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Optimization and prediction of CBN tool life sustainability during AA1100 CNC turning by response surface methodology.
H, Faisal M; Krishnan, A Mohana; Prabagaran, S; Venkatesh, R; Kumar, D Satish; Christysudha, J; Seikh, A H; Iqbal, A; Ramaraj, Elangomathavan.
Afiliación
  • H FM; Department of Mechanical Engineering, Ilahia College of Engineering and Technology, Mulavoor, 686673, Kerala, India.
  • Krishnan AM; Department of Mechanical Engineering, K.Ramakrishnan College of Engineering, Trichy, 621112, Tamilnadu, India.
  • Prabagaran S; Department of Mechanical Engineering, Karpagam Academy of Higher Education, Coimbatore, 641021, Tamil Nadu, India.
  • Venkatesh R; Department of Mechanical Engineering, Saveetha School of Engineering, SIMATS, Chennai, 602105, Tamilnadu, India.
  • Kumar DS; Department of Mechanical Engineering, Saveetha School of Engineering, SIMATS, Chennai, 602105, Tamilnadu, India.
  • Christysudha J; Department of Electrical and Electronics Engineering, Anand Institute of Higher Technology, Kazhipattur, Chennai, 603103, India.
  • Seikh AH; Mechanical Engineering Department, College of Engineering, King Saud University, Riyadh, 11421, Saudi Arabia.
  • Iqbal A; Department of Materials Technologies, Faculty of Materials Engineering, Silesian University of Technology, 44-100, Gliwice, Poland.
  • Ramaraj E; Department of Biology, College of Natural and Computational Sciences, Debre Tabor University, Amhara Region, Ethiopia.
Heliyon ; 9(8): e18807, 2023 Aug.
Article en En | MEDLINE | ID: mdl-37560707
The aluminium alloy (AA1100) was familiar with automotive flexible shaft coupling applications due to its high strength, good machinability, and superior thermal and resistance to corrosion characteristics. Machining tool life drives the prominent role for deciding the product quality (machining) act aims to productivity target with zero interruptions. The novelty of this present investigation is the focus on increasing tool life during the complexity of CNC turning operation for AA1100 alloy by using CBN coated insert tool with varied input parameters of spindle speed (SS), feed rate (f), and depth of cut (DOC). Design of experiment (L16), analysis of variance (ANOVA) statistical system adopted with response surface methodology (RSM) is implemented for experimental analysis. The turning input parameters of SS, f and DOC are considered as factors and its SS (900, 1100, 1300, and 1500 rpm), f (0.1, 0.15, 0.2, and 0.25), and DOC (0.1, 0.2, 0.3, and 0.4 mm) values are treated as levels. The investigational analysis was made with the ANOVA technique and the desirability of high tool life with input turning parameters was optimized by RSM, and sample no 11/16 was predicted as high tool life and performed with extended working hours compared to other samples. The RSM optimized best turning parameter combinations are 0.1 mm DOC, 0.2mm/rev to 0.25mm/rev f, and 1300 rpm-1500 rpm SS, facilitating a higher tool life of more than 20min.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Heliyon Año: 2023 Tipo del documento: Article País de afiliación: India Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Heliyon Año: 2023 Tipo del documento: Article País de afiliación: India Pais de publicación: Reino Unido