Surface generation modeling of micro milling process with stochastic tool wear

Zhang, Xuewei; Yu, Tianbiao; Zhao, Ji

doi:10.1016/j.precisioneng.2019.10.015

Cited by 52 publications

(18 citation statements)

References 25 publications

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“…Zhang et al [35] presented an improved analytical surface generation model for micro milling that considers stochastic tool wear. The proposed surface generation model uses probabilistic approach based on the particle filter algorithm to predict the stochastic tool wear progression.…”

Section: Tool Deflection and Surface Roughness Modelingmentioning

confidence: 99%

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Micro milling process modeling: a review

Mamedov

2021

Manufacturing Rev.

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The trend towards miniature manufacturing in high technological fields like bioengineering, electronics and aerospace has increased dramatically over the last decade. Many methods of micro manufacturing have been researched and applied to manufacture small scale components. Among these manufacturing methods micro-mechanical machining methods have shown themselves to be attractive alternatives. Micro milling is one of the most frequently used micro-mechanical machining method with high potential for the precise manufacturing of complex parts. The aim of this work is to present the principal aspects related to micro milling technology, with emphasis on process modeling and quality of the finished product. A general view on process modeling starting from chip thickness models up to tool and workpiece machining induced distortion models is depicted. Specifically, different modeling techniques related to modeling of micro milling process are evaluated and important aspects that authors revealed during their research are presented. Finally, implications are discussed and suggestions for future research are presented.

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Section: Tool Deflection and Surface Roughness Modelingmentioning

confidence: 99%

“…10. Predicted and measured surface topography of micro milling process with spindle speed 20 000 rpm, feed rate 0.2 mm/ s, radial depth of cut 0.508 mm, and axial depth of cut 0.15 mm [35]. Fig.…”

Section: Thermal Modelingmentioning

confidence: 99%

Micro milling process modeling: a review

Mamedov

2021

Manufacturing Rev.

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“…can be estimated without numerous experimental work, which is often time and cost consuming. The micromilling process was modelled and simulated by the researchers using (i) analytical models [78,148,239], (ii) numerical models [117,191,249], (iii) regression analysis [42,171] or (iv) response surface methodology [200,201,205]. Table 4 summarises the key scientific studies from the past five years in the topic of modelling of the micro-milling process.…”

Section: Micro-milling Modellingmentioning

confidence: 99%

A review on micro-milling: recent advances and future trends

Balázs

Geier

Takács

et al. 2020

Int J Adv Manuf Technol

125

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Recently, mechanical micro-milling is one of the most promising micro-manufacturing processes for productive and accurate complex-feature generation in various materials including metals, ceramics, polymers and composites. The micro-milling technology is widely adapted already in many high-tech industrial sectors; however, its reliability and predictability require further developments. In this paper, micro-milling related recent results and developments are reviewed and discussed including micro-chip removal and micro-burr formation mechanisms, cutting forces, cutting temperature, vibrations, surface roughness, cutting fluids, workpiece materials, process monitoring, micro-tools and coatings, and process-modelling. Finally, possible future trends and research directions are highlighted in the micro-milling and micro-machining areas.

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“…The use of precision milling enables the production of components with high surface quality, and thus eliminates the need for additional finishing operations [ 17 ]. Studies [ 11 , 18 , 19 , 20 , 21 , 22 , 23 ] conducted on aluminium and titanium alloys show that their surface condition predominantly depends on the precision milling parameters, the most important being feed per tooth as it determines the initiation of the cutting process. A too low feed per tooth value causes ploughing and, in effect, a significant deterioration in the workpiece surface condition.…”

Section: Introductionmentioning

confidence: 99%

Dimensional Accuracy and Surface Quality of AZ91D Magnesium Alloy Components after Precision Milling

2021

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This study investigates a precision milling process conducted with the use of conventional end mills and a standard CNC (Computer Numerical Control) machine tool. Milling tests were performed on samples of AZ91D magnesium alloy using TiB2- and TiAlN-coated three-edge end mills measuring 16 mm in diameter. The following technological parameters were made variable: cutting speed, feed per tooth and axial depth of cut. The effects of precision milling were evaluated by analysing the scatter of dimension values obtained in successive tool passes. In addition to that, deviations from the assumed nominal depth as well as obtained ranges of dimension varation were analysed. The study also examined surface quality obtained in the precision milling process, based on the basic surface roughness parameters: Ra, Rz and RSm. Results have confirmed that the use of conventional cutting tools and a standard CNC machine tool makes it possible to manufacture components characterized by relatively small scatter of dimension values and high accuracy classes. Additionally, the results have shown that the type of tool coating and variations of individual technological parameters exert impact on the dimensional accuracy and surface quality obtained.

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Surface generation modeling of micro milling process with stochastic tool wear

Cited by 52 publications

References 25 publications

Micro milling process modeling: a review

Micro milling process modeling: a review

A review on micro-milling: recent advances and future trends

Dimensional Accuracy and Surface Quality of AZ91D Magnesium Alloy Components after Precision Milling

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