RETRACTED: Cutting tool wear minimization in drilling operations of titanium alloy Ti-6Al-4V

Aamir M Giasin K Tolouei-Rad M , et al. A review: drilling performance and hole quality of aluminium alloys for aerospace applications. Journal of Materials Research and Technology 2020; 9: 12484–12500.

Dursun T Soutis C . Recent developments in advanced aircraft aluminium alloys. Materials & Design (1980-2015) 2014; 56: 862–871.

Dhar N Kamruzzaman M Ahmed M . Effect of minimum quantity lubrication (MQL) on tool wear and surface roughness in turning AISI-4340 steel. J Mater Process Technol 2006; 172: 299–304.

Lindvall R Lenrick F Persson H , et al. Performance and wear mechanisms of PCD and pcBN cutting tools during machining titanium alloy Ti6Al4V. Wear 2020; 454: 203329.

Attanasio A Ceretti E Outeiro J , et al. Numerical simulation of tool wear in drilling Inconel 718 under flood and cryogenic cooling conditions. Wear 2020; 458: 203403.

Sharma A Jain V Gupta D . Characterization of chipping and tool wear during drilling of float glass using rotary ultrasonic machining. Measurement 2018; 128: 254–263.

Singh G Gupta MK Mia M , et al. Modeling and optimization of tool wear in MQL-assisted milling of Inconel 718 superalloy using evolutionary techniques. The International Journal of Advanced Manufacturing Technology 2018; 97: 481–494.

Liu M-K Tseng Y-H Tran M-Q . Tool wear monitoring and prediction based on sound signal. The International Journal of Advanced Manufacturing Technology 2019; 103: 3361–3373.

Xu L Huang C Li C , et al. Estimation of tool wear and optimization of cutting parameters based on novel ANFIS-PSO method toward intelligent machining. J Intell Manuf 2021; 32: 77–90.

Yarar E Karabay S . Investigation of the effects of ultrasonic assisted drilling on tool wear and optimization of drilling parameters. CIRP Journal of Manufacturing Science and Technology 2020; 31: 265–280.

Capasso S Paiva J Junior EL , et al. A novel method of assessing and predicting coated cutting tool wear during Inconel DA 718 turning. Wear 2019; 432: 202949.

Nouri M Fussell BK Ziniti BL , et al. Real-time tool wear monitoring in milling using a cutting condition independent method. Int J Mach Tools Manuf 2015; 89: 1–13.

Rizal M Ghani J Nuawi M , et al. Cutting tool wear classification and detection using multi-sensor signals and Mahalanobis-Taguchi System. Wear 2017; 376: 1759–1765.

Shankar S Mohanraj T Rajasekar R . Prediction of cutting tool wear during milling process using artificial intelligence techniques. Int J Computer Integr Manuf 2019; 32: 174–182.

Maruda RW Krolczyk GM Nieslony P , et al. The influence of the cooling conditions on the cutting tool wear and the chip formation mechanism. J Manuf Process 2016; 24: 107–115.

Rech J Giovenco A Courbon C , et al. Toward a new tribological approach to predict cutting tool wear. CIRP Ann 2018; 67: 65–68.

Shen Y Yang F Habibullah MS , et al. Predicting tool wear size across multi-cutting conditions using advanced machine learning techniques. J Intell Manuf 2021; 32: 1753–1766.

Zhao T Zhou J Bushlya V , et al. Effect of cutting edge radius on surface roughness and tool wear in hard turning of AISI 52100 steel. The International Journal of Advanced Manufacturing Technology 2017; 91: 3611–3618.

He Z Shi T Xuan J , et al. Research on tool wear prediction based on temperature signals and deep learning. Wear 2021; 478: 203902.

Maruda RW Krolczyk GM Feldshtein E , et al. Tool wear characterizations in finish turning of AISI 1045 carbon steel for MQCL conditions. Wear 2017; 372: 54–67.

Soori M Arezoo B Habibi M . Accuracy analysis of tool deflection error modelling in prediction of milled surfaces by a virtual machining system. Int J Comput Appl Technol 2017; 55: 308–321.

