Uncertainty analysis of milling parameters using Monte Carlo simulation, the Taguchi optimization method and data-driven modeling

Kahraman, Mehmet Fatih; Bilge, Habibullah; Ozturk, Sabri

doi:10.3139/120.111344

Cited by 15 publications

(7 citation statements)

References 31 publications

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“…this stage was employed to ensure the theoretical optimum results are verified with the real test whether they are acceptable, valid, and robust. at the end of anoVa analysis, a confirmation test is generally essential to eliminate concerns about the choice of control parameters, the way the experiment was designed as well as assumptions that have been made throughout this analysis [26][27][28][29]. the parameters used in confirmatory tests have been applied by Minitab software.…”

Section: Verification Testmentioning

confidence: 99%

Archives of Metallurgy and Materials

Leong

Shayfull

Fathullah

et al. 2021

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In machInIng uSIng taguchI method the increasing needs of using aluminum epoxy composite as a replacement to solid metal rapid prototyping has opened to interests in optimizing its machining processes. this paper reported on the success of optimizing the surface roughness of aluminium epoxy composite using milling process along with a new finding on the best combination parameters. taguchi method was used as the optimization method whereas spindle speed, feed rate, and depth of cut were set as input factors using an L9 orthogonal array. analysis of Variance was used to identify the significant factors influencing the surface roughness. experiment was conducted in dry condition using a vertical milling machine and the surface roughness after the machining was evaluated. optimum combination of cutting parameters was identified after the finest surface roughness (response) based on the signal-to-noise ratio calculated. Cutting parameters selected after preliminary testing are cutting speeds of (2000, 3000 and 4000) rpm, feed rate (300, 400 and 500) mm/min, and cutting depth (0.15, 0.20, and 0.25) mm. the result showed that cutting speed had the largest percentage contribution to surface roughness with 69% and the second highest contribution was feed rate with 22% and depth of cut at 9%. the spindle speed was found as the most significant factor influencing the quality of surface roughness. the result is significant particularly in providing important guidelines for industries in selecting the right combination of parameters as well as to be cautious with the most significant factor affecting the milling process of metal epoxy composite.

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Section: Verification Testmentioning

confidence: 99%

Archives of Metallurgy and Materials

Leong

Shayfull

Fathullah

et al. 2021

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“…Kahraman et al. 7,8 calculated the undeformed chip thickness to determine the grinding parameters, and optimized the grinding parameters using response surface methodology. The authors also studied the uncertainty analysis of milling parameters based on Monte Carlo simulation and Taguchi optimization method.…”

Section: Introductionmentioning

confidence: 99%

A new method for optimizing process parameters of active measurement grinding based on grey target decision making

Zheng

Liu

Guo

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part C:

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Active measurement technology is used widely in the modern precision-grinding process; currently, however, it is tedious and time consuming to adjust the process parameters of grinding process. This process usually depends on the experience of operators, which directly affects the processing efficiency and intelligent control level. Aiming to optimize these grinding-process parameters, we propose a grey target decision-making method based on the uniform effect measure to realize the intelligent optimization of process parameters. First, we obtain the experimental data of process parameters and evaluation parameters using the orthogonal experimental method, and then we calculate and analyze the degree of relation between process parameters and evaluation parameters based on grey system theory. Then we can obtain the process parameters that have the greatest influence on the workpiece surface roughness, workpiece roundness, and grinding process time. Second, through the proposed grey target decision-making method based on the uniform effect measure, and combined with grey relation analysis, we assign the weights of different evaluation parameters. By optimizing the calculation of multigroup evaluation parameters, we obtain the group of evaluation parameters with the best synthetic effect and identify the optimal combination of parameters to guide production. Through a large number of experimental verifications and analyses, we find that the proposed grinding process parameters optimization method can obtain the best combination of process parameters and can effectively improve processing quality and processing efficiency. The research results provide a theoretical basis for the optimization of grinding process parameters and enhance the intelligent degree of precision grinding.

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“…In recent years, the use of soda-lime glass, which is an organic material in many engineering fields, is superior in comparison to other materials with hardness, low density, low heat and electrical conductivity [9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

“…Many analysis methods have been used for the optimization of the parameters used for glass machining and for the design of the experiment. Also, the experimental design of Taguchi method is used for planning of experiments [13][14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Optimization of Axial Misalignment due to Glass Drilling by Statistical Methods

Harmanci

Ozturk

2020

Sakarya University Journal of Science

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Flat glass has a significant utilization in the domestic appliances sector. Drilling of glass is frequently used in the white goods sector. In this research, the glass drilling method is explained in detail, the determined axial misalignment values using the tool rotation speed and the feed rate were investigated. The drilling operation with its parameters must be optimized precisely, in order to have good control over the productivity, quality, and cost aspect of the application. Using the Ø18.3 mm drill tool, drilling process was performed with different rotation speeds (rpm) and feed rates (mm/sec). The impressions of drilling parameter on output variable were investigated using Analysis of Variance (ANOVA). Probabilistic uncertainty analysis based on Monte Carlo simulation was carried out. According to the results, the suggested model and optimization method could be used for estimating axial misalignment and this investigation is reliable and proper for figuring out the problems met in machining operations. Furthermore, Monte Carlo simulations were obtained quite effective for identification of the uncertainties in axial misalignment that could not be possible to be caught by deterministic ways. The optimum axial misalignment value was found to be 0.11823 mm.

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Uncertainty analysis of milling parameters using Monte Carlo simulation, the Taguchi optimization method and data-driven modeling

Cited by 15 publications

References 31 publications

Archives of Metallurgy and Materials

Archives of Metallurgy and Materials

A new method for optimizing process parameters of active measurement grinding based on grey target decision making

Optimization of Axial Misalignment due to Glass Drilling by Statistical Methods

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