Analysis–synthesis of dimensional deviation of the machining feature for discrete-part manufacturing processes

Wan, Xiaojin; Chen, Xiong; Wang, Xufeng; Zhang, Xiaoming; Xiong, Yan

doi:10.1016/j.ijmachtools.2009.07.014

Cited by 14 publications

(4 citation statements)

References 22 publications

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“…Zhou et al [9] further generalized the deviation representation and proposed a generic linear state space model based on differential motion vectors (DMVs). A similar model was proposed by Wan et al [23] including error sources due to workpiece-fixture local contact compliance. Recently, Abellan-Nebot et al [11] extended the state space model developed in [9] by including specific machining-induced variations such as those due to geometric-thermal variations of machine-tools, cutting-tool deflections or cuttingtool wear.…”

Section: Stream Of Variation Modeling For Mmpsmentioning

confidence: 99%

Process-oriented tolerancing using the extended stream of variation model

Abellán-Nebot

Liu

Romero

2013

Computers in Industry

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Current works on process-oriented tolerancing for multi-station manufacturing processes (MMPs) have been mainly focused on allocating fixture tolerances to ensure part quality specifications at a minimum manufacturing cost. Some works have also included fixture maintenance policies into the tolerance allocation problem since they are related to both manufacturing cost and final part quality. However, there is a lack of incorporation of other factors that lead to increase of manufacturing cost and degrade of product quality, such as cutting-tool wear and machine-tool thermal state. The allocation of the admissible values of these process variables may be critical due to their impact on cutting-tool replacement and quality loss costs. In this paper, the process-oriented tolerancing is expanded based on the recently developed, extended stream of variation (SoV) model, which explicitly represents the influence of machining process variables in the variation propagation along MMPs. In addition, the probability distribution functions (pdf) for some machining process variables are analyzed, and a procedure to derive part quality constraints according to GD&T specifications is also shown. With this modeling capability extension, a complete process-oriented tolerancing can be conducted, reaching a real minimum manufacturing cost. In order to demonstrate the advantage of the proposed methodology over a conventional method, a case study is analyzed in detail.

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Section: Stream Of Variation Modeling For Mmpsmentioning

confidence: 99%

Process-oriented tolerancing using the extended stream of variation model

Abellán-Nebot

Liu

Romero

2013

Computers in Industry

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“…Consider a workpiece and the ith locator/clamp come into contact at a point C i , the desired the contact stiffness, normal and tangential contact stiffness Ref. [21,23] yield as follows:…”

Section: Problem Formulationmentioning

confidence: 99%

“…These work only predicted the displacement of the workpiece, did not consider the effect of the displacement of the workpiece on the machining feature, consequently, cannot be directly used to analyze the machining accuracy of the machining feature. Recent work [21,22] built the relationship model between the machining error and the geometric default (including machining datum), local deformation and entire deformation of the workpiece-fixture, these models can be only utilized to predict the machining error due to the workpiecefixture system.…”

Section: Introductionmentioning

confidence: 99%

An error control approach to tool path adjustment conforming to the deformation of thin-walled workpiece

Wan

Hua

Wang

et al. 2011

International Journal of Machine Tools and Manufacture

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“…However, manufacturing free-form surfaces is a highly complicated process [4]. Due to the influence of system errors and random noise of manufacturing process, dimensional deviation [5] and dimensional variation [6] are inevitable for batch parts. Dimensional deviation is the relative deviation of the dimension distribution center of the batch parts to its design dimension, which is the result of the system errors on parts' dimension.…”

Section: Introductionmentioning

confidence: 99%

Dimensional Deviation Estimation for Parts with Free-Form Surfaces

Zhao

Wang

Zhou

et al. 2018

Mathematical Problems in Engineering

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Dimensional deviation is a prerequisite for improving the manufacturing process of parts with free-form surfaces, for example, the reverse adjustment of the die cavity of turbine blade. Influenced by random noise of the manufacturing process, dimensional variation is inevitable for batch parts. Therefore, it may cause unacceptable error to estimate batch parts dimensional deviation by a single sample. Meanwhile, the optimum sample size for estimating dimensional deviation is difficult to determine. To overcome this problem, a practical method for estimating of dimensional deviation of parts with free-form surface is proposed. Firstly, displacements of the discrete points on part surface are employed to represent dimensional error of the part. Estimating dimensional deviation of parts is actually to estimate the simultaneous confidence intervals of the discrete point displacements. Secondly, Bonferroni simultaneous confidence intervals are adopted to estimate the confidence intervals of the part dimensional deviation. Moreover, the accuracy of the estimation will be continuously improved by increasing samples. Consequently, a practical dimensional deviation estimation method is presented. Finally, a compressor blade is adopted to illustrate the proposed method. The percentage of estimation error of the blade dimensional deviation that is less than 0.05mm, which is the estimation error limit, of all the 100 times sampling experiments is 99%, exceeding the given confidence level of 95%, while the percentage of the existing method is below the confidence level, only 87%.

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Analysis–synthesis of dimensional deviation of the machining feature for discrete-part manufacturing processes

Cited by 14 publications

References 22 publications

Process-oriented tolerancing using the extended stream of variation model

Process-oriented tolerancing using the extended stream of variation model

An error control approach to tool path adjustment conforming to the deformation of thin-walled workpiece

Dimensional Deviation Estimation for Parts with Free-Form Surfaces

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