Structural Engineering and Mechanics

  • 제73권5호
  • /
  • Pages.501-513
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  • 2020
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  • 1225-4568(pISSN)
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  • 1598-6217(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Design optimization in hard turning of E19 alloy steel by analysing surface roughness, tool vibration and productivity

  • Azizi, Mohamed Walid (Advanced Technologies in Mechanical Production Research Laboratory (LRTAPM), Badji Mokhtar - Annaba University) ;
  • Keblouti, Ouahid (Advanced Technologies in Mechanical Production Research Laboratory (LRTAPM), Badji Mokhtar - Annaba University) ;
  • Boulanouar, Lakhdar (Advanced Technologies in Mechanical Production Research Laboratory (LRTAPM), Badji Mokhtar - Annaba University) ;
  • Yallese, Mohamed Athmane (Mechanics and Structures Research Laboratory (LMS), May 8th 1945 University)
  • 투고 : 2019.06.22
  • 심사 : 2019.10.19
  • 발행 : 2020.03.10
⟨ 이전 논문 다음 논문 ⟩

초록

In the present work, the optimization of machining parameters to achieve the desired technological parameters such as surface roughness, tool radial vibration and material removal rate have been carried out using response surface methodology (RSM). The hard turning of EN19 alloy steel with coated carbide (GC3015) cutting tools was studied. The main problem faced in manufacturer of hard and high precision components is the selection of optimum combination of cutting parameters for achieving required quality of surface finish with maximum production rate. This problem can be solved by development of mathematical model and execution of experiments by RSM. A face centred central composite design (FCCD), which comes under the RSM approach, with cutting parameters (cutting speed, feed rate and depth of cut) was used for statistical analysis. A second-order regression model were developed to correlate the cutting parameters with surface roughness, tool vibration and material removal rate. Consequently, numerical and graphical optimization were performed to obtain the most appropriate cutting parameters to produce the lowest surface roughness with minimal tool vibration and maximum material removal rate using desirability function approach. Finally, confirmation experiments were performed to verify the pertinence of the developed mathematical models.

키워드

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