Accuracy analysis of machine tools using Elastically Linked Systems

Archenti, Andreas; Nicolescu, Mihai

doi:10.1016/j.cirp.2013.03.100

Cited by 40 publications

(15 citation statements)

References 7 publications

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“…This is a significant difference between precision micromachining and conventional macro machining. Moreover, the static stiffness of a machine tool, which affects the machining system capability, is not directly linked to the feed rate [72]. Therefore, the feed marks observed on the Al alloy macrochips at all conditions-from a low to high feed rate-as shown in Figure 15b.…”

Section: Feed Rate Response (Frr) On the Phenomenology Of Chip Formationmentioning

confidence: 98%

Influence of Feed Rate Response (FRR) on Chip Formation in Micro and Macro Machining of Al Alloy

Rahman

Bhuiyan

Sharma

et al. 2021

Metals

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In this paper, the investigation of chip formation of aluminum alloy in different machining strategies (i.e., micro and macro cutting) is performed to develop a holistic view of the chip formation phenomenon. The study of chip morphology is useful to understand the mechanics of surface generation in machining. Experiments were carried out to evaluate the feed rate response (FRR) in both ultra-precision micro and conventional macro machining processes. A comprehensive study was carried out to explore the material removal mechanics with both experimental findings and theoretical insights. The results of the variation of chip morphology showed the dependence on feed rate in orthogonal turning. The transformation of discontinuous to continuous chip production—a remarkable phenomenon in micro machining—has been identified for the conventional macro machining of Al alloy. This is validated by the surface crevice formation in the transition region. Variation of the surface morphology confirms the phenomenology (transformation mechanics) of chip formation.

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Section: Feed Rate Response (Frr) On the Phenomenology Of Chip Formationmentioning

confidence: 98%

Influence of Feed Rate Response (FRR) on Chip Formation in Micro and Macro Machining of Al Alloy

Rahman

Bhuiyan

Sharma

et al. 2021

Metals

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“…Therefore, it results in spatial variation of static stiffness of the system. The importance of conducting studies of the static stiffness distribution in the workspace is being highlighted in recent years [2][3][4]. Both the knowledge of the stiffness distribution and cutting force parameters can be used to predict some machining errors in machine's workspace.…”

Section: Introductionmentioning

confidence: 99%

Measurement and identification of generalised translational static stiffness in machining space of five-axis machine tool

Jastrzębska

Parus²,

Jastrzębski³

et al. 2022

Preprint

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This work presents a measurement for the identification of translational quasi-static stiffness of machine tool using Stiffness Workspace System (SWS). The novelty of this work is a significant modification of the SWS. The changes in measurement procedure and data analysis as well as new technical solutions are described in detail. A methodology for generalised translational static stiffness determination is presented. The major purpose of this paper is to provide the information about quasi-static stiffness values that characterise a typical machine tool. The measurement procedure is implemented in a case study on a 5-axis machining centre. Measurement results were used to determine the generalised translational stiffness indicators of points in the workspace. Then, the static stiffness distribution on the XY plane over machining space was estimated. The obtained results confirm the importance of analyses of static stiffness distribution as they point out areas where some possible changes occur. In the conclusion of the paper the utility value of the information of translational static stiffness is emphasized.

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“…Afterwards, σ Ek is propagated to obtain the variance-covariance matrix ofB k (varB k ). Finally, the Jacobian of the quadratic models is used to propagate the variance-covariance matrices ofB k to obtain the error bars U(Ŷ k ), shown in Equation (8). The SCB surfaces are plotted using the set of error bars U(Ŷ k ).…”

Section: Optimization Of the Calibration Setup Parametersmentioning

confidence: 99%

“…Internal heat sources such as the drive motors, the electronic and pneumatic systems, the spindle, and the linear guides induce gradients of temperature that imply the expansion of machine tool parts [4][5][6][7]. Load and cutting strength are non-negligible effects to consider, too [8,9]. One way to improve the volumetric accuracy of a machine tool is to enhance machine tool design.…”

Section: Introductionmentioning

confidence: 99%

Measurement Parameters Optimized for Sequential Multilateration in Calibrating a Machine Tool with a DOE Method

et al. 2016

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Improving volumetric error compensation is one of the machine tool user's key objectives. Smart compensation is bound to calibration accuracy. Calibration quality depends largely on its setup factors. An evaluation criterion is thus required to test the quality of the compensation deduced from these setup factors. The residual error map, which characterizes post-compensation machine errors, is therefore chosen and then needs to be evaluated. In this study, the translation axes of a machine tool were calibrated with a multilateration tracking laser interferometer. In order to optimize such measurements, the residual error map was then characterized by two appliances: a laser interferometer and the tracking laser already employed for the calibration, using for that purpose the sequential multilateration technique. This research work thus aimed to obtain a smart setup of parameters of machine tool calibration analyzing these two residual error maps through the Design Of Experiment (DOE) method. To achieve this goal, the first step was to define the setup parameters for calibrating a compact machine tool with a multilateration tracking laser. The second step was to define both of the measurement processes that are employed to estimate the residual error map. The third step was to obtain the optimized setup parameters using the DOE method.

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Accuracy analysis of machine tools using Elastically Linked Systems

Cited by 40 publications

References 7 publications

Influence of Feed Rate Response (FRR) on Chip Formation in Micro and Macro Machining of Al Alloy

Influence of Feed Rate Response (FRR) on Chip Formation in Micro and Macro Machining of Al Alloy

Measurement and identification of generalised translational static stiffness in machining space of five-axis machine tool

Measurement Parameters Optimized for Sequential Multilateration in Calibrating a Machine Tool with a DOE Method

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