Evaluation of CMM Uncertainty Through Monte Carlo Simulations

Balsamo, Alessandro; Ciommo, M. Di; Mugno, R.; Rebaglia, Bruno I.; Ricci, Elisa; Grella, R.

doi:10.1016/s0007-8506(07)63218-1

Cited by 80 publications

(38 citation statements)

References 5 publications

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“…Monte Carlo simulation has been used by Schwenke et al [16], Cox et al [17], Trapet et al [18], Balsamo et al [19] and others to assess measurement uncertainty. In addition, the 2008 GUM includes a supplemental guide that deals with the use of Monte Carlo simulation as a tool for evaluating measurement uncertainty through the propagation of distributions [20].…”

Section: Methodsmentioning

confidence: 99%

Silicon bulk micromachined hybrid dimensional artifact.

Claudet

Tran

Bauer

et al. 2010

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A mesoscale dimensional artifact based on silicon bulk micromachining fabrication has been developed and manufactured with the intention of evaluating the artifact both on a high precision coordinate measuring machine (CMM) and video-probe based measuring systems. This hybrid artifact has features that can be located by both a touch probe and a video probe system with a k=2 uncertainty of 0.4 m, more than twice as good as a glass reference artifact. We also present evidence that this uncertainty could be lowered to as little as 50 nm (k=2).While video-probe based systems are commonly used to inspect mesoscale mechanical components, a video-probe system's certified accuracy is generally much worse than its repeatability. To solve this problem, an artifact has been developed which can be calibrated using a commercially available high-accuracy tactile system and then be used to calibrate typical production vision-based measurement systems. This allows for error mapping to a higher degree of accuracy than is possible with a glass reference artifact.Details of the designed features and manufacturing process of the hybrid dimensional artifact are given and a comparison of the designed features to the measured features of the manufactured artifact is presented and discussed. Measurement results from vision and touch probe systems are compared and evaluated to determine the capability of the manufactured artifact to serve as a calibration tool for video-probe systems. An uncertainty analysis for calibration of the artifact using a CMM is presented. 3 ACKNOWLEDGMENTS

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Section: Methodsmentioning

confidence: 99%

Silicon bulk micromachined hybrid dimensional artifact.

Claudet

Tran

Bauer

et al. 2010

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“…Modelling of the overall uncertainty value using Monte Carlo simulation or Bayesian theory [23,25] can provide a probability of measurement uncertainty. Considering the 3-and 5-axis volumetric performance simulations, uncertainties in the individual errors of ±10% (based on an average relationship between typical errors from a laser interferometer system typically used for machine tool error measurement and the ISO standard tolerances) could contribute up to 53 µm and 88 µm, respectively.…”

Section: Effect Of the Uncertainty Of Measurementmentioning

confidence: 99%

The role of measurement and modelling of machine tools in improving product quality

Longstaff

Fletcher

Parkinson

et al. 2013

Int. J. Metrol. Qual. Eng.

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Abstract. Manufacturing of high-quality components and assemblies is clearly recognised by industrialised nations as an important means of wealth generation. A "right first time" paradigm to producing finished components is the desirable goal to maximise economic benefits and reduce environmental impact. Such an ambition is only achievable through an accurate model of the machinery used to shape the finished article. In the first analysis, computer aided design (CAD) and computer aided manufacturing (CAM) can be used to produce an instruction list of three-dimensional coordinates and intervening tool paths to translate the intent of a design engineer into an unambiguous set of commands for a manufacturing machine. However, in order for the resultant manufacturing program to produce the desired output within the specified tolerance, the model of the machine has to be sufficiently accurate. In this paper, the spatial and temporal sources of error and various contemporary means of modelling are discussed. Limitations and assumptions in the models are highlighted and an estimate of their impact is made. Measurement of machine tools plays a vital role in establishing the accuracy of a particular machine and calibrating its unique model, but is an often misunderstood and misapplied discipline. Typically, the individual errors of the machine will be quantified at a given moment in time, but without sufficient consideration either for the uncertainty of individual measurements or a full appreciation of the complex interaction between each independently measured error. This paper draws on the concept of a "conformance zone", as specified in the ISO 230:1 -2012, to emphasise the need for a fuller understanding of the complex uncertainty of measurement model for a machine tool. Work towards closing the gap in this understanding is described and limitations are noted.

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“…The MC method repeats simulated measurements, each consisting of the nominal measurement value with random noise of the sensor added to it. Therefore, the MC method can propagate the probability density function (PDF) of each input quantity, from each coordinate acquisition station, directly to the total measurement set through the measurement model [21][22][23].…”

Section: Estimation Of Measuring Uncertainties Based On Monte Carlo Smentioning

confidence: 99%

Fusion Estimation of Point Sets from Multiple Stations of Spherical Coordinate Instruments Utilizing Uncertainty Estimation Based on Monte Carlo

Zhang¹,

Qu²

2012

Measurement Science Review

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Multiple instrument stations, based on spherical coordinate measurements, are often used in the measurement of large objects. A data fusion method is proposed to derive optimal estimations of the positions of the object features, measured by more than one device. First, each device has a dedicated coordinate system that is linked together through the measurement of common points. Second, the weighted mean coordinates are derived. The covariance matrix of the sensory, covering of the radial distance and the angles, is propagated to get a weight matrix. Third, a nonlinear function is minimized to determine the optimized coordinate of the points. Monte Carlo error propagation is utilized to estimate the uncertainty of the fusion points. Simulation of the fusion algorithms is performed using laser tracking and laser radar. The fusion algorithm experiments are performed using two laser tracking stations. Simulation and experiments prove that the fusion method improves the precision of the measurements of an object's location, due to incorporating the degree of uncertainty for each measurement point.

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Evaluation of CMM Uncertainty Through Monte Carlo Simulations

Cited by 80 publications

References 5 publications

Silicon bulk micromachined hybrid dimensional artifact.

Silicon bulk micromachined hybrid dimensional artifact.

The role of measurement and modelling of machine tools in improving product quality

Fusion Estimation of Point Sets from Multiple Stations of Spherical Coordinate Instruments Utilizing Uncertainty Estimation Based on Monte Carlo

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