Abstract
Process understanding and process monitoring are of great importance in production in order to control processes and guarantee a high quality. Demanding customer requirements with an increasing number of variants pose an even greater challenge to the quality of the processes, as this must be maintained at the highest level even in the event of process changes. In addition, new regulations and standards require process data to be recorded and stored, especially in manufacturing environments for medical and safety equipment (e.g., surgical instruments, camera systems in the automotive industry). Continuous variations in production processes and changes to products and the production system mean that the planning effort required to implement process monitoring has become vast. This is where automated planning and decision support systems become important. They are able to manage the complexity arising from alternative solutions and present suitable alternatives to the user. This article deals with the computer-aided identification of assembly features, which influence process monitoring and the generation of production system-neutral tasks for process monitoring. Computer-aided feature recognition methods were used to derive features from three-dimensional models. Furthermore, a skill-based approach was used to formulate tasks for process monitoring. This publication thus aims at the automated and product-specific generation of processes for process monitoring.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.