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Automation of online quality control in injection moulding
Author(s) -
SchnerrHäselbarth O.,
Michaeli W.
Publication year - 2000
Publication title -
macromolecular materials and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 96
eISSN - 1439-2054
pISSN - 1438-7492
DOI - 10.1002/1439-2054(20001201)284:1<81::aid-mame81>3.0.co;2-q
Subject(s) - automation , quality (philosophy) , injection moulding , process engineering , molding (decorative) , documentation , control (management) , process control , process (computing) , materials science , manufacturing engineering , artificial neural network , computer science , production (economics) , data quality , control engineering , mechanical engineering , engineering , artificial intelligence , composite material , operations management , philosophy , epistemology , metric (unit) , economics , macroeconomics , programming language , operating system
Intelligent quality control for monitoring and documentation of the quality of injection‐molded parts is due to replace conventional quality control. Physical process data, such as temperature and pressure, are measured by online quality control within the production cycle. An empirical mathematical model of the molding properties allows their calculation on the basis of the data acquired at the end of each production cycle. The data obtained with the new neural algorithm show better results than all algorithms applied so far.