scholarly journals Sensitivity Analysis of Tool Wear in Drilling of Titanium Aluminides

Metals ◽  
2019 ◽  
Vol 9 (3) ◽  
pp. 297 ◽  
Author(s):  
Aitor Beranoagirre ◽  
Gorka Urbikain ◽  
Raúl Marticorena ◽  
Andrés Bustillo ◽  
Luis López de Lacalle
Keyword(s):  
Titanium Aluminides ◽  
Dimensional Accuracy ◽  
Cutting Parameters ◽  
Combined Cycle ◽  
Aircraft Engines ◽  
Anova Analysis ◽  
Considerable Part ◽  
Tial Alloys ◽  
Optimization Of Cutting Parameters ◽  
Optimal Set

In the aerospace industry, a large number of holes need to be drilled to mechanically connect the components of aircraft engines. The working conditions for such components demand a good response of their mechanical properties at high temperatures. The new gamma TiAl are in the transition between the 2nd and 3rd generation, and several applications are proposed for that sector. Thus, NASA is proposing the use of the alloys in the Revolutionary Turbine Accelerator/Turbine-Based Combined Cycle (RTA/TBCC) Program for the next-generation launch vehicle, with gamma TiAl as a potential compressor and structural material. However, the information and datasets available regarding cutting performance in titanium aluminides are relatively scarce. So, a considerable part of the current research efforts in this field is dedicated to process optimization of cutting parameters and tool geometries. The present work is framed in the study of wear when machining holes in these difficult-to-cut alloys. In particular, the work presents the results from drilling tests on three types of gamma TiAl alloys, extruded MoCuSi, ingot MoCuSi, and TNB type, to define an optimal set of cutting parameters. Maintaining uniform, gradual wear is key to avoiding tool breakage and enabling good hole dimensional accuracy. So, this paper proposes a model based on ANOVA analysis to identify the relationships between cutting conditions and resulting wear and estimate tool life. The best cutting parameters were found at vc = 10–15 m/min and fn = 0.025 mm/rev.

Elemental Segregation and O-Phase Formation in a Gamma-TiAl Alloy

2018 ◽  
Vol 941 ◽  
pp. 741-746 ◽  
Author(s):  
Heike Gabrisch ◽  
Tobias Krekeler ◽  
Uwe Lorenz ◽  
Marcus Willi Rackel ◽  
Martin Ritter ◽  
...  
Keyword(s):  
Tial Alloy ◽  
Titanium Aluminides ◽  
Orthorhombic Phase ◽  
Aircraft Engines ◽  
Duplex Microstructure ◽  
Two Phase ◽  
Chemical Homogeneity ◽  
Phase Form ◽  
Tial Alloys ◽  
O Phase

Titanium aluminides based on the L10 ordered g-phase are promising structural light-weight materials for applications in aircraft engines. Typical compositions for γ-TiAl alloys lie in the range Ti-(44-48)Al (at.-%). For high creep resistance, a two-phase microstructure based on lamellar (α2+γ)-colonies is desirable that may be tuned towards better ductility by introducing pure γ-grains (near lamellar or duplex microstructure).γ-TiAl alloys are often alloyed with niobium for increased oxidation resistance and improved mechanical properties. HEXRD and TEM studies of the alloy Ti-42Al-8.5Nb revealed that the orthorhombic O-phase forms during annealing at 500-650°C. This orthorhombic phase has been known in Nb-rich, Al-lean, α2-based Ti-aluminides since the late 1980ies (Nb> 12.5 at.-%, Al< 31 at.-%) but the finding in γ-based alloys is new.TEM imaging showed that the O-phase is located within α2 lamellae of lamellar (α2+γ)-colonies. O-phase domains and α2 phase form small columnar crystallites based in the α2/γ interface. The columnar crystallites grow parallel to the [0001] direction of the α2 phase and appear as facets when observed along this direction. The evolution of domains and facets with annealing time and the chemical homogeneity of the phases are investigated.The results of STEM imaging show that O-phase domains form during annealing at 550 °C for 8hours or 168 hours. After 168 hours of annealing Nb segregations are observed by EDX mapping within O-phase domains. In comparison, no segregation of niobium is detected after 8 hours of annealing.

scholarly journals Effect of Technological Parameters on the Quality and Dimensional Accuracy of Castings Manufactured by Patternless Process Technology

2014 ◽  
Vol 59 (3) ◽  
pp. 1069-1072 ◽  
Author(s):  
E. Krivoš ◽  
R. Pastirčák ◽  
R. Madaj
Keyword(s):  
Tool Wear ◽  
Dimensional Accuracy ◽  
Cutting Parameters ◽  
Silica Sand ◽  
Technological Parameters ◽  
Process Technology ◽  
Shape Accuracy ◽  
Molding Compounds ◽  
Optimization Of Cutting Parameters

Abstract Submitted article deals with the effect of selected technological parameters on the quality and dimensional accuracy of prototype castings made by Patternless process technology. During experiments were used two types of molding compounds (foamed gypsum and compound based on silica sand and resin). Experiments were focused on optimization of cutting parameters in terms of efficiency, accuracy and possibilities to minimize tool wear. Article deals also with the dimensional and shape accuracy of the castings made by Z-Cast technology. The main aim of the research is to optimize Patternless process technology to such an extent, that achieved dimensional and shape accuracy will be comparable to castings made by the Z-Cast technology.

