The main objective of all processes to manufacture high-tech products is compliance with the specified ranges of permissible variation. For this purpose, all data must be recorded that might provide some evidence of status changes anywhere along the process chain. Sensors in machinery and equipment can provide valuable clues as to whether or not the actual values will fall into the tolerance range.
All data from the sensors and the production system will be stored individually for each product, creating a digital twin that retains a full production history including project data and order specifications. Identification systems allow this twin to be assigned to the individual component, making it available for every downstream process step. The extended product data models provide relevant, context-specific data from the manufacturing history for further analyses, accelerating process development and process optimization in the production of prototypes as well as large series.
A specific time and place must be recorded for each set of sensor data about default process parameters, the temperature in the hall or machine vibrations. This still provides technological challenges, but the causes of certain defects can be revealed only if the process can be fully traced back.