Projects per year
Abstract
Despite impressive advances in forming and joining technology, manufacturing industry is still heavily reliant on conventional material removal processes, in which controlled shearing of the work-piece occurs. Such processes typically involve the use of CNC machining centers, which, in principle, are capable of sustained periods of unattended operation. However, the quality of the finished work-piece, in terms of its conformance to dimensional and surface finish requirements, is strongly dependent upon the cutting conditions and, crucially, upon the state of the cutting tools used. A number of cutting tool life management systems are employed but these are usually based on expired life criteria and are of limited applicability. More sophisticated procedures exist, typically based on acoustic emission or spindle torque sensors, for dynamically sensing tool condition during operation. Such systems are potentially more useful but still only indicate that some aspect of the cutting process has changed and usually require human intervention.
The current work, carried out in conjunction with the University of Hull, UK, addresses the need for better control of machining processes with the objective of increased operating efficiency based on reduced scrap, rework and lower tool inventory. The work reported here is primarily concerned with the application of intelligent systems to tool management and is based on the use of laser scattering techniques to detect and characterize edge defects in milling cutters [1].
Such processes involve the use of cutting tools which are significantly harder than the work- piece itself and are usually carried out on CNC machining centers, either as stand alone devices or as integral parts of machining cells and systems. Such systems typically include automated tool and work-piece transport/handling and swarf management and, in principle, are capable of sustained periods of unattended operation in a 'lights out' factory environment.
Investment in cutting tools is not trivial and in a study of a large UK manufacturing company, with a tool inventory value of almost £3 million (AED 17.1M), it became apparent that some tools could be used in a less than optimum condition whilst others were needlessly replaced or refurbished.
The cutting process itself can be overseen by some form of adaptive control and several systems of differing complexity are commercially available. Most systems are relatively unsophisticated in that they control a single machining parameter, usually feed rate, in order to keep spindle torque within predefined constraints. These systems in no way compare with the sensitive control capable of being exercised by a skilled machinist. Furthermore, they are unable to dynamically react to observable changes in the condition of the work-piece as a result of the cutting process.
The current work, carried out in conjunction with the University of Hull, UK, addresses the need for better control of machining processes with the objective of increased operating efficiency based on reduced scrap, rework and lower tool inventory. The work reported here is primarily concerned with the application of intelligent systems to tool management and is based on the use of laser scattering techniques to detect and characterize edge defects in milling cutters [1].
Such processes involve the use of cutting tools which are significantly harder than the work- piece itself and are usually carried out on CNC machining centers, either as stand alone devices or as integral parts of machining cells and systems. Such systems typically include automated tool and work-piece transport/handling and swarf management and, in principle, are capable of sustained periods of unattended operation in a 'lights out' factory environment.
Investment in cutting tools is not trivial and in a study of a large UK manufacturing company, with a tool inventory value of almost £3 million (AED 17.1M), it became apparent that some tools could be used in a less than optimum condition whilst others were needlessly replaced or refurbished.
The cutting process itself can be overseen by some form of adaptive control and several systems of differing complexity are commercially available. Most systems are relatively unsophisticated in that they control a single machining parameter, usually feed rate, in order to keep spindle torque within predefined constraints. These systems in no way compare with the sensitive control capable of being exercised by a skilled machinist. Furthermore, they are unable to dynamically react to observable changes in the condition of the work-piece as a result of the cutting process.
Original language | English |
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Number of pages | 4 |
Publication status | Published - Apr 2003 |
Event | 4th Annual UAE University Research Conference - UAE University, Al Ain, United Arab Emirates Duration: 27 Apr 2004 → 29 Apr 2004 |
Conference
Conference | 4th Annual UAE University Research Conference |
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Country/Territory | United Arab Emirates |
City | Al Ain |
Period | 27/04/04 → 29/04/04 |
ASJC Scopus subject areas
- Industrial and Manufacturing Engineering
- Mechanical Engineering
Fingerprint
Dive into the research topics of 'Advances in Tool Management Systems'. Together they form a unique fingerprint.Projects
- 1 Finished
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Intelligent Integrated Tool Management and Handling System
Randeree, K.
1/01/90 → 31/12/92
Project: Project at former HEI
File
Research output
- 3 Conference proceeding
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Automatic Defect Recognition in Cutting Tools
James, R. D., Leishman, I. R. & Randeree, K., Jun 1999, Proceedings of the 32nd International Symposium on Automotive Technology and Automation: Advances in Automotive and Transportation Technology and Practice for the 21st Century. Croydon, England: Automotive Automation Ltd, p. 261-268 8 p.Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding › peer-review
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Laser Scanning Techniques for Defect Recognition on Cutting Tools
Dalgliesh, G., James, R. D. & Randeree, K., Jun 1998, 31st International Symposium on Automotive Technology and Automation. Automotive Automation Ltd, p. 189-196 8 p.Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding › peer-review
File -
Laser Scanning Techniques for Automated Inspection
Dalgliesh, G., James, R. D., Randeree, K. & Swift, K. G., Jun 1997, 30th International Symposium on Automotive Technology and Automation: ISATA ‘97: Rapid Prototyping/Laser Applications in the Automotive Industries. Croydon: Automotive Automation Ltd, p. 423-430 8 p.Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding › peer-review