A study led by Professor Amin Al-Habaibeh - of the School of Architecture, Design and the Built Environment - found that by combining infrared cameras and artificial neural networks it was possible to consistently detect when cutting tools were broken or missing.
The technology – which does not require any contact with the manufacturing machinery – could provide live feedback via computer to alert operators in order to help prevent catastrophic tool damage.
The study was supervised by Professor Al-Habaibeh and Professor Ahmad Lotfi, of the university's School of Science and Technology and developed by PhD researcher, Milad Elgargni. A description of the work is published in The International Journal of Advanced Manufacturing Technology.
"This could be a very efficient method for manufacturers to maintain the productivity of their manufacturing lines and the quality of their products in an automated way," says Professor Al-Habaibeh. "The real advantage is that the system can detect problems in real time, which is difficult to achieve by common methods. Because the artificial intelligence system can learn, it's possible for it to monitor various cutting tools, making it flexible for consumers to use."
"As the technology is based on using a simple infra red camera, it should be easy for manufacturers to put it in place without any upheaval in relation to their existing equipment," Mr Elgargni adds.
"We believe, also, that it would be possible to develop the technology further to help detect gradual tool wear, which would help provide operators with increased awareness of the condition of the tools."