Self-learning multi-stage quality monitoring procedures for (laser) material processing

Project title Self-learning multi-stage quality monitoring procedures for (laser) material processing (SmQL)
Project duration 01.07.2019 – 30.11.2020

Small and medium-sized companies that supply products in a coordinated process chain (such as the cutting of semi-finished products, followed by laser welding) are confronted with changing tasks and mostly small batch sizes. Due to the increasing product complexity and the increased variety of variants, the effort for the development of production processes in small and medium-sized companies is constantly increasing. The digitalization of process knowledge represents a special challenge for processing small and medium-sized companies in many cases.

Therefore, an expert system is being developed in the "SmQL" research project to support manufacturing companies in the field of laser material processing, process control and process prediction of new products and product variants.

Publications about the project

A product-dependent, individual process development represents a main cost driver in laser material processing. Therefore, the expert system SmQL is being developed in an FQS-funded project, in which process knowledge can be stored in a formalized form and represented in rule form. This is intended to minimize times for setup processes and secure knowledge in the company in the long term.

expert system, industry 4.0, laser materials processing

Sponsor

The IGF project 20419N/2 of the Research Association Quality (FQS) is funded via the German Federation of Industrial Research Associations (AiF) in the programme of Industrial Collective Research (IGF) by the Federal Ministry for Economic Affairs and Energy (BMWi) based on a decision of the German Bundestag.

Partner

Your contact person

Dr.-Ing.

Benjamin Küster

Manager production automation