Bioinspired intelligent SLM cell

Abstract

Selective Laser Melting (SLM) is an additive manufacturing (AM) process the requires the control of a huge number of parameters to gain reproducible, high quality parts. This is typical for all types of AM technologies. Modelling attempts of such processes are either simple and crude or drastically overstrain the time budget and still do not take into account all influences that affect part quality. A possible way out of this dilemma is a bioinspired intelligent SLM machine. Thereby, basic approaches and methods of biological systems are transferred and adapted for the SLM machine and process. Essential properties of such a system are intense sensing capabilities essentially based on optical means, coupled with a memory based expert system, learning abilities and reasoning using associative connection of information. Mandatory are also communication with other entities and last and most important the implanted drive to optimize and enhance the result of all actions. Different artificial intelligence methods for different tasks within the SLM process are foreseen to cope with individual steps along the whole process chain. For the design of an expert system a proper data structuring according to influence groups must be achieved. Furthermore it is important to utilize suitable modelling approaches to reduce teaching and learning efforts.