Soori M Arezoo B Habibi M . Virtual machining considering dimensional, geometrical and tool deflection errors in three-axis CNC milling machines. J Manuf Syst 2014; 33: 498–507.

Soori M Arezoo B Habibi M . Dimensional and geometrical errors of three-axis CNC milling machines in a virtual machining system. Computer-Aided Design 2013; 45: 1306–1313.

Soori M Arezoo B Habibi M . Tool deflection error of three-axis computer numerical control milling machines, monitoring and minimizing by a virtual machining system. J Manuf Sci Eng 2016; 138: 081005–081016.

Soori M Asmael M . Virtual minimization of residual stress and deflection error in five-axis milling of turbine blades. Strojniski Vestnik/Journal of Mechanical Engineering 2021; 67: 235–244.

Soori M Asmael M . Cutting temperatures in milling operations of difficult-to-cut materials. Journal of New Technology and Materials 2021; 11: 47–56.

Soori M Arezoo B . A review in machining-induced residual stress. Journal of New Technology and Materials 2022; 12: 64–83.

Soori M Asmael M Khan A , et al. Minimization of surface roughness in 5-axis milling of turbine blades. Mech Based Des Struct Mach 2021: 1–18.

Soori M Asamel M . Mechanical behavior of materials in metal cutting operations, A review. Journal of New Technology and Materials 2020; 10: 79–89.

Soori M Asamel M Solyali D . Recent development in friction stir welding process: a review. SAE International Journal of Materials and Manufacturing 2020; 14: 18.

Soori M Asmael M . Classification of research and applications of the computer aided process planning in manufacturing systems. Independent Journal of Management & Production 2021; 12: 1250–1281.

Soori M Asmael M . A review of the recent development in machining parameter optimization. Jordan Journal of Mechanical & Industrial Engineering 2022; 16: 205–223.

Soori M Arezoo B . Virtual machining systems for CNC milling and turning machine tools: a review. International Journal of Engineering and Future Technology 2020; 18: 56–104.

Soori M Arezoo B . Cutting tool wear prediction in machining operations, A review. Journal of New Technology and Materials 2022; 12: 15–26.

Soori M Asmael M. Minimization of Deflection Error in Five Axis Milling of Impeller Blades. Facta Universitatis, series: Mechanical Engineering 2021.

Dastres R Soori M Asmael M . Radio frequency identification (RFID) based wireless manufacturing systems, A review. Independent Journal of Management & Production 2022; 13: 258–290.

Glaa N Mehdi K Zitoune R . Numerical modeling and experimental analysis of thrust cutting force and torque in drilling process of titanium alloy Ti6Al4V. The International Journal of Advanced Manufacturing Technology 2018; 96: 2815–2824.

Takeyama H Murata R. Basic investigation of tool wear. 1963.

Ji C Li Y Qin X , et al. 3D FEM simulation of helical milling hole process for titanium alloy ti-6Al-4V. The International Journal of Advanced Manufacturing Technology 2015; 81: 1733–1742.

He A Xie G Zhang H , et al. A comparative study on Johnson–Cook, modified Johnson–Cook and Arrhenius-type constitutive models to predict the high temperature flow stress in 20CrMo alloy steel. Materials & Design (1980-2015) 2013; 52: 677–685.

Lin Y Chen X-M . A combined Johnson–Cook and Zerilli–Armstrong model for hot compressed typical high-strength alloy steel. Comput Mater Sci 2010; 49: 628–633.

Ren J Cai J Zhou J , et al. Inverse determination of improved constitutive equation for cutting titanium alloy Ti-6Al-4V based on finite element analysis. The International Journal of Advanced Manufacturing Technology 2018; 97: 3671–3682.

Kumar BS Baskar N . Integration of fuzzy logic with response surface methodology for thrust force and surface roughness modeling of drilling on titanium alloy. The International Journal of Advanced Manufacturing Technology 2013; 65: 1501–1514.

Bement TR . Taguchi techniques for quality engineering. Oxfordshire, UK: Taylor & Francis, 1989.

Yang X Richard Liu C . Machining titanium and its alloys. Mach Sci Technol 1999; 3: 107–139.