Abstract
The increasing requirements of high quality and low cost of products have created an urgent need to implement new technologies in current automated manufacturing environments. Condition monitoring systems of manufacturing processes have been recognised in recent years as one of the essential technologies that provide the competitive advantage in many manufacturing environments. This paper aims to developing an effective sensor fusion model for turning processes for the detection of tool wear. Multi-sensors combined with a novelty detection algorithm are used to detect tool wear and provide diagnostic and prognostic information. A novel approach using dynamic threshold is utilised to improve the accuracy of the novelty detection system. The results found indicate that the suggested approach provides a responsive and effective solution in monitoring tool wear in turning.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
