How to Determine if Sensor Position Optimization is Possible

The effectiveness of sensor position optimization depends on confirming the compliance with process stability and the accuracy of temperature measurement data. This is accomplished by verifying that the sensor is not impacted by frictional heat by comparing temperature measurements with real molding outcomes.

 

1. Crucial Indicators of Judgment

The phenomenon

An explanation

A steady temperature display for the hot runner without any unusual leaps

The temperature curve that has been optimized is smooth, preventing sudden spikes brought on by excessive shear.

Reliable product quality in both high- and low-speed scenarios

Accurate temperature control response is shown by the absence of flaws like flash or short shots during high-speed injection molding.

Melte measured a temperature difference of < ±5°C from the displayed value.

directly confirms the accuracy of temperature measurements; higher optimization outcomes are indicated by lesser mistakes.

uniform multi-cavity filling without over-holding pressure or brief injections in a single cavity.

shows representative and symmetrical sensor locations in every channel.

Practical Case: Following the optimization of an automobile connection mold, the short shot rate went back to zero and the disparity between the measured and displayed melt temperature dropped from +22°C to +4°C.

 

2. Methods of On-Site Verification

Infrared Thermal Imager Scanning: As soon as the mold is opened, scan the hot runner surface to make sure the temperature distribution is uniform and there are no "hot spots" in places like flow dividers and nozzle tips.

TUS Furnace Temperature Uniformity Test: Set up several temperature measurement locations in accordance with AMS 2750 criteria to ensure representativeness by confirming that the temperature deviation surrounding the sensors is ≤±2°C.

Measuring and Comparing Melt Temperature: Compare the hot runner reading with the actual melt temperature at the output. More optimization is needed if the difference is more than 5°C.

Note: To guaranty long-term stability, at least three rounds of continuous production verification should be carried out following the first optimization.

 

3. Suggestions for Continuous Monitoring

Create a sensor location file and record the parameters for depth, angle, and distance;

Repeat melt temperature measurements and TUS testing on a regular basis (e.g., quarterly);

For dynamic management, include temperature variations and fault rates in the process monitoring dashboard.

Safety principle: We can only verify that the optimization is in place by combining "data comparison + multi-method verification + continuous tracking".