Applications of Neural Nets and Evolutionary Programming to Process Monitoring

961634

05/01/1996

Event
International Programmable Conference & Exposition
Authors Abstract
Content
Process modeling benefits are well understood: better quality, and minimal scrap, environmental impact, and unplanned maintenance. The cost of implementing and maintaining process models, however, has limited application of model-based process monitoring and control.
New technologies have changed this, with adaptive process modeling reducing the cost of developing and maintaining process models, and thus broadening applications. Applications of neural networks and evolutionary programming have demonstrated quantifiable benefits in process performance, maintenance costs, emissions, and scrap rates. Discrete part, and batch and continuous processing applications are presented to illustrate application qualification criteria and typical costs and benefits.
Meta TagsDetails
DOI
https://doi.org/10.4271/961634
Pages
5
Citation
VerDuin, W., "Applications of Neural Nets and Evolutionary Programming to Process Monitoring," SAE Technical Paper 961634, 1996, https://doi.org/10.4271/961634.
Additional Details
Publisher
Published
May 1, 1996
Product Code
961634
Content Type
Technical Paper
Language
English