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

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## Abstract

**:**

## 1. Introduction

## 2. Machines, Materials, and Methods

## 3. Results

#### 3.1. Controlling the Clamping Stage

^{−8}, which corresponds to a strong correlation between the two values and a low probability of no significant linear correlation between the two values.

#### 3.2. Controlling the Filling Phase

#### 3.3. Manual Switchover Method with Pressure Measurement

^{3}of melt was injected, cavity 08 was already filled, while cavity 07 was almost filled. The sensors at tertiary channels cannot show the difference between the cavities connected to that channel (Figure 8a), which is a great disadvantage. The sensors in front of the gate can separate the individual cavities due to their position, but they cannot show the filling of the cavities either (Figure 8b). In contrast, the pressure data obtained from the sensors in the cavities clearly show that the melt flows differently in the individual cavities. The maximum pressure measured at the end of the cavity sensor shows this filling phenomenon the best because the maximum pressure in cavity 08 is already greater than zero when the volume of the injected melt is 22 cm

^{3}(Figure 8d). The results of the post-gate sensors show a similar trend (Figure 8c). Figure 8c,d show that cavities 02, 05, and 06 are filled next due to the almost 100 bar maximum pressure jump. Cavities 01, 03, and 04 were the last to be filled when 24.5 cm

^{3}of melt was injected into the mold. The sensors in the channel can show the filling of these last cavities as the slope of the maximum pressure function changes significantly from here. However, the in-cavity sensors demonstrate higher accuracy in this case. Therefore, in-cavity sensors are much more recommended for this method, while their use was less promising in the previous method.

#### 3.4. Mold Filling Imbalance Detection with a Pressure Sensor

#### 3.5. Controlling the Holding Phase

## 4. Conclusions

- We investigated several methods of using pressure sensors to control multi-cavity molds. One such method was to optimize the clamping force. The results show that the pressure curves and the pressure integral are suitable for determining the optimal clamping force. This method can save time and energy, as we can use the information from the pressure curves to find the optimal clamping force faster, and its value may be lower than the maximum clamping force of the machine.
- Subsequently, we compared two methods for controlling filling as a function of in-mold sensor location. The results showed that the use of in-channel sensors is recommended for a pressure-controlled SWOP. In contrast, in the volume-controlled hybrid method, the sensors in the cavity were the only sensors capable of correctly detecting the end of filling.
- The dependence of mold filling imbalance on injection rate and melt temperature was examined with in-mold sensors. Our results show that the imbalance increases with the injection rate, but this effect can be reduced by increasing the temperature of the melt.
- In the last experiment, we optimized the holding phase. 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 gate freeze-off time from pressure measurements. There was little difference between the gate freeze-off times calculated from mass measurements and pressure measurements.

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

## Appendix A

Source of Variation | DoF | Sum of Squares | Mean Square | F-Statistic | p-Value |
---|---|---|---|---|---|

Melt temperature (T_{m}) | 2 | 0.0269 | 0.0135 | 203.4625 | 8.54 × 10^{−36} |

Injection velocity (v_{inj}) | 1 | 0.0100 | 0.0100 | 151.9124 | 1.04 × 10^{−21} |

T_{m} × v_{inj} | 2 | 0.0014 | 0.0007 | 10.8474 | 5.50 × 10^{−5} |

Error | 99 | 0.0065 | 0.0001 | ||

Total | 104 |

Source of Variation | DoF | Sum of Squares | Mean Square | F-Statistic | p-Value |
---|---|---|---|---|---|

Melt temperature (T_{m}) | 2 | 0.0256 | 0.0128 | 146.7638 | 2.44 × 10^{−30} |

Injection velocity (v_{inj}) | 1 | 0.0109 | 0.0109 | 125.0406 | 2.95 × 10^{−19} |

T_{m} × v_{inj} | 2 | 0.0018 | 0.0009 | 10.4503 | 7.63 × 10^{−5} |

Error | 99 | 0.0086 | 0.0001 | ||

Total | 104 |

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**Figure 2.**In-mold pressure change as a function of time at different clamping forces (cavity 04, post-gate sensor).

**Figure 3.**The change of the pressure integral (

**a**) and part weight (

**b**) of the inner (07 and 08) and outer (01 and 02) cavities due to a change in the clamping force.

**Figure 4.**The adjusted p-values (from the Tukey–Kramer post hoc test) for each clamping force pair for the pressure integrals (below the diagonal) and part weights values (above the diagonal).

**Figure 5.**The effect of sensor location on switchover pressure (sensors from the flow path to cavity 02).

**Figure 6.**The effect of the switchover pressure threshold on in-mold pressure, measured with a sensor in a runner (tertiary channel sensor to cavity 02).

