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AbstractThis paper describes work carried out to develop methods of verifying that machine tools are capable of machining parts to within specification, immediately before carrying out critical material removal operations, and with negligible impact on process times. A review of machine tool calibration and verification technologies identified that current techniques were not suitable due to requirements for significant time and skilled human intervention. A ‘solution toolkit’ is presented consisting of a selection circular tests and artefact probing which are able to rapidly verify the kinematic errors and in some cases also dynamic errors for different types of machine tool, as well as supplementary methods for tool and spindle error detection. A novel artefact probing process is introduced which simplifies data processing so that the process can be readily automated using only the native machine tool controller. Laboratory testing and industrial case studies are described which demonstrate the effectiveness of this approach.
/dk/atira/pure/subjectarea/asjc/2200/2207, Machine tool verification, Machine Tool Verification, Control and Systems Engineering, On-machine probing, /dk/atira/pure/subjectarea/asjc/2200/2209, Machine tool calibration, On-Machine Probing, Industrial and Manufacturing Engineering, Machine Tool Calibration
/dk/atira/pure/subjectarea/asjc/2200/2207, Machine tool verification, Machine Tool Verification, Control and Systems Engineering, On-machine probing, /dk/atira/pure/subjectarea/asjc/2200/2209, Machine tool calibration, On-Machine Probing, Industrial and Manufacturing Engineering, Machine Tool Calibration
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 7 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |