Details of Grant 

EPSRC Reference:	GR/R13401/01
Title:	Novel Metrology-Based Control Algorithms For Precision Manufacture (CAPM)
Principal Investigator:	Ford, Professor DG
Other Investigators:	Myers, Professor A
Researcher Co-Investigators:
Project Partners:	Cincinnati Milacron Ltd Kistler Instruments Ltd Metrology Direct Ltd Renishaw Siemens
Department:	Sch of Computing and Engineering
Organisation:	University of Huddersfield
Scheme:	Standard Research (Pre-FEC)
Starts:	01 March 2001	Ends:	31 May 2004	Value (£):	342,017
EPSRC Research Topic Classifications:	Manufacturing Machine & Plant
EPSRC Industrial Sector Classifications:	Manufacturing
Related Grants:
Panel History:
Summary on Grant Application Form
This proposal is to quantify and optimise the performance of a CNC machine tool under cutting conditions, by investigating those parameters that affect dimension, form and surface finish tolerances. The investigation will also determine correction algorithms on and off-line and produce passive/active condition monitoring strategies and practices. Its novelty lies in the combining of knowledge of three specialised research groups whose activities include 'state of the art' control of those parameters affecting dimensional accuracy, form, surface finish and integrity. This will be the first known attempt to control all those parameters, which will allow a component to be produced automatically approaching the tolerance restrictions imposed by the machine tool axis repeatability limits and its environment. The machine dimensional accuracy is affected by static, dynamic and thermal stiffness of the machine tool structure. Form considerations are the result of the control system dynamic performance, which in itself is a function of the programming algorithms, drive performance, machine cutting process. Surface finish is functions of toolwear, vibration and isolated events. This proposal, which carries a significant element of risk, has only been considered to be feasible because of the significant progress of 3D surface characterisation, and the respective teams standing in error minimisation practices. Our industrial partners represent machine tool builders, equipment suppliers and end users involved in the need for improvement with their high performance applications for milling and turning operations.
Key Findings
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Potential use in non-academic contexts
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Impacts
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Project URL:
Further Information:
Organisation Website:	http://www.hud.ac.uk