2015
DOI: 10.4028/www.scientific.net/amm.794.339
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CNC Tool Path Generation on Multi-Core Processors

Abstract: Tool path generation for CNC machine tools is mainly responsible for quality, accuracy and productivity of the manufacturing process and therefore in the focus of research activities. Many approaches regarding this topic yield to complex algorithms and thus, demand for the availability of sufficient processing performance realizing this algorithms in a CNC real-time environment. For that reason this paper presents an approach on how to use multi-core processors for CNC tool path generation functions. A partiti… Show more

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Cited by 4 publications
(2 citation statements)
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“…The parallelization of the interpreter function including the cutter radius compensation [7], of the look-ahead function [8] and of the interpolation function [9] allows to increase data throughput, to reduce the CNC cycle time, to enhance interpolation algorithms or to consider a larger number of elements in one turn for a better velocity profile. However, up to now a concept for realizing a slope function was missing.…”
Section: Related Workmentioning
confidence: 99%
See 1 more Smart Citation
“…The parallelization of the interpreter function including the cutter radius compensation [7], of the look-ahead function [8] and of the interpolation function [9] allows to increase data throughput, to reduce the CNC cycle time, to enhance interpolation algorithms or to consider a larger number of elements in one turn for a better velocity profile. However, up to now a concept for realizing a slope function was missing.…”
Section: Related Workmentioning
confidence: 99%
“…Following the parallelization concept as proposed in [9] enables to calculate each dimension of the curve concurrently. The subsequent calculation of the arc length integrating the tool path's first derivative is used for parametrizing the curve in a manner that results in a constant velocity profile avoiding acceleration steps and can be executed concurrently, as well.…”
Section: ) Interpolationmentioning
confidence: 99%