Intelligent methods for the process parameter determination of plastic injection molding

Huang, Gao; Zhang, Yun; Zhou, Xundao; Li, Dequn

doi:10.1007/s11465-018-0491-0

Cited by 41 publications

(22 citation statements)

References 82 publications

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“…ese methods can guide optimization [132] and optimize some product defects that cannot be quantitatively described, such as flash, flow lines, and pores.…”

Section: Taguchi Methodmentioning

confidence: 99%

“…In order to obtain better optimization results, iterative optimization algorithms are often utilized to obtain a convergent global optimal combination of parameters. Iterative optimization approaches can be classified into deterministic and stochastic approaches according to the methods of improving the optimal point within each iteration [132]. Stochastic approaches have been mostly employed for injection molding process parameter optimization and are generally referred to as intelligent optimization algorithms.…”

Section: Iterative Optimization Methodsmentioning

confidence: 99%

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Intelligent Injection Molding on Sensing, Optimization, and Control

Zhao

Zhang

Dong

et al. 2020

Advances in Polymer Technology

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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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“…ese methods can guide optimization [132] and optimize some product defects that cannot be quantitatively described, such as flash, flow lines, and pores.…”

Section: Taguchi Methodmentioning

confidence: 99%

Section: Iterative Optimization Methodsmentioning

confidence: 99%

Intelligent Injection Molding on Sensing, Optimization, and Control

Zhao

Zhang

Dong

et al. 2020

Advances in Polymer Technology

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“…(3) rough the integrated application of the above two systems, the fault diagnosis of the injection molding process was realized, and the quality model of injection molding process was established to optimize the process parameters based on the data-driven [40,41], which could achieve "intelligent injection. "…”

Section: Injection Molding Integration Intelligent Controlmentioning

confidence: 99%

A Study on Intelligent Manufacturing Industrial Internet for Injection Molding Industry Based on Digital Twin

Wang

et al. 2021

Complexity

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As one of the basic manufacturing industries in China, injection molding industry is faced with the problems of low degree of informatization and intelligence, resulting in low production efficiency and high costs. It is urgent to integrate deeply with new generation of information technology to achieve transformation and upgrade. In this paper, an integrative industrial Internet architecture of “integration of intelligent equipment, intelligent production lines, intelligent workshops, intelligent factories, and intelligent formats” was described. The injection molding intelligent control system, the production management, control platform based on the MES system, and other key technologies were researched. Also, the smart factory architecture based on digital twin was established, and the implementation method of the smart factory digital twin system was elaborated. The feasibility and effectiveness of the method had been verified through the industrial application, which provided the technical supports for the injection molding industrial Internet system. Finally, the intelligent manufacturing industrial Internet cloud platform for injection molding industry was prospected.

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“…Data Provider(s). Given that potential providers invest resources when collecting parameter records [1,30,38] and possibly share their know-how with business partners or competitors, they are only willing to contribute against compensation [94], e.g., payments, and despite a required participation overhead. Furthermore, the data provider's identity and valuable provided data must be protected, i.e., no third party may get access to all records.…”

Section: Entities and Trust Assumptionsmentioning

confidence: 99%