Share Email Print

Proceedings Paper

Tolerance allocation for an electronic system using neural network/Monte Carlo approach
Author(s): Mohammed Al-Mohammed; Daniel Esteve; Jaque Boucher
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

The intense global competition to produce quality products at a low cost has led many industrial nations to consider tolerances as a key factor to bring about cost as well as to remain competitive. In actually, Tolerance allocation stays widely applied on the Mechanic System. It is known that to study the tolerances in an electronic domain, Monte-Carlo method well be used. But the later method spends a long time. This paper reviews several methods (Worst-case, Statistical Method, Least Cost Allocation by Optimization methods) that can be used for treating the tolerancing problem for an Electronic System and explains their advantages and their limitations. Then, it proposes an efficient method based on the Neural Networks associated with Monte-Carlo method as basis data. The network is trained using the Error Back Propagation Algorithm to predict the individual part tolerances, minimizing the total cost of the system by a method of optimization. This proposed approach has been applied on Small-Signal Amplifier Circuit as an example. This method can be easily extended to a complex system of n-components.

Paper Details

Date Published: 12 December 2001
PDF: 12 pages
Proc. SPIE 4540, Sensors, Systems, and Next-Generation Satellites V, (12 December 2001); doi: 10.1117/12.450689
Show Author Affiliations
Mohammed Al-Mohammed, Institute National Polytechnique Toulouse/ENSEEIHT (France)
Daniel Esteve, Institute National Polytechnique Toulouse/ENSEEIHT and LAAS-CNRS (France)
Jaque Boucher, LAAS-CNRS (France)

Published in SPIE Proceedings Vol. 4540:
Sensors, Systems, and Next-Generation Satellites V
Hiroyuki Fujisada; Joan B. Lurie; Konradin Weber; Joan B. Lurie; Konradin Weber, Editor(s)

© SPIE. Terms of Use
Back to Top