolete. Such forecasts can only be probabilistic, and depend on numerous system parameters, both endogenous and exogenous. Anticipating obsolescence makes it possible to take rational decisions that minimize negative impacts. Against this backdrop, numerous studies have been developed to create models for forecasting obsolescence risk. Two types of methods can be distinguished: methods based on mathematical models and methods based on machine learning.
3.1 Mathematical models
-
Various mathematical techniques have been used to predict system obsolescence. The first method developed is based on the Gaussian model...
Exclusive to subscribers. 97% yet to be discovered!
You do not have access to this resource.
Click here to request your free trial access!
Already subscribed? Log in!
The Ultimate Scientific and Technical Reference
This article is included in
Environment
This offer includes:
Knowledge Base
Updated and enriched with articles validated by our scientific committees
Services
A set of exclusive tools to complement the resources
Practical Path
Operational and didactic, to guarantee the acquisition of transversal skills
Doc & Quiz
Interactive articles with quizzes, for constructive reading
Obsolescence forecasting techniques
Bibliography
Bibliography
Standards and norms
- Obsolescence management. AFNOR Édition. - IEC 62402 - 2019
- Diminishing Manufacturing Sources and material Shortages (DMSMS) – DoD Supply Chain Management Regulation. - SD-22 - 2022
- Obsolescence management – Exchange of information regarding on changes and discontinuations of products and units. - VDMA 24903 - 2017
Exclusive to subscribers. 97% yet to be discovered!
You do not have access to this resource.
Click here to request your free trial access!
Already subscribed? Log in!
The Ultimate Scientific and Technical Reference