EXplainable AI for automated Production Systems

EXplainable AI for automated Production Systems

Automated production systems (aPS) are an essential building block for global industry. Holistic solution portfolios that intelligently control and monitor production processes and enable continuous improvements are essential for market success. The XAPS (EXplainable AI for automated Production Systems) project will make production processes more intelligent using explainable AI methods and thus strengthen both the suppliers of aPS solutions and the German industry that operates aPS. 

Automated production systems (aPS) arrange resources in complex processes. These resources process intermediate products and check their quality. Depending on the test result, an intermediate product is passed on in the process or rejected for manual testing and reworking. Although the individual steps are monitored, the interdependencies between material, processing steps, operating resources, operating equipment maintenance and test results are so complex, that even if the intermediate products are processed correctly, an end product may lack the required quality, which leads to expensive rework or rejects. The goal of the project is to discover complex dependencies between errors and processing at an early stage using machine learning and also to explain them using AI in such a way that the operator can optimize his aPS efficiently and effectively.  

Operating Time: 01/2020 - 12/2021

Source of Funding: BMBF - KMU Innovativ


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