E-Manufacturing: Business Paradigms And Supporting Technologies: 18th International Conference On Cad/Cam, Robotics, And Factories Of The Future (Cars & Fof), July 2004

• Main Authors: Shetty, Devdas, Tamaldin, Noreffendy, Campana, Claudio, Kondo, Jun
• Format: Book
• Language: English
• Published: Kluwer Academic Publishers Norwell, MA, USA ©2004 2004
• Subjects: TJ Mechanical engineering and machinery
• Online Access: http://eprints.utem.edu.my/id/eprint/5048/1/Utilizing_neural_network_for_online_inspection.docx; http://eprints.utem.edu.my/id/eprint/5048/; https://encrypted.google.com/books?id=ZpuFWqWU2-gC&printsec=frontcover&source=gbs_ViewAPI#v=onepage&q&f=false

Utilizing Neural Network For Mechatronics, On-Line Inspection And Process Control. A trend in the area of automated manufacturing is the incorporation of artificial intelligence methods (example, neural network) to enhance the on-line inspection and process control. Intelligent on-line inspection and process control in modern manufacturing system have significant potential in improving production performance and quality of its product. Our research paper presents an approach for on-line inspection methodology that is applied to different areas such as metrology,precision measurement, mechatronics and bio-film thickness evaluation. In the case of metrology, the on-line measurement technique was applied for surface roughness measurement on the production floor. In the case of Mechatronics, the neural network technique was applied to the damped sensing and control system. finally, an example of bio-film thickness evaluation using neural network is presented.