- Research Project
ACIMO: Analyse acoustique intelligente de la machine
A method for monitoring the condition of tools in the manufacturing process is being developed in the Innosuisse ACIMO project. This aims to reduce the process interruptions and overall costs per manufactured item.
- Lead school(s) School of Engineering and Computer Science
- Institute Institute for Intelligent Industrial Systems
- Research unit I3S / Prozessoptimierung in der Fertigung
- Funding organisation Innosuisse
- Duration (planned) 13.06.2022 - 13.03.2024
- Project management Prof. Dr. Axel Fuerst
- Head of project Simon Walther
Severin Nathanael Herren
Association de Recherche Communautaire des moyens de production Microtechniques (ARCM)
Haute Ecole Arc Ingénierie
- Keywords Condition Monitoring, Hybrid Machine Learning, Smart Sensors, Tool Wear
During the process of manufacturing components, tools undergo wear and tear depending on the level of usage and environmental conditions. Heavy wear to tools may result in components having inadequate surface properties and inaccurate dimensions. Heavy wear and its consequences arise if tools are not changed soon enough. Conversely, changing tools too early incurs higher tooling costs and means more process interruptions.
Course of action
The ACIMO concept aims to take measurements of the tools and to read the process parameters during the manufacturing process. Proven quality criteria of components, such as surface quality and dimensional accuracy, provide an indication of the wear and tear of tools.
The measurement data acquired will be used to create a model through machine learning which can determine a tool’s level of wear.
BFH is responsible for developing the measurement strategy and the machine learning model. A condition monitoring model will be created using the data produced, the physical knowledge available, the process data and the quality characteristics.
The project is led by the Haute Ecole Arc Ingénierie.