Intelligent setting of process parameters for injection molding based on case-based reasoning of molding features
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Intelligent setting of process parameters for injection molding based on case-based reasoning of molding features Shengrui Yu1,3 · Tianfeng Zhang1 · Yun Zhang2 · Zhigao Huang2 · Huang Gao2 Lih-Sheng Turng3,4 · Huamin Zhou2
· Wen Han1 ·
Received: 31 January 2020 / Accepted: 19 August 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Process parameters of injection molding are the key factors affecting the final quality and the molding efficiency of products. In the traditional automatic setting of process parameters based on case-based reasoning, only the geometric features of molds are considered, which may not be the representative feature of products and cause the reasoning process to fail. This problem of failure manifests itself in that the molding process parameters inferred by the reasoning system may be very different between molds with similar geometric features or very similar between molds with different geometric features. Therefore, this paper proposes a case-based-reasoning method based on molding features in order to overcome this problem by a method of dimensionality reduction, composed of three stages which (1) obtain the injection pressure profile data through actual injection molding or filling simulation analysis, (2) calculate the similarity of the pressure profiles between target case and each of source cases in case database using the nearest neighbor method, and sort according to the value of similarity, (3) find the case with a maximum of similarity out as the one closest to the target case, and take the process parameters of the most similar case as the solution of the target case according to case modification strategies. This method simplifies the high-dimensional molding features to the pressure profile at the injection location with two-dimensional data features. Experiments show that the new method has a high retrieval accuracy and sensitivity. Moreover, even slight differences in molding can be captured easily. Keywords Injection molding · Process parameter · Intelligent setting · Molding feature · Pressure profile
Introduction The optimization of injection process may effectively improve product quality (Mohan et al. 2017; Dar et al. 2017), shorten cycle time (Kitayama et al. 2017a, b), and even reduce
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Huang Gao [email protected] Shengrui Yu [email protected]
1
School of Mechanical and Electronic Engineering, Jingdezhen Ceramic Institute, Jingdezhen 333403, China
2
State Key Lab of Material Processing and Die & Mold Technology, Huazhong University of Science and Technology, Wuhan 430074, China
3
Wisconsin Institutes for Discovery, University of Wisconsin-Madison, Madison, WI 53715, USA
4
Department of Mechanical Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA
manufacturing costs (Tian et al. 2017; Liu et al. 2017) in plastic injection molding. Traditionally, the determination of process parameter depends on the trial-and-error method (Tian et al. 2017), but this method cannot take into consideration the eff
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