Artificial neural network-based online defect detection system with in-mold temperature and pressure sensors for high pr
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ORIGINAL ARTICLE
Artificial neural network-based online defect detection system with in-mold temperature and pressure sensors for high precision injection molding Joseph C. Chen 1 & Gangjian Guo 1
&
Wei-Nian Wang 1
Received: 9 July 2020 / Accepted: 27 August 2020 # Springer-Verlag London Ltd., part of Springer Nature 2020
Abstract Injection molding is widely used for mass production of thermoplastic parts with complex geometry and tight dimensional tolerance. However, due to the unavoidable shrinkage and uncontrollable process condition variations, defective parts may occur. Thus, dimensional control and online defect detection are extremely important for quality control, particularly for high precision injection molding. The conventional monitoring and control are based on machine setting parameters, but it may not capture the molding condition variations under the unchanged machine settings. This paper develops an artificial neural network (ANN)based online defect detection system with the real-time data extracted from in-mold temperature and pressure sensors. Both multilinear linear regression (MLR) and ANN models were developed based on the real-time data, but the ANN model is much better than the MLR model. The ANN model has a high prediction accuracy of 98.34% with the coefficient of determination R2 of 91.37%. When applied to defect detection, the ANN model has a defect detection accuracy of 94.4% in consideration of type I and type II errors. This research demonstrates the feasibility of integrating such an ANN-based expert system to injection molding process, to improve online dimensional monitoring. The ANN model also can be easily adapted for detecting other quality characteristics of injection moldings, which would be helpful for the advances in intelligent injection molding. Keywords Artificial neural network . Injection molding . Online defect detection . Sensors
1 Introduction Injection molding is one of widely applied manufacturing techniques that are suitable for mass-producing thermoplastic parts with complex geometries and various mechanical properties. It is widely used in a variety of industry sectors such as medical, aerospace, automotive, and consumer electronics industries. Injection molding is a versatile process. Its products can easily change colors by blending with pigments during the process, without a secondary painting step [1]. As a highly tailorable material, thermoplastic can be reinforced with all kinds of fibers and property-modification particles during the injection molding process [2–5]. Although injection molding has many benefits to offer, it is a very complicated process
* Gangjian Guo [email protected] 1
Department of Industrial & Manufacturing Engineering & Technology, Bradley University, Peoria, IL 61625, USA
which consists of a plasticating stage and an injection stage. In the plasticating stage, solid plastic pellets are fed into the hopper and then pushed forward by the reciprocating screw inside the heated barrel. The plastic pellets are heated, mixed,
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