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      Intelligent Injection Molding on Sensing, Optimization, and Control

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          Abstract

          Injection molding is one of the most significant material processing methods for mass production of plastic products. It is widely used in various industry sectors, and its products are ubiquitous in our daily life. The settings and optimization of the injection molding process dictate the geometric precision and mechanical properties of the final products. Therefore, sensing, optimization, and control of the injection molding process have a crucial influence on product quality and have become an active research field with abundant literature. This paper defines the concept of intelligent injection molding as the integral application of these three procedures—sensing, optimization, and control. This paper reviews recent studies on methods for the detection of relevant physical variables, optimization of process parameters, and control strategies of machine variables in the molding process. Finally, conclusions are drawn to discuss future research directions and technologies, as well as algorithms worthy of being explored and developed.

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            Industrial applications of computed tomography

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                Author and article information

                Journal
                Advances in Polymer Technology
                Advances in Polymer Technology
                Hindawi Limited
                0730-6679
                1098-2329
                March 31 2020
                March 31 2020
                : 2020
                : 1-22
                Affiliations
                [1 ]The State Key Laboratory of Fluid Power and Mechatronic Systems, College of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China
                [2 ]Key Laboratory of 3D Printing Process and Equipment of Zhejiang Province, College of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China
                [3 ]Tederic Machinery Co., Ltd., Hangzhou 311224, China
                [4 ]Department of Mechanical Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA
                [5 ]Wisconsin Institute for Discovery, University of Wisconsin-Madison, Madison, WI 53715, USA
                Article
                10.1155/2020/7023616
                7359f69a-0638-4cfb-8236-987759765e62
                © 2020

                http://creativecommons.org/licenses/by/4.0/

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