IAS with 5 papers at the 57th CIRP CMS 2024 International Conference in Póvoa de Varzim, Portugal
In this conference, our IAS group for IT in automated manufacturing joined industry leaders and explored the future of automation technology in manufacturing. Key areas of our interest for IT, software and AI in manufacturing domain covering key advances in industrial automation, digital twins and more:
Our papers, presented by Frederike Bodenstein, Maurice Artelt and Tobias Eberhart are on:
- Creating behavioral models for libraries of mechatronic components, thereby minimizing the effort of creating behavioral models for mechatronic components.
- Quantitative evaluation of automated behavior model creation for industrial automation, improving reliability in industrial automation applications.
- Automated Configuration of Behavior Models in Digital Twins by using a knowledge graph for automation, enhancing the capabilities of digital twins.
- Hybrid approaches and datasets for predicting useful life: Review of hybrid approaches for predicting the remaining useful life of components.
Our group for IT in manufacturing jointed industry leaders and explored the future of automation technology in manufacturing technology. Key areas of our interest for IT, Software and AI in the manufacturing domain covering key advancements in industrial automation, digital twins, and more:
Our contributions presented by Frederike Bodenstein, Maurice Artelt and Tobias Eberhart are about:
- Efficient Creation of Behavior Models for Libraries of Mechatronic Components
thereby minimizing Minimizing the effort in creating behavior models for mechatronic components, enhancing efficiency in industrial automation. - Quantitative Evaluation of Automated Behavior Model Creation for Industrial Automation
in order to evaluate the effectiveness of automated behavior model creation, improving reliability in industrial automation applications. - Automated Configuration of Behavior Models in Digital Twins
by Using a knowledge-graph to automate behavior model configuration, advancing the capabilities of digital twins. - Hybrid Approaches and Datasets for Remaining Useful Life Prediction:
Reviewing hybrid approaches for predicting the remaining useful life of components, crucial for predictive maintenance.
