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Optimization of Micro-milling Parameters Regarding Burr Size Minimization via RSM and Simulated Annealing Algorithm

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Abstract

In micro-machining process, there are a lot of factors that affect formation of burr along micro-component’s edges. Therefore, finding suitable machining parameters significantly reduces the burr size in micro-products. In the current work, experimental investigations have been performed to study effects of micro-milling parameters (i.e. cutting speed, feed rate and depth of cut) on burr height and burr thickness of the micro-grooves of 316 stainless steel in up milling and down milling operations. The aforementioned factors were varied over their working ranges while other parameters such as tool material, tool condition, lubrication etc. were kept constant. Here, experiments were designed and conducted based on three factors-three levels face centered central composite design. The response surface methodology (RSM) and analysis of variances were applied on generated data to correlate empirical relationships between micro-milling parameters and burr characteristics. Further, the developed RSM models was then associated with principal component analysis and simulated annealing to minimize burr characteristics in both up-milling and down-milling processes, simultaneously. According to optimization results, spindle speed of 15,000 RPM, feed rate 5 mm/tooth and depth of cut of 0.15 is the most optimal factor combination that causes minimum burr sizes.

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Abbreviations

Bhup :

Burr height in up milling

Btup :

Burr thickness in up milling

Bhdown :

Burr height in down milling

Btdown :

Burr thickness in down milling

RSM:

Response surface methodology

ANOVA:

Analysis of variances

N:

Spindle speed

F :

Feed rate

doc:

depth of cut

SEM:

Scanning electron microscopy

PCA:

Principal component analysis

SA:

Simulated annealing

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Authors and Affiliations

  1. Mechanical Engineering Department, Tabriz Branch, Islamic Tabriz University, Sari, Iran

    Saeed Parsa Khanghah

  2. Mechanical Engineering Department, Sari Branch, Islamic Aazad University, Sari, Iran

    Mehrzad Boozarpoor

  3. Technical and Vocational University of Neyshabour, Neyshabour, Iran

    Mohesen Lotfi

  4. Mechanical Engineering Department, Babol University of Technology, Babol, Iran

    Reza Teimouri

Authors
  1. Saeed Parsa Khanghah
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  2. Mehrzad Boozarpoor
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  3. Mohesen Lotfi
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  4. Reza Teimouri
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Correspondence to Reza Teimouri.

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Khanghah, S.P., Boozarpoor, M., Lotfi, M. et al. Optimization of Micro-milling Parameters Regarding Burr Size Minimization via RSM and Simulated Annealing Algorithm. Trans Indian Inst Met 68, 897–910 (2015). https://doi.org/10.1007/s12666-015-0525-9

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  • DOI: https://doi.org/10.1007/s12666-015-0525-9

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