A Monte Carlo analysis of uncertainty in supporting assembly of large-aperture optical lenses

Shen, Yiping; Luo, Xin; Liu, Yuan; Chen, Xuedong

doi:10.1177/0954405413489293

Cited by 9 publications

(9 citation statements)

References 19 publications

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“…MCS is considered to be one of the most widely used methods for probabilistic analysis of mechanical systems due to its high accuracy and easy of application (Tian et al, 2015;Shen et al, 2013;Ahn et al, 2011). In the MCS techniques, sampling for each random variable is randomly selected based on distribution information of the random variable.…”

Section: Direct Mcsmentioning

confidence: 99%

Prediction of surface location error in milling considering the effects of uncertain factors

et al. 2017

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Abstract. Machining accuracy of a milled surface is influenced by process dynamics. Surface location error (SLE) in milling determines final dimensional accuracy of the finished surface. Therefore, it is critical to predict, control, and minimize SLE. In traditional methods, the effects of uncertain factors are usually ignored during prediction of SLE, and this would tend to generate estimation errors. In order to solve this problem, this paper presents methods for probabilistic analysis of SLE in milling. A dynamic model for milling process is built to determine relationship between SLE and cutting parameters using full-discretization method (FDM). Monte-Carlo simulation (MCS) method and artificial neural network (ANN) based MCS method are proposed for predicting reliability of the milling process. Finally, a numerical example is used to evaluate the accuracy and efficiency of the proposed method.

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Section: Direct Mcsmentioning

confidence: 99%

Prediction of surface location error in milling considering the effects of uncertain factors

et al. 2017

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“…The process is illustrated in Figure 1. The PUMA approach is a practical method suited to industrial use, for the most rigorous uncertainty evaluations a Monte Carlo approach is increasingly being taken [14] but this makes iterations more difficult.…”

Section: -P2mentioning

confidence: 99%

Uncertainty evaluation method for axi-symmetric measurement machines

Muelaner

Keogh

2016

Int. J. Metrol. Qual. Eng.

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This paper describes a method of uncertainty evaluation for axi-symmetric measurement machines. Specialized measuring machines for the inspection of axisymmetric components enable the measurement of properties such as roundness (radial runout), axial runout and coning. These machines typically consist of a rotary table and a number of contact measurement probes located on slideways. Sources of uncertainty include the probe calibration process, probe repeatability, probe alignment, geometric errors in the rotary table, the dimensional stability of the structure holding the probes and form errors in the reference hemisphere which is used to calibrate the system. The generic method is described and an evaluation of an industrial machine is described as a worked example. Expanded uncertainties, at 95% confidence, were then calculated for the measurement of; radial runout (1.2 μm with a plunger probe or 1.7 μm with a lever probe); axial runout (1.2 μm with a plunger probe or 1.5 μm with a lever probe); and coning/swash (0.44 arcseconds with a plunger probe or 0.60 arcseconds with a lever probe).

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“…This may lead to fracture in optical components [19,20]. Several experimental results are reported, establishing the relationship between SSD and surface roughness of the optical components [21][22][23][24]. Some researchers studied the crystallographic orientation of the material and its role in the generation of SSD [25].…”

Section: Introductionmentioning

confidence: 99%

Effect of machining parameters on surface finish and subsurface damage for diamond-turned germanium

Sharma

Mishra

Garg

et al. 2020

J Braz. Soc. Mech. Sci. Eng.

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Germanium lenses are widely used in various scientific and technological applications mainly infrared optical components. The performance of these lenses depends upon the surface finish, which is challenging to achieve during ductile-regime machining. It is crucial to provide the optimum parameters to ensure the high-quality surface, without surface and subsurface damage. In the present work, an attempt has been made to analyse the effect of input machining parameters on surface finish and subsurface damage distribution, induced during the diamond turning. Taguchi's optimization has been performed to optimize the parameters affecting the performance and surface quality of fabricated components. Abbott-Firestone (A-F) curve is utilized to study the distribution of peaks and valleys on the machined surface. Additionally, chip morphology and machining forces are analysed to study the material removal behaviour at varying parameters. Further, indentations are performed on the best and worst combinations to examine the effect of parameters selection on surface cracks propagation. It is found that surface with a greater number of valleys leads to chipping during indentation. In this study, a surface roughness of 2.3 nm is achieved with minimum subsurface deformation.

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A Monte Carlo analysis of uncertainty in supporting assembly of large-aperture optical lenses

Cited by 9 publications

References 19 publications

Prediction of surface location error in milling considering the effects of uncertain factors

Prediction of surface location error in milling considering the effects of uncertain factors

Uncertainty evaluation method for axi-symmetric measurement machines

Effect of machining parameters on surface finish and subsurface damage for diamond-turned germanium

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