Optimization of Cutting Parameters Considering Surface Roughness When Milling AISI 304 Steel Using Coated Wc-Co and Tialn / Wc-Co Coated

2019 ◽  
Author(s):  
Murilo Pereira Lopes ◽  
Jose Rubens Gonçalves Carneiro ◽  
Gilmar Cordeiro da Silva ◽  
Carlos Eduardo Santos ◽  
Ítalo Bruno dos Santos
Keyword(s):  
Surface Roughness ◽  
Cutting Parameters ◽  
Aisi 304 ◽  
Aisi 304 Steel ◽  
Optimization Of Cutting Parameters

Prediction of Surface Roughness and Optimization of Cutting Parameters in CNC Turning of Rotational Features

2020 ◽  
Vol 38 (8A) ◽  
pp. 1143-1153
Author(s):  
Yousif K. Shounia ◽  
Tahseen F. Abbas ◽  
Raed R. Shwaish
Keyword(s):  
Surface Roughness ◽  
Linear Regression ◽  
Regression Model ◽  
Linear Regression Model ◽  
Feed Rate ◽  
Cutting Parameters ◽  
Spindle Speed ◽  
Depth Of Cut ◽  
Non Linear ◽  
Optimization Of Cutting Parameters

This research presents a model for prediction surface roughness in terms of process parameters in turning aluminum alloy 1200. The geometry to be machined has four rotational features: straight, taper, convex and concave, while a design of experiments was created through the Taguchi L25 orthogonal array experiments in minitab17 three factors with five Levels depth of cut (0.04, 0.06, 0.08, 0.10 and 0.12) mm, spindle speed (1200, 1400, 1600, 1800 and 2000) r.p.m and feed rate (60, 70, 80, 90 and 100) mm/min. A multiple non-linear regression model has been used which is a set of statistical extrapolation processes to estimate the relationships input variables and output which the surface roughness which prediction outside the range of the data. According to the non-linear regression model, the optimum surface roughness can be obtained at 1800 rpm of spindle speed, feed-rate of 80 mm/min and depth of cut 0.04 mm then the best surface roughness comes out to be 0.04 μm at tapper feature at depth of cut 0.01 mm and same spindle speed and feed rate pervious which gives the error of 3.23% at evolution equation.

Optimization of Cutting Parameters in Milling Process Using Genetic Algorithm and ANOVA (March 2020)

2020 ◽  
Vol 38 (10A) ◽  
pp. 1489-1503
Author(s):  
Marwa Q. Ibraheem
Keyword(s):  
Genetic Algorithm ◽  
Tool Wear ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Optimal Value ◽  
Optimization Of Cutting Parameters

In this present work use a genetic algorithm for the selection of cutting conditions in milling operation such as cutting speed, feed and depth of cut to investigate the optimal value and the effects of it on the material removal rate and tool wear. The material selected for this work was Ti-6Al-4V Alloy using H13A carbide as a cutting tool. Two objective functions have been adopted gives minimum tool wear and maximum material removal rate that is simultaneously optimized. Finally, it does conclude from the results that the optimal value of cutting speed is (1992.601m/min), depth of cut is (1.55mm) and feed is (148.203mm/rev) for the present work.

Research Status of Subsequent Machining of Laser Cladding Layers

2020 ◽  
Vol 15 ◽  
Author(s):  
Lei Li ◽  
Yujun Cai ◽  
Guohe Li ◽  
Meng Liu
Keyword(s):  
Tool Wear ◽  
Surface Quality ◽  
Laser Cladding ◽  
Wear Surface ◽  
Chip Formation ◽  
Cutting Temperature ◽  
Dimensional Accuracy ◽  
Cutting Parameters ◽  
Cladding Layer ◽  
Cladding Layers

Background: As an important method of remanufacturing, laser cladding can be used to obtain the parts with specific shapes by stacking materials layer by layer. The formation mechanism of laser cladding determines the “Staircase effect”, which makes the surface quality can hardly meet the dimensional accuracy of the parts. Therefore, the subsequent machining must be performed to improve the dimensional accuracy and surface quality of cladding parts. Methods: In this paper, chip formation, cutting force, cutting temperature, tool wear, surface quality, and optimization of cutting parameters in the subsequent cutting of laser cladding layer are analyzed. Scholars have expounded and studied these five aspects but the cutting mechanism of laser cladding need further research. Results: The characteristics of cladding layer are similar to that of difficult to machine materials, and the change of parameters has a significant impact on the cutting performance. Conclusion: The research status of subsequent machining of cladding layers is summarized, mainly from the aspects of chip formation, cutting force, cutting temperature, tool wear, surface quality, and cutting parameters optimization. Besides, the existing problems and further developments of subsequent machining of cladding layers are pointed out. The efforts are helpful to promote the development and application of laser cladding remanufacturing technology.

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