Experimental Investigation and Fuzzy Based Prediction of Titanium Alloy Performance During Drilling Process

• Autorzy: Shareef Israa R. , Hussein Hiba K. , Mahdi Basma Luay

Identyfikatory

DOI

10.12913/22998624/174515

• Języki publikacji: EN

Abstrakty

EN

Recently, titanium and its alloys have been widely used in industry. Titanium alloys are difficult to machine due to high tool wear, cutting temperature, and edge formation. Thus, this analysis predicts how machining parameters, particularly drilling parameters, affect titanium work piece integrity. This study used Taguchi and fuzzy control software to calculate the effects of cutting parameters and drill tip angle on surface roughness maximal temperature in titanium alloy workpieces during dry drilling. Three 10 mm cutting tools have 106°, 118°, and 130° tip angles. Cutting tools are made of high-speed steel. The work piece model is a parallelogram with 100mm width, 150mm length, and 30mm thickness. Cutting settings include three spindle speeds. (500, 1000, and 1500) rpm with 0.1, 0.2, and 0.3 mm/rev feed rates. All simulations have the same hole depth (4 mm). We also estimated and discussed the rate of temperature change due to cutting settings. This prediction is used to diagnose and improve drilling, increase tool life, and safeguard the work piece. This reduces titanium drilling costs and effort. The machining model's work piece temperature is influenced by spindle speed and tool tip angle, but feed rate has no effect. Drillers can optimise drilling performance and obtain desired results including efficient penetration rates, shortened drilling time, and reduced equipment failure by regulating these parameters. Fuzzy Logic predicts drilling parameters on Titanium workpieces with encouraging results.

Słowa kluczowe

EN

Taguchi; drilling optimization; surface roughness; fuzzy logic; work piece temperature; titanium Ti-6Al-4V

• Wydawca: Lublin University of Technology ; Polish Society of Ecological Engineering (PTIE), Branch of PTIE in Lublin
• Czasopismo: Advances in Science and Technology. Research Journal
• Rocznik: 2023
• Tom: Vol. 17, no 6
• Strony: 192--205
• Opis fizyczny: Bibliogr. 37 poz., fig., tab.

Twórcy

autor

Shareef Israa R.

• Department of Mechatronics Engineering, Al-Khwarizmi College of Engineering, University of Baghdad, Baghdad, Iraq

• https://orcid.org/0000-0002-9372-0538

autor

Hussein Hiba K.

• Department of Automated Manufacturing Engineering, Al-Khwarizmi College of Engineering, University of Baghdad, Baghdad, Iraq

• https://orcid.org/0000-0002-6389-9696

autor

Mahdi Basma Luay

• Department of Automated Manufacturing Engineering, Al-Khwarizmi College of Engineering, University of Baghdad, Baghdad, Iraq

• https://orcid.org/0000-0002-0461-2106

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).