A Proposed Technique to Acquire Cavity Pressure Using a Surface Strain Sensor During Injection-Compression Molding

Guan, Wenxian; Huang, Hanxiong

doi:10.1115/1.4023376

Cited by 10 publications

(8 citation statements)

References 21 publications

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“…Cavity pressure has been found to be a reliable process indicator in injection molding, for both part quality and process monitoring [ 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 ]. Specifically, it has been found to provide real-time detection of part and process deviation.…”

Section: Introductionmentioning

confidence: 99%

“…The temperature signal showed a reliable correlation with respect to the resin-arrival-time difference, but the pressure signal did not produce a reliable result. Guan et al [ 25 ] proposed that the mold surface strain profile could indicate the part weight or thickness and the critical time when the part surface lost contact with the cavity surface in a large area. The monitoring of the mold surface strain could serve as an interesting alternative to the direct monitoring of the cavity pressure, with respect to process and part quality control for ICM.…”

Section: Introductionmentioning

confidence: 99%

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Research on Quality Characterization Method of Micro-Injection Products Based on Cavity Pressure

et al. 2021

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The cavity pressure in the injection molding process is closely related to the quality of the molded products, and is used for process monitoring and control, to upgrade the quality of the molded products. The experimental platform was built to carry out the cavity pressure experiment with a micro spline injection mold in the paper. The process parameters were changed, such as V/P switchover, mold temperature, melt temperature, packing pressure, and injection rate, in order to analyze the influence of the process parameters on the product weight. The peak cavity pressure and area under the pressure curve were the two attributes utilized in investigating the correlation between cavity pressure and part weight. The experimental results show that the later switchover allowed the injection to proceed longer and produce a heavier tensile specimen. By comparing different cavity pressure curves, the general shapes of the curves were able to indicate different types of shortage produced. When the V/P switchover position is 10 mm, the coefficient of determination (R2 value) of part weight, for the peak cavity pressure and area under the curve, were 0.7706 and 0.8565, respectively. This showed that the area under the curve appeared to be a better process and quality indicator than the peak cavity pressure.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Research on Quality Characterization Method of Micro-Injection Products Based on Cavity Pressure

et al. 2021

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“…A previous work [24] was carried out by the authors to investigate the role of the mold surface strain playing in the process monitoring of ICM. The results implied that the peak mold surface strain quantitatively depended on the peak cavity pressure in the compression stage.…”

Section: Introductionmentioning

confidence: 99%

Manipulation and online monitoring of micro-replication quality during injection-compression molding

Guan¹,

Huang²,

Wu³

2012

J. Micromech. Microeng.

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The accurate and rapid replication of micro-/nano-features with a high aspect ratio (AR) is one of the main challenges in micro-molding. In this work, the micro-injection-compression molding (μ-ICM) process and a new monitoring technique were combined to replicate micro-features with controllable and detectable ARs. Using a surface strain sensor mounted on the external surface of the mold, indirect acquisition of accurate cavity pressure during post-filling was realized, based on the specific pressure distribution on the mold predicted by the Hele-Shaw flow simulation. The feasibility of the proposed measuring technique was verified both numerically via finite-element analysis for the mold strain and experimentally by comparing cavity pressure profiles acquired directly and indirectly. Furthermore, primarily dominated by the maximum cavity pressure appearing during post-filling, the AR of molded polystyrene micro-feature in the downstream of cavity could be monitored via this technique with certain accuracy, and controlled by manipulating the compression force. Also the qualitative AR results of the other upstream micro-features were detectable in μ-ICM. Within a cycle time of 26 s, a maximum AR of about 12.1 was achieved on micro-features, indicating the potential for the mass production of complex micro parts applying μ-ICM.

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“…In addition, product quality can be monitored by installing sensors at different runner positions. Guan and Huang [20] used a surface strain sensor and pressure sensors installed at the cavity and surface of the mold, respectively, and found that the cavity pressure was proportional to the mold surface strain through a data-based regression method. Using this correlation, the precise cavity pressure distribution could be obtained indirectly via mold surface strain data.…”

Section: Process Optimizationmentioning

confidence: 99%

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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A Proposed Technique to Acquire Cavity Pressure Using a Surface Strain Sensor During Injection-Compression Molding

Cited by 10 publications

References 21 publications

Research on Quality Characterization Method of Micro-Injection Products Based on Cavity Pressure

Research on Quality Characterization Method of Micro-Injection Products Based on Cavity Pressure

Manipulation and online monitoring of micro-replication quality during injection-compression molding

Intelligent Injection Molding on Sensing, Optimization, and Control

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