Hybrid Artificial Intelligence System for the Design of Highly-Automated Production Systems

The automated design of production systems is a young field of research which has not been widely explored by industry nor research in recent decades. Currently, the effort spent in production system design is increasing significantly in automotive industry due to the number of product variants and product complexity. Intelligent methods can support engineers in repetitive tasks and give them more opportunity to focus on work which requires their core competencies. This paper presents a novel artificial intelligence methodology that automatically generates initial production system configurations based on real industrial scenarios in the automotive field of body-in-white production. The hybrid methodology reacts flexibly against data sets of different content and has been implemented in a software prototype

Neural Network Hyperparameter Optimization for the Assisted Selection of Assembly Equipment

The design of assembly systems has been mainly a manual task including activities such as gathering and analyzing product data, deriving the production process and assigning suitable manufacturing resources. Especially in the early phases of assembly system design in automotive industry, the complexity reaches a substantial level, caused by the increasing number of product variants and the decreased time to market. In order to mitigate the arising challenges, researchers are continuously developing novel methods to support the design of assembly systems. This paper presents an artificial intelligence system for assisting production engineers in the selection of suitable equipment for highly automated assembly systems

ModelTracer: User-friendly traceability for the development of mechatronic products

The development of complex mechatronic systems demands an integration of models throughout the virtual product development process. Systems engineering is an approach for enabling the development of successful interdisciplinary products. Traceability, one of the most important aspects of systems engineering, is a method for explicit documentation of logical relationships between development artifacts. In this paper we present a prototype traceability tool, ModelTracer, which aims to reduce the cognitive effort for the creation and maintenance of traceability models in systems engineering