Key Words: AI, Data Analysis, Production Optimization

Technology Processor Solves Highly Complex Optimization Tasks

Digital methods and disruptive manufacturing technologies for a future-proof corporate alignment and economic success: The industry is facing major changes with regard to digitalization and sustainability of its productions. One promising support in this development is artificial intelligence (AI). With AI, highly complex processes can be controlled and monitored. Data analyses provide the basis for increasing productivity and show intelligent objects in decentralized productions the next independent step. However, the road to meaningful and usable data is long. Every company has different data and, more importantly, different data structures. Data must reach the evaluation interface from machine, computer and paper in as high a quality as possible – e.g. correct column, same data type, same notation, etc. But how can this be realized? How should the data be handled?
It is possible to answer these questions using the technology processor developed at the DAP chair for the use case of additive production. Based on the object orienta¬tion known from programming, optimized structures for data storage are built. These generated data structures are machine-readable and can be interpreted by man and machine via metadata. With the help of this collected data, the technology processor solves highly complex multidimensional optimization tasks in the conflicting areas of time, cost and quality. Initial results show for example, that it is possible to automatically select orientations at least as well as humans and, at the same time, to consider production logistics variables such as machine utilization. This allows companies to make detailed and good decisions with a broad data base that enables resource-efficient and competitive AM production.
Andreas Collet, M. Sc.

Andreas Collet, M. Sc.

RWTH Aachen Chair
Digital Additive Production DAP
Campus-Boulevard 73
52074 Aachen