Quality prediction result

The Quality Prediction result is used to estimate the quality of the mechanical properties and appearance of the part. This result is derived from the pressure, temperature, and other results.

good fill pattern

Fill confidence

The colors displayed in the Quality prediction result indicate the following:

fill confidence

  1. Will have high quality
  2. May have quality problems
  3. Will definitely have quality problems.
Note: The Quality prediction result is not available if there is a short shot. Fix the cause of the short shot and rerun the study, to view this result.

Things to look for

Colors other than green indicate that you may have problems with the quality of molded part. Note the location of these other colors - if yellow\orange areas occur where mechanical strength in not needed, or where the quality of the surface appearance is unimportant, they may be of no concern. As the percentages of yellow/orange and red increase, the part quality decreases.

Using this result

A good quality part is defined by whether or not it meets the design specifications for mechanical strength and surface appearance. When analyzing this result to determine whether a good quality part can be molded, consider which colors are visible and how much of each color appears. You should also look at the Fill Confidence result to see how likely it is that the part will fill.

If the part is mostly green, with some small yellow/orange areas, it may be acceptable but you should look carefully at other results to see where and why the area is not green.

If there are yellow/orange or red areas, it may be that the temperature in those areas was too low, or too high, as the plastic flowed through them. The temperature at the flow front is one factor used to determine the confidence that the cavity will fill.

Problems caused by temperature:

Next steps

There are a number of ways to improve the quality prediction result, but it is important to remember that as you make changes, there will be other consequences. To improve the quality prediction result when temperature is the cause of problem areas: