Optimization process parameters and adaptive quality monitoring injection molding process for materials with different viscosity

Su, Chi‐Wei; Su, Weijie; Cheng, Feng-Jung; Liou, Guan-Yan; Hwang, Sheng-Jye; Peng, Hsin‐Shu; Chu, Hsiao-Yeh

doi:10.1016/j.polymertesting.2022.107526

Cited by 17 publications

(17 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It can be thus observed that when molding PS materials, the melt flow resistance requires a higher molding pressure to push the plastic materials, making the melt pressure-peak and viscosity index of the PS greater than that of PP materials. Through the literature [1,2], it can be found that by installing the sensor at the barrel position and by sensing the pressure trend change of the melt, the pressure trends obtained are the same as at the nozzle position. Moreover, by installing the sensor at the barrel position, it is also possible to grasp the changes in the plasticizing and injection conditions of the material.…”

Section: Melting Pressure and Its Relevance To Viscosity Indexmentioning

confidence: 99%

“…Scientific injection molding technologies involve the integration and collaboration of cyber-physical systems and smart manufacturing. In order to achieve adaptive process control and production optimization, the injection molding system with real-time sensing has gradually become the development and application trend of smart injection molding in the rubber and plastics industries [1][2][3][4]. Injection molding is a highly non-linear process in which many factors affect the product quality during long-run fabrication processes.…”

Section: Introductionmentioning

confidence: 99%

“…The present study focused on PP and PS molding finished products with a thickness of 4 mm and investigated the melt-flow characteristics and its pressure-trend change. Additionally, the calculation formula (Equation ( 1), [1,2,5,[21][22][23]) of a viscosity index was introduced to compare the effects of PP and PS under the same and different MI parameters. During injection molding, properties of the material can vary considerably due to the difference between semi-crystalline (PP) and amorphous (PS) polymer materials; at the same time, a higher melting pressure is generally required in order to accurately obtain samples' weight/dimensional.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Injection Barrel/Nozzle/Mold-Cavity Scientific Real-Time Sensing and Molding Quality Monitoring for Different Polymer-Material Processes

Liew

Peng

Huang

et al. 2022

Sensors

Self Cite

View full text Add to dashboard Cite

Scientific injection molding technologies involve the integration and collaboration of cyber-physical systems and smart manufacturing. In order to achieve adaptive process control and production optimization, injection molding systems with real-time sensing have gradually become the development- and application-trend of smart injection molding. At the same time, this technology is a highly non-linear process in which many factors affect the product quality during long-run fabrication processes. Therefore, in order to grasp changes in the characteristics of plastic materials and product quality monitoring, the injection process has become an important research topic. We installed sensors in the molding machine (injection barrel, nozzle, and mold-cavity) to collect the melting pressure and used different materials (semi-crystalline and amorphous polymer; the melting-fill-index (MFI) is unified to 14.5 ± 0.5 g/10 min) to explore the influences of melting pressure variation and its viscosity index on the quality characteristics of molded products. The experiment reveals that a combination of barrel, nozzle, and mold-cavity sensing on the melt-pressure trend-based injection process-control incorporated with viscosity index monitoring can confirm the weight and shrinkage variation of the injection product. At the same time, the pressure and viscosity index value measured and calculated during the melt-filling of two materials with similar MI resulted in significant variations in the amorphous polymer. This study showed the possibility of mastering and controlling the rheology (barrel position) and shrinkage properties of polymers and successful application in various product-quality monitoring platforms.

show abstract

Section: Melting Pressure and Its Relevance To Viscosity Indexmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Injection Barrel/Nozzle/Mold-Cavity Scientific Real-Time Sensing and Molding Quality Monitoring for Different Polymer-Material Processes

Liew

Peng

Huang

et al. 2022

Sensors

Self Cite

View full text Add to dashboard Cite

show abstract

“…By using one sensor on the nozzle of the injection-molding machine, the cost of the adaptive process control system can be reduced, and the product weight variation can be minimized to 0.21%. Su et al [ 20 ] proposed a standard process parameter setup procedure and combined the tie-bar strain gauge and nozzle pressure sensor to reduce the variation of product weight.…”

Section: Introductionmentioning

confidence: 99%

Optimize Injection-Molding Process Parameters and Build an Adaptive Process Control System Based on Nozzle Pressure Profile and Clamping Force

Liou

Cheng

et al. 2023

Polymers

Self Cite

View full text Add to dashboard Cite

The injection-molding process is a non-linear process, and the product quality and long-term production stability are affected by several factors. To stabilize the product quality effected by these factors, this research establishes a standard process parameter setup procedure and an adaptive process control system based on the data collected by a nozzle pressure sensor and a tie-bar strain gauge to achieve this goal. In this research, process parameters such as the V/P switchover point, injection velocity, packing pressure, and clamping force are sequentially optimized based on the characteristics of the pressure profile. After the optimization process, this research defines the standard quality characteristics through the optimized process parameters and combines it with the adaptive process control system in order to achieve the purpose of automatic adjustment of the machine and maintain high-quality production. Finally, three different viscosity materials are used to verify the effectiveness of the optimization procedure and the adaptive process control system. With the system, the variation of product weight was reduced to 0.106%, 0.092%, and 0.079%, respectively.

show abstract

“…The time at which the filling stage ends and the holding stage starts is referred to as the switchover point (SWOP). The right setting of the SWOP is crucial for the stability of the quality of injection-molded parts [ 24 ]. The traditional method to determine the SWOP uses an offline mass measurement.…”

Section: Introductionmentioning

confidence: 99%

Multiple In-Mold Sensors for Quality and Process Control in Injection Molding

Párizs

Török

Ageyeva

et al. 2023

Sensors

View full text Add to dashboard Cite

The simultaneous improvement of injection molding process efficiency and product quality, as required by Industry 4.0, is a complex, non-trivial task that requires a comprehensive approach, which involves a combination of sensoring and information techniques. In this study, we investigated the suitability of in-mold pressure sensors to control the injection molding process in multi-cavity molds. We have conducted several experiments to show how to optimize the clamping force, switchover, or holding time by measuring only pressure in a multi-cavity mold. The results show that the pressure curves and the pressure integral are suitable for determining optimal clamping force. We also proved that in-channel sensors could be effectively used for a pressure-controlled SWOP. In the volume-controlled method, only the sensors in the cavity were capable of correctly detecting the end of the filling. We proposed a method to optimize the holding phase. In this method, we first determined the integration time of the area under the pressure curve and then performed a model fit using the relationship between the pressure integral and product mass. The saturation curve fitted to the pressure data can easily determine the gate freeze-off time from pressure measurements.

show abstract

Optimization process parameters and adaptive quality monitoring injection molding process for materials with different viscosity

Cited by 17 publications

References 17 publications

Injection Barrel/Nozzle/Mold-Cavity Scientific Real-Time Sensing and Molding Quality Monitoring for Different Polymer-Material Processes

Injection Barrel/Nozzle/Mold-Cavity Scientific Real-Time Sensing and Molding Quality Monitoring for Different Polymer-Material Processes

Optimize Injection-Molding Process Parameters and Build an Adaptive Process Control System Based on Nozzle Pressure Profile and Clamping Force

Multiple In-Mold Sensors for Quality and Process Control in Injection Molding

Contact Info

Product

Resources

About