2020
DOI: 10.1016/j.jmapro.2020.02.011
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An approach to calculate grinding wheel path for complex end mill groove grinding based on an optimization algorithm

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Cited by 25 publications
(6 citation statements)
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“…With regard to the flute grinding of a cylindrical end-mill with variable geometric parameters, Li et al [19] simplified the flute geometry as four characteristic curves and derived the wheel position by making the wheel surface be tangent to the four curves to generate the variable core radius and pitch; Based on cross-section sensitivity analysis, Li et al [20] proposed the iterative algorithm for searching the wheel position to generate the variable core radius, and they presented the two-pass grinding method for the flute with segmented unequal helical angles [21]. With respect to the flute grinding of tapered end-mills, some researchers [22,23] derived the wheel location by the conjugate condition between the wheel surface and the cutting-edge curve and minimized the machining error of the variable core radius iteratively; Wang et al [24] discretized the tapered end-mill into a series of thin cylindrical end-mills and then the problem of wheel path planning is converted to a series of sub-problem of wheel position determination for cylindrical end-mills; Roy et al [25] applied deep learning method to generate the wheel path that can yield the desired variable core radius and flute width, of which the input parameters contains the flute parameters and wheel geometry and the output parameters are the wheel positions and the minimum wheel width.…”
Section: Introductionmentioning
confidence: 99%
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“…With regard to the flute grinding of a cylindrical end-mill with variable geometric parameters, Li et al [19] simplified the flute geometry as four characteristic curves and derived the wheel position by making the wheel surface be tangent to the four curves to generate the variable core radius and pitch; Based on cross-section sensitivity analysis, Li et al [20] proposed the iterative algorithm for searching the wheel position to generate the variable core radius, and they presented the two-pass grinding method for the flute with segmented unequal helical angles [21]. With respect to the flute grinding of tapered end-mills, some researchers [22,23] derived the wheel location by the conjugate condition between the wheel surface and the cutting-edge curve and minimized the machining error of the variable core radius iteratively; Wang et al [24] discretized the tapered end-mill into a series of thin cylindrical end-mills and then the problem of wheel path planning is converted to a series of sub-problem of wheel position determination for cylindrical end-mills; Roy et al [25] applied deep learning method to generate the wheel path that can yield the desired variable core radius and flute width, of which the input parameters contains the flute parameters and wheel geometry and the output parameters are the wheel positions and the minimum wheel width.…”
Section: Introductionmentioning
confidence: 99%
“…Up to now, the problem of wheel path planning in flute grinding of non-cylindrical end-mills still deserves further investigation. The methods presented in the public literature have some limitations such as the inability to control the variable flute width [15-18, 20-22, 23], low efficiency due to the need for cross-section prediction [20][21][22]24], applicability only to wheels with sharp edges [19], and excessive complexity [24,25]. To overcome these limitations, this paper proposes a new method of wheel path planning for flute grinding of non-cylindrical end-mills based on circular arc projection (CAP).…”
Section: Introductionmentioning
confidence: 99%
“…In this work, special attention is study of image processing mechanisms when scanning helical surfaces of end mills manufactured on a multi-axis CNC grinding machine. The main measuring element is the helical flute of the end mill [18,19]. The helical groove has a number of technical difficulties that complicate the processing of an array of images and the quality of transmission of information about the object.…”
Section: Introductionmentioning
confidence: 99%
“…However, the enveloping equation was a transcendental equation which was hard to be solved. To solve the problem, two methods were mainly used: divide-and-conquer method and objective function [2].…”
Section: Introductionmentioning
confidence: 99%
“…Li [2]built a general model is established to calculate the wheel path for complex groove machining based on a mathematical optimization model, which have three constraints and one objective. Considering that the worn wheel would result in groove grinding error without a proper compensation, Liu [18,19] proposed a compensation algorithm of worn wheel by analyzing the boundary contact condition which is influenced by wheel wear.…”
Section: Introductionmentioning
confidence: 99%