Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Adaptive Process Control in Rubber Industry.

Rüdiger W Brause1, Ulf Pietruschka1

  • 1a J.W. Goethe University , Germany.

International Journal of Occupational Safety and Ergonomics : JOSE
|December 22, 1999
PubMed
Summary

This study presents an adaptive artificial neural network solution for rubber industry process control. This method offers significant human and economic benefits, even with limited data, improving rubber profile extrusion in tire production.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same journal

Impact of occupational safety and health services on urinary heavy-metal burden and respiratory function in construction workers.

International journal of occupational safety and ergonomics : JOSE·2026
Same journal

Correction.

International journal of occupational safety and ergonomics : JOSE·2026
Same journal

Temporal leadership and safety behavior of new-generation of construction workers: the moderating effect of perceived work meaning.

International journal of occupational safety and ergonomics : JOSE·2026
Same journal

Estimation of prevalence of pneumoconiosis among Indian dental healthcare professionals - an analytical cross-sectional study.

International journal of occupational safety and ergonomics : JOSE·2026
Same journal

Sensor technologies to monitor sedentary behaviour in the workplace: a scoping review.

International journal of occupational safety and ergonomics : JOSE·2026
Same journal

Optimization and prediction of overall moisture management capacity of cut-protective fabric.

International journal of occupational safety and ergonomics : JOSE·2026

Area of Science:

  • Industrial process control
  • Artificial intelligence in manufacturing
  • Polymer processing

Background:

  • Rubber industry process control faces challenges in parameter approximation.
  • Traditional methods may lack adaptability and efficiency.
  • Optimizing rubber extrusion for tire production is crucial.

Purpose of the Study:

  • To describe problems in rubber industry process control.
  • To present an adaptive solution using artificial neural networks.
  • To highlight the human and economic benefits of adaptive control.

Main Methods:

  • Modeling industrial problems with artificial neural networks.
  • Applying an adaptive solution to rubber profile extrusion.
  • Utilizing a limited number of training samples for model development.
Keywords:
extruder mask estimationknowledge accumulationneural networksnonlinear adaptive controlrubber production automatisation

Related Experiment Videos

Main Results:

  • The adaptive solution demonstrates good results in rubber extrusion.
  • Effective process parameter approximation was achieved.
  • The method shows viability even with sparse training data.

Conclusions:

  • Adaptive solutions offer attractive human and economic benefits for the rubber industry.
  • Artificial neural networks are effective for modeling and controlling rubber extrusion processes.
  • The proposed method is efficient, requiring minimal training data.