Shape-adaptive CNC milling for complex contours on deformed thin-walled revolution surface parts

Xu, Jizheng; Xu, Longkun; Li, Yifei; Sun, Yuwen

doi:10.1016/j.jmapro.2020.10.001

Cited by 16 publications

(3 citation statements)

References 23 publications

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“…By means of the three-point estimate method [24], the input variables with a high importance to the failure probability of machining distortion are obtained. Firstly, three estimate points (Xi (1) , Xi (2) , and Xi (3) ) are extracted from the input variables Xi; Secondly, standard locations and weights of three estimate points can be obtained by solving the following Eqs. ( 4)-( 9); Thirdly, the estimate values of δi are computed using Eq.…”

Section: Definition Of the Failure Probability Of Machining Distortionmentioning

confidence: 99%

“…where Xi (1) , Xi (2) , and Xi (3) represent estimate points of Xi; and 3 i X l ( ) are the standard locations of the three estimate points;…”

Section: Definition Of the Failure Probability Of Machining Distortionmentioning

confidence: 99%

“…Uncertainties occurring in the machining process of thin-walled parts will lead to uncertain performance, such as dimensional accuracy and surface finish quality. Some researchers proposed that precise settings for machining parameters [1,2], cutter path [3] and workpiece stiffness [4] are beneficial to obtain the desired performance. To evaluate the effects of uncertain factors on the machining results, uncertainty analysis has been successfully and widely applied in engineering.…”

Section: Introductionmentioning

confidence: 99%

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Influence of Uncertain Parameters on Machining Distortion of Thin-walled Parts

Qin²,

Tang³

et al. 2022

Preprint

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Thin-walled parts refer to lightweight structural parts comprised of thin plates and stiffeners. During the machining process of thin-walled parts, machining distortion often occurs due to uncertain factors such as varying stiffness, cutting force, cutting temperature, residual stress and other factors. This paper studied the minimization of the failure probability of machining distortion by controlling the uncertainties of inputs. For this, a fuzzy inference model for the machining system was proposed to determine the effects of uncertain factors on the machining distortion errors, which was composed of rule frame and result frame. In the rule frame, machining parameters, outline size, and wall thickness were used as inputs. In the result frame, linear stiffness, cutter path, as well as cutting force were taken as the input parameters. The values of machining distortion were the output, taken into a threshold function. Comprehensive matching was defined to measure the importance of uncertain inputs to outputs. Machining distortion will exceed the specification (failure) with the increase in comprehensive matching. Therefore, the comprehensive matching index evaluates the effects of the uncertainties on the machining distortion and quantify the effects of given uncertain parameters. Two engineering examples were employed to illustrate the accuracy and efficiency of the proposed approach. It revealed that the comprehensive matching of cutting force to the failure probability of machining distortion was the maximum, 0.040, which was 12 to 13 times greater than that of linear stiffness or cutter path.

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Section: Definition Of the Failure Probability Of Machining Distortionmentioning

confidence: 99%

“…where Xi (1) , Xi (2) , and Xi (3) represent estimate points of Xi; and 3 i X l ( ) are the standard locations of the three estimate points;…”

Section: Definition Of the Failure Probability Of Machining Distortionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Influence of Uncertain Parameters on Machining Distortion of Thin-walled Parts

Qin²,

Tang³

et al. 2022

Preprint

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Analysis and compensation of surface flatness of thin-walled valve body parts

Xiao

Ge²,

Feng³

et al. 2022

Int J Adv Manuf Technol

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A method for analyzing the texture features of free-form surface polishing paths based on co-occurrence matrix

Zhou

et al. 2022

Int J Adv Manuf Technol

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Analysis of polished surface texture features has been the subject of many classic studies in surface polishing technology and is a key indicator for evaluating the polishing path. In this paper, a new method to analyze the texture features of polishing based on co-occurrence matrix is proposed. It extends the previous approach termed the residual level co-occurrence matrix (RLCM) focusing on the distribution of surface polishing residues, leading to more targeted and stabilized evaluation results. This method can be used in the path planning stage to estimate the polishing quality of the planned path without physical processing, which can avoid resource waste in the physical world. Furthermore, in this method the usage of images is avoided, which can ensure that the results are not affected by the light and image quality. Simulation experiments as well as empirical investigations were conducted to verify the feasibility of the method. The results of both consistently reveal that the proposed method is able to accurately describe the texture feature and correctly analyze the texture feature.

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Shape-adaptive CNC milling for complex contours on deformed thin-walled revolution surface parts

Cited by 16 publications

References 23 publications

Influence of Uncertain Parameters on Machining Distortion of Thin-walled Parts

Influence of Uncertain Parameters on Machining Distortion of Thin-walled Parts

Analysis and compensation of surface flatness of thin-walled valve body parts

A method for analyzing the texture features of free-form surface polishing paths based on co-occurrence matrix

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