Intelligent monitoring technology to make manufacturing more efficient

Researchers at Nottingham Trent University have developed a new artificial intelligence system which detects problems with cutting tools on manufacturing lines with 100 per cent accuracy.

Researchers at Nottingham Trent University have developed a new artificial intelligence system which detects problems with cutting tools on manufacturing lines with 100% accuracy.

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.

It has been published by the International Journal of Advanced Manufacturing Technology.

Al-Habaibeh, a professor of intelligent engineering systems, said: "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.

"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."

Mr Elgargni added: "As the technology is based on using a simple infrared camera, it should be easy for manufacturers to put it in place without any upheaval in relation to their existing equipment.

"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."

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Intelligent monitoring technology to make manufacturing more efficient

Published on 5 December 2014
  • Category: Business; Research; School of Architecture, Design and the Built Environment; School of Science and Technology

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