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With the trend of increasing sensors implementation in production systems and comprehensive networking, essential preconditions are becoming required to be established for the successful application of data-driven methods of equipment monitoring, process optimization, and other relevant automation tasks. As a protocol, these tasks should be performed by engineers. Engineers usually do not have enough experience with data mining or machine learning techniques and are often skeptical about the world of artificial intelligence (AI). Quality assurance of AI results and transparency throughout the IT chain are essential for the acceptance and low-risk dissemination of AI applications in production and automation technology. This article presents a conceptual method of the stepwise and level-wise control and improvement of data quality as one of the most important sources of AI failures. The appropriate process model (V-model for quality assurance) forms the basis for this.

Increasing global demand for composites continues to be driven by the aerospace industry. However, expensive raw material and the complexity of manufacturing process increases the risk level in composite technology. Considering the complexities of composite manufacturing, our paper describes a data management application in composite manufacturing at an aerospace manufacturer. The scope of this manufacturing data management application is from the raw material issuance from warehouse to the painted final composite product. After a description of the application, we will discuss potential problems and possible solutions and improvements of the data management in composite manufacturing in the aerospace industry.

The paper wants to illustrate a new approach for modelling and analysing innovative technological process chains aiming at the determination of cause-effect relations between material properties and manufacturing conditions concerning the required component quality. The intention is to assist the domain specific experts at their research and development of novel technologies. A supporting software tool is under development. Using the example of the process chain of the manufacturing of a hybrid yarn textile thermoplastic composite component the application of the approach and the test of the software tool was performed for the modelling of the process chain and for the analysing of a selected process step. Therefrom requirements were derived for the further development of the methods and the software tool.

International audience; Engineering design approach are curently CAD-centred design process. Manufacturing information is selected and assessed very late in the design process and above all as a reactive task instead of being proactive to lead the design choices. DFM appraoches are therefore assesment methods that compare several design alternatives and not real design approaches at all. Main added value of this research work concerns the use of a product-process interface model to jointly manage both the product and the manufacturing data in a proactive DFM way. The DFM synthesis approach and the interface model are presented via the description of the DFM software platform.