**Figure 8.**Maximum pressure for each cavity based on: (

**a**) tertiary channel sensors; (

**b**) pre-gate sensors; (

**c**) post-gate sensors; (

**d**) end-of-cavity sensors.

**Figure 9.**Melt arrival times to the end-of-cavity sensors: (

**a**) v

_{inj}= 10 cm

^{3}/s and for (

**b**) v

_{inj}=110 cm

^{3}/s (T

_{melt}= 215 °C).

**Figure 10.**Effect of melt temperature and injection rate on the ratio of the longest and shortest melt arrival times: (

**a**) cavity 03–07; (

**b**) cavity 04–08.

**Figure 11.**In-mold pressure curves as a function of time and holding time measured with a: (

**a**) pre-gate sensor; (

**b**) post-gate sensor (cavity 01).

**Figure 12.**The changing of the correlation coefficients and their 95% confidence interval between the pressure integral and mass based on integration time and the adjusted probabilities for each correlation (cavity 08).

**Figure 13.**Relationship between the pressure integral and sample mass (R = 0.973 with a significance level of 0.05).

**Figure 14.**Mass and pressure integral as a function of holding time (cavity no. 1, post-gate sensor, p

_{hold}= 600 bar, integration time 3 s).

**Figure 15.**Predicting gate freeze-off time from the saturation curve from the measurement of mass and pressure.

**Table 1.**Recommended processing parameters by the manufacturer (Terluran GP-35 ABS) and the mechanical properties of the material.

Processing Parameter | Values |
---|---|

Drying temperature and time | 80 °C for 4 h |

Recommended melt temperature range | 220–280 °C |

Recommended mold temperature range | 30–60 °C |

Mechanical Properties | Values |

Tensile stress at yield at 23 °C | 44 MPa |

Tensile strain at yield at 23 °C | 2.4% |

Charpy notched impact strength at 23 °C | 19 kJ/m^{2} |

Values | |||||
---|---|---|---|---|---|

Process parameter | Exp. 01 | Exp. 02 | Exp. 03 | Exp. 04 | Exp. 05 |

Clamping force, kN | - | 700 | 700 | 700 | 700 |

Injection rate, cm^{3}/s | 50 | 50 | 50 | - | 50 |

Switchover control | Volume | Pressure | Volume | Volume | Volume |

Switchover point, cm^{3} | 7 | - | - | 6 | 7 |

Screw rotation speed, m/min | 15 | 15 | 15 | 15 | 15 |

Back pressure, bar | 40 | 40 | 40 | 40 | 40 |

Decompression, cm^{3} | 5 | 5 | 5 | 5 | 5 |

Dose volume, cm^{3} | 26 | 26 | 26 | 26 | 26 |

Holding pressure, bar | 600 | 0 | 0 | 600 | 600 |

Holding time, s | 2 | 0 | 0 | 2 | - |

Cooling time, s | 15 | 18 | 18 | 15 | 18 |

Melt temperature, °C | 225 | 225 | 225 | - | 225 |

Mold temperature, °C | 40 | 40 | 40 | 40 | 40 |

Experiment Number | Changed Setting | Setting Levels |
---|---|---|

01—clamping force | Clamping force, kN | 300/325/350/400/500/600/700/800/900/1000 |

02—pressure controlled SWOP | Switchover pressure limit on sensors, bar | 50/100/125/150 |

03—hybrid SWOP | Switch over volume, cm^{3} | 9.0/8.0/7.0/6.8/6.6/6.4/6.2 |

04—imbalance | Melt temperature, °C | 215/225/235 |

injection rate, cm^{3}/s | 10/20/35/50/65/80/110 | |

05—gate freeze-off | Holding time, s | 0.00/0.25/0.50/0.75/1.00/1.25/1.50/ 1.75/2.00/2.25/2.50/2.75/3.00 |

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**MDPI and ACS Style**

Párizs, R.D.; Török, D.; Ageyeva, T.; Kovács, J.G.
Multiple In-Mold Sensors for Quality and Process Control in Injection Molding. *Sensors* **2023**, *23*, 1735.
https://doi.org/10.3390/s23031735

**AMA Style**

Párizs RD, Török D, Ageyeva T, Kovács JG.
Multiple In-Mold Sensors for Quality and Process Control in Injection Molding. *Sensors*. 2023; 23(3):1735.
https://doi.org/10.3390/s23031735

**Chicago/Turabian Style**

Párizs, Richárd Dominik, Dániel Török, Tatyana Ageyeva, and József Gábor Kovács.
2023. "Multiple In-Mold Sensors for Quality and Process Control in Injection Molding" *Sensors* 23, no. 3: 1735.
https://doi.org/10.3390/s23031735