Geometric error sensitivity analysis for a 6-axis welding equipment based on Lie theory

Fang, Weihua; Tian, Xiaohui

doi:10.1007/s00170-020-06527-9

Cited by 10 publications

(6 citation statements)

References 28 publications

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“…This paper proposes a new SA method to quantify the impact of geometric error on the machining accuracy and extract the key geometric errors. By comparison with the existing SA methods [14][15][16][17][18][19][20][21][22][23][24][25][26], the superiorities of the new SA method are listed as follows: (1) A novel sensitivity index is proposed to solve the problem that the SA results of angular error and linear error need compared separately, which significantly simplifies the SA procedures and improves the computational efficiency. ( 2) The proposed SA model takes into account the characteristic of geometric error changes with different machining positions, which solves the problem that the universality of SA results obtained by assuming all the angular errors and linear errors have the same value is poor.…”

Section: Discussionmentioning

confidence: 99%

“…The sensitivity coefficients were calculated by taking only one machining point as an example to determine the key error components. Fang et al [20] developed a new SA model by utilizing the Lie theory. Due to the units of angular error and linear error are different, the sensitivity coefficients of two kinds errors were calculated and compared respectively.…”

Section: Introductionmentioning

confidence: 99%

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An approach to enhancing machining accuracy of five-axis machine tools based on a new sensitivity analysis method

Tao

Fan

et al. 2022

Int J Adv Manuf Technol

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Identification of key geometric errors is an essential prerequisite for improving the machining accuracy of five-axis machine tools. This paper presents a new sensitivity analysis (SA) method to extract key geometric errors, and then to improve the machining performance of machine tools by compensating key geometric error components. Development of geometric error prediction model is involved to obtain geometric error values at arbitrary positions at first. Based on the multi-body system theory and flank milling theory, the machining error model is developed, which considers 37 geometric errors. Then, a new SA method is introduced by taking the machining error model as sensitivity analysis model and taking the geometric errors as analytical factors. Meanwhile, a sensitivity index, which has the characteristics of simple expression and clear physical meaning, is proposed, i.e., the peak value of the machining error caused by each geometric error. Moreover, the simulations analysis is carried out to obtain the sensitivity coefficient of each geometric error and the key error components. Finally, the validity and correctness of the proposed method is demonstrated by the experiments. Furthermore, the SA method can be extended to multi-axis machine tools.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An approach to enhancing machining accuracy of five-axis machine tools based on a new sensitivity analysis method

Tao

Fan

et al. 2022

Int J Adv Manuf Technol

View full text Add to dashboard Cite

show abstract

“…This paper proposes a new SA method to quantify the influence degree of geometric error on the machining accuracy and extract the key geometric error components. By comparison with the existing SA methods [14][15][16][17][18][19][20][21][22][23][24][25][26], the superiorities of the new SA method are listed as follows: (1) A novel sensitivity index is proposed to solve the problem that the SA results of angular error and linear error need compared separately, which significantly simplified the SA procedures and improves the computational efficiency.…”

Section: Discussionmentioning

confidence: 99%

Machining Accuracy Enhancement of Five-axis Machine Tools by a New Sensitivity Analysis Method Based on Machining Error Model

Tao

Chen

et al. 2022

Preprint

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Identification of key geometric errors is an essential prerequisite for improving the machining accuracy of five-axis machine tools. This paper presents a new sensitivity analysis (SA) method to extract key geometric errors, and then to improve the machining performance of machine tools by compensating key geometric error components. Development of geometric error prediction model is involved to obtain geometric error values at arbitrary positions at first. Based on the multi-body system theory and flank milling theory, the machining error prediction model is developed, which considers 37 geometric errors. Then, a new SA method is introduced by taking the machining error model as sensitivity analysis model and taking the geometric errors as analytical factors. Meanwhile, a sensitivity index, which has the characteristics of simple expression and clear physical meaning, is proposed, i.e., the peak value of the machining error caused by each geometric error. Moreover, the simulations analysis is carried out to obtain the sensitivity coefficient of each geometric error and the key error components. Finally, the validity and correctness of the proposed method is demonstrated by the experiments. Furthermore, the SA method can be extended to multi-axis machine tools.

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“…In addition to this, dimension relevant sensitivity analysis of 2 stretchable spherical relevant source was carried out in this investigation. From a detailed literature survey [19][20][21][22][23], it could be understood that experimental investigations carried out on several fusion relevant welding methodologies, employing the sensitivity relevant analysis are limited. For example, Kim et al [20] in their experimental work, employed sensitivity based analysis to identify and compare the individual impacts of the employed attributes of the automated gas metal arc joining process, on the geometry of employed bead, so as to validate the measurement related flaws on the uncertainty values w.r. t anticipated parameters.…”

Section: Introductionmentioning

confidence: 99%

Analysis of sensitivity and formulation of empirical relationship between parameters of FSW process and tensile strength of AZ80A Mg alloy joints

Gunasekaran,

Sevvel,

Vasanthe Roy

et al. 2023

Mater. Res. Express

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In this research paper, an endeavour was made to devise empirical relations amidst the process parameters of friction stir welding (FSW) and tensile relevant strength of AZ80A Mg alloy joints, based on a 6 parameters – 5 levels based central composite design (CCD). Mathematical equations illustrating the impact of process parameters of FSW were formulated based on quadratic regression based analysis to optimize the parameters for attaining superior tensile strength and sensitivity related equations were established from these numerical models. A detailed sensitivity characteristic relevant map for the FSW of AZ80A Mg alloys was established forecasting the fine tuning related prerequisites of the employed FSW parameters. Coefficient of determinant (R2) announced that 99.062% of the overall variability was described by the formulated model and only lower than 1% of the overall variations was not justified by the model. Predicted R2 was also in perfect agreement with the adjusted R2 and announced the model’s capability to demonstrate 95.43% of the variability in the generated data. Highest value of tensile relevant strength (80.77% of the parent metal) was exhibited by the AZ80A Mg alloy joint fabricated under optimized parameters. Tensile relevant strength of AZ80A Mg joints was observed to be highly sensitive to traverse speed of the employed tool.

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Geometric error sensitivity analysis for a 6-axis welding equipment based on Lie theory

Cited by 10 publications

References 28 publications

An approach to enhancing machining accuracy of five-axis machine tools based on a new sensitivity analysis method

An approach to enhancing machining accuracy of five-axis machine tools based on a new sensitivity analysis method

Machining Accuracy Enhancement of Five-axis Machine Tools by a New Sensitivity Analysis Method Based on Machining Error Model

Analysis of sensitivity and formulation of empirical relationship between parameters of FSW process and tensile strength of AZ80A Mg alloy joints

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