"The ZAero project aims at going beyond the current state of the art concerning intelligent production of large carbon fiber parts. Three major topics are involved: smart inline quality control, closing the feedback loop from individual parts ""as produced"" to mechanical simulation, and implementation of smart decision support for human operators.
Lay-up sensor technology developed within the ZAero project covers large areas of carbon fiber material at a high resolution. The large amount of data that is acquired in this way puts high demands on data processing. The ZAero project developed systems that can handle large and complex data sets. Cutting-edge machine learning methods are deployed to extract the most relevant information from the data. The use of such methods leads to a shift of responsibilities for the human operator. The focus for the human shifts from manual quality inspection of individual processes towards supervision of sensor systems and data analysis.
Mechanical simulation used to be focused on the ""ideal"" manufacturing process of a part. In real production processes, however, deviations of the real part from its design occur. The assessment of such deviations is in many cases very difficult to perform. Subsequently, a very restrictive handling of defects is often implemented in conventional production. Because of strict rules, deviations observed for real parts in production often lead to unnecessary scrapping or re-work. By implementation of real-time mechanical simulation based on the real part as manufactured, the ZAero project enables quick assessment of individual deviations during production. The boundaries of design and production phases are therefore becoming more and more blurred. Although such advanced feedback-loops are limited to specific production domains (i.e. carbon fiber parts in the aerospace industry), future production environments are expected to make much more use of the quick interaction of design and manufacturing. This will enable more iterative production processes in different domains. The ZAero project contributes to the implementation of such flexible production systems.
As a huge amount of data is collected in future production environments, it will be necessary to equip the human operator with the right tools to control and run production systems. As top-level decisions will always be in the hands of a human operator, all relevant data must be prepared and displayed to that operator. Within the ZAero project, a decision support tool was developed and demonstrated at the end of the project. The tool collects information from the manufacturing processes (sensor data), mechanical simulations for individual parts, and logistic simulation of the complete production environment. This global view enables the human operator to meet optimal decisions at the level of the produced part as well as on the level of the whole production chain."
