Measurement Optimization from CAD Using Artificial Intelligence
Conducting measurements is a daily and time-consuming process that is critical to the manufacturing industry. The most widespread way to carry out the measuring process is using a Coordinate Measuring Machine (CMM). In this paper, a methodology is presented to accelerate the measuring procedure by optimally programming a CMM. The proposed methodology utilizes the information from a computer-aided design (CAD) file and the capabilities of CMMs in order to optimize the measurement process. An improved artificial fish swarm algorithm was modified to meet the requirements of the measurement process and the capabilities of the CMMs. In addition, the ant colony optimization method is applied to extract the optimal sequence of measurements throughout the multiple areas on the component. The resulting optimal path also utilizes the free areas between the different manufactured features of the component. Finally, the resulting path is collision-free, ensuring the integrity and the safety of the CMM. The proposed methodology is verified through real-world experiments.
Authors
- Michel Theodor Mansour
- Gabriel Mansour (ORCID: https://orcid.org/0000-0001-7215-2685)
- Ápostolos Tsagaris (ORCID: https://orcid.org/0000-0002-1671-9330)
- Ilias Chouridis
- Vasileios Papageorgiou (ORCID: https://orcid.org/0009-0006-1804-2198)
Institutions
- International Hellenic University (GR)
- Aristotle University of Thessaloniki (GR)
Publication Details
- Journal
- Metrology
- Published
- 2025-10-29
- DOI
- https://doi.org/10.3390/metrology5040064
- Primary Topic
- Industrial Vision Systems and Defect Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00