Academic Journal
Interpretation of the effect of transient process data on part quality of injection molding based on explainable artificial intelligence.
| العنوان: | Interpretation of the effect of transient process data on part quality of injection molding based on explainable artificial intelligence. |
|---|---|
| المؤلفون: | Gim, Jinsu1,2 (AUTHOR), Turng, Lih-Sheng1,2 (AUTHOR) turng@engr.wisc.edu |
| المصدر: | International Journal of Production Research. Dec2023, Vol. 61 Issue 23, p8192-8212. 21p. |
| مصطلحات موضوعية: | *ARTIFICIAL intelligence, *PLASTIC products manufacturing, INJECTION molding, DATA quality, QUALITY factor, MACHINE learning |
| مستخلص: | This paper proposes an interpretation methodology for the effect of transient process data on quality of injection molded parts. The transient process data measured in the actual processing space have been regarded as the most relevant information to manufacturing processes and product quality. However, its interpretation to pinpoint which feature in the data would affect part quality has traditionally relied on knowledge and understanding of the manufacturing process. The main objective of this method is to reduce the dependency of the transient process data analysis on process knowledge and understanding by using explainable artificial intelligence (XAI). The contribution of the 'section-wise' features in the transient process data to the quality prediction of machine learning (ML) models was investigated for the first time. The interpretation results of the effect of cavity pressure and mold surface temperature on four different quality factors represented reasonable explanations of the characteristics of the polymer materials, product geometry, and molding process. Due to the intermediate relationship of the transient process data with the user-specified process parameters and the resulting quality variables, the interpretation results can be further utilized to optimize the process and provide the optimal transient process data profile for best part quality. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| قاعدة البيانات: | Business Source Index |
كن أول من يترك تعليقا!