- Ernst Kussul2,
- Tatiana Baidyk2,
- Felipe Lara-Rosano2,
- Oleksandr Makeyev3,
- Anabel Martin2 &
- …
- Donald Wunsch4
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Abstract
Some of the artificial intelligence (AI) methods could be used to improve the performance of automation systems in manufacturing processes. However, the application of these methods in the industry is not widespread because of the high cost of the experiments with the AI systems applied to the conventional manufacturing systems. To reduce the cost of such experiments, we have developed a special micromechanical equipment, similar to conventional mechanical equipment, but of a lot smaller overall sizes and therefore of lower cost. This equipment can be used for evaluation of different AI methods in an easy and inexpensive way. The methods that show good results can be transferred to the industry through appropriate scaling. This paper contains brief description of low cost microequipment prototypes and some AI methods that can be evaluated with mentioned prototypes.
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Authors and Affiliations
Center of Applied Sciences and Technological Development, National Autonomous University of Mexico, Cd. Universitaria, Circuito Exterior s/n, 04510, Coyoacán, México, D.F., Mexico
Ernst Kussul, Tatiana Baidyk, Felipe Lara-Rosano & Anabel Martin
Dept. of Electrical and Computer Engineering, Clarkson University, 5720, Potsdam, NY, 136992, USA
Oleksandr Makeyev
Applied Computational Intelligence Lab, Dept. of Electrical and Computer Engineering, University of Missouri-Rolla, 1870 Miner Circle, Rolla, MO, 65409, USA
Donald Wunsch
- Ernst Kussul
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- Tatiana Baidyk
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- Felipe Lara-Rosano
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- Oleksandr Makeyev
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- Anabel Martin
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- Donald Wunsch
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University of Technology, Sydney, Australia
John Debenham
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Kussul, E., Baidyk, T., Lara-Rosano, F., Makeyev, O., Martin, A., Wunsch, D. (2006). Micromechanics as a Testbed for Artificial Intelligence Methods Evaluation. In: Debenham, J. (eds) Professional Practice in Artificial Intelligence. IFIP WCC TC12 2006. IFIP International Federation for Information Processing, vol 218. Springer, Boston, MA . https://doi.org/10.1007/978-0-387-34749-3_29
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