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 .
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.
|Conference||4th Annual UAE University Research Conference|
|Country||United Arab Emirates|
|Period||27/04/04 → 29/04/04|
- Industrial and Manufacturing Engineering
- Mechanical Engineering