Cookie settings

We use several types of cookies on this website to provide you with an optimal online experience, to increase the user-friendliness of our portal and to constantly improve our communication with you. You can decide which categories you want to allow and which you do not want to allow (see "Custom settings" for more information).
Name Usage Duration
privacylayerStatus Agreement Cookie hint1 year
Name Usage Duration
_gaGoogle Analytics2 years
_gidGoogle Analytics1 day
_gatGoogle Analytics1 minute
_galiGoogle Analytics30 seconds

Q-DAS | COVID-19 Information

REDUCING UNCERTAINTY

REDUCING UNCERTAINTY

Suitable measurement processes help you reduce uncertainties

15 October 2012: Edgar Dietrich

In industrial production, the applied measurement processes evaluate and assess the quality of manufacturing and production facilities as well as the produced parts, components and products. The results gained by the measurement processes and the statistical evaluation always include different uncertainties.

Quality evaluation

Depending on the manufacturing or production process, selected quality characteristics are inspected in or after the different process steps. You may conduct a 100% inspection or an inspection based on a sample. You evaluate the manufacturing or production quality graphically by using various visualizations or numerically by calculating capability indices. The recorded measured values are evaluated statistically and the required statistics are calculated. These data are processed numerically and, depending on the respective application and the responsible user group, graphically, too. Only by succeeding in communicating the results quickly specifically to the respective task and user and in making them easily accessible, these results are applied in order to evaluate and assess processes and certain issues. In this case they contribute to the quality evaluation.

Uncertainty

The results or issues include, amongst others, uncertainties as a result of:

  • measurement and test processes
  • the application of statistical procedures
  • erroneous data recording, transfer and management
  • erroneous communication of results

You may solve the problems caused by the last two sources of error with organizational measures and IT support, e.g. by permanently checking the plausibility of data where relevant. The application of Q-DAS products helps you to describe processes by means of validated statistical procedures specifying the confidence intervals for the single statistics...