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Multi-objective parametric optimization of wire electric discharge machining for Die Hard Steels using supervised machine learning techniques
Published in Rajeev Agrawal, J. Paulo Davim, Maria L. R. Varela, Monica Sharma, Industry 4.0 and Climate Change, 2023
Pratyush Bhatt, Pranav Taneja, Navriti Gupta
The output variables obtained in WEDM are: Surface Roughness (Ra): It is a measure of irregularities on machined surfaces or the measure of vertical aberrations along a flat surface. It is measured in μm using a surface roughness comparator or profilometer.Material Removal Rate (MRR): It refers to the material removed per unit time. It is measured in mm3/min [6]. MRR=Kerfwidth(k)×Thicknessofworkpiece(t)×Cuttingvelocity(Vc)
Multiobjective Optimization of BSL 165 Aluminium Composite For Aeronautical Applications
Published in Samson Jerold Samuel Chelladurai, Suresh Mayilswamy, Arun Seeralan Balakrishnan, S. Gnanasekaran, Green Materials and Advanced Manufacturing Technology, 2020
R. Suresh Kumar, T. Ramakrishnan, S. Balasubramani
The entire study is carried out in the following sequences: The experiments are conducted on a 3-axis CNC vertical machining centre with a high-speed steel end-mill cutter of 12 mm diameter having four flutes with 22 mm overhung length under wet condition.The process parameters considered are spindle speed (rpm), feed rate (mm/rev), depth of cut (mm) and coolant flow rate (l/min).The surface roughness is measured by using a surface roughness tester.The experiment is conducted at three levels, four-factor central composite rotatable designs having 25 sequences of experimental runs.The second-order quadratic model is developed for the prediction of surface roughness and MRR and is checked for its adequacy using analysis of variance (ANOVA).GA is utilized to determine the optimized set of machining parameters that leads to the minimum value of surface roughness (Ra) and the maximum value of MRR.Validation of the result is confirmed by performing experimental runs.
Imperialism and Finance
Published in Leo Alting, Geoffrey Boothroyd, Manufacturing Engineering Processes, 2020
Superimposed on these purely geometrical considerations are the effects of the cutting process, including the possible existence of a built-up edge on the tool. A built-up edge results in a rough surface. Since the tendency to produce a built-up edge is decreased for increasing cutting speeds, it might be expected that the surface roughness decreases by increasing cutting speed, and this is indeed the case. Furthermore, an effective cutting lubricant can reduce the surface roughness because it reduces the built-up edge.
Assessment Techniques for Studying the Effects of Fire on Stone Materials: A Literature Review
Published in International Journal of Architectural Heritage, 2020
Edite Martinho, Amélia Dionísio
Surface roughness is usually measured using a profilometer, though it can be measured by manual comparison against with a known surface roughness sample (surface roughness comparator). Profilometers can be of different types depending on whether they require direct contact with the surface. The mechanical contact method uses a shaped-tip stylus, typically made of diamond and is the most common technique for assessing surface characteristics. However, during the last decade optical methods have begun to be used in different areas to evaluate the surface roughness, and may even substitute mechanical surface roughness measurements in some applications. Besides being non-destructive and not requiring mechanical contact with the measured surface, optical methods provide higher response speed and greater accuracy and reliability. A single image acquisition can capture the information necessary for 2D or 3D surface measurements. Different profile roughness parameters can be calculated and are defined according international standards such as the European Committee for Standardization BS EN ISO 4287 (2000).
Role and importance of surface heterogeneities in transport of particles in saturated porous media
Published in Critical Reviews in Environmental Science and Technology, 2020
Chongyang Shen, Yan Jin, Jie Zhuang, Tiantian Li, Baoshan Xing
Surface roughness may be defined as deviation of the actual surface topography from an ideal smooth surface (Kreder, Alvarenga, Kim, & Aizenberg, 2016). The surfaces of natural collector grains all contain some degree of physical nonuniformity of certain scale (Suresh & Walz, 1996). For example, silicates and aluminosilicates are the dominant primary minerals in soil and aquifer sediments and their surface topographies can be quite irregular due to the presence of physical heterogeneities such as steps, pits, and intergranular pores of various sizes (Fischer et al., 2014). Furthermore, secondary minerals like carbonate and sulfate minerals and oxides of aluminum, iron and manganese are frequently present as coatings on the surfaces of the primary minerals (Ryan & Elimelech, 1996). These components are expected to change the surface topographies and result in roughness over a wide range of length scales.
Experimental investigations into transient roughness reduction in ball-end magneto-rheological finishing process
Published in Materials and Manufacturing Processes, 2019
The quality and magnitude of surface roughness in a component significantly impacts its properties, viz. frictional losses, component life under loads, and wear resistance in most industrial applications. The rapid advancement in industries such as the electronics, optical, aerospace, energy sectors, etc., significantly increased the demand of precise surface finish quality on component surfaces. Surface finishing of new advanced materials which tend to have higher values of hardness, toughness; strength to weight ratio, etc., has been a big quandary for the industries. Conventional finishing processes like lapping, grinding and honing create burrs, residual stresses, subsurface damage, etc., and also using them on delicate materials like glass is not possible. Obtaining the surface roughness value down to the level of nanometers is difficult and uneconomical through conventional finishing processes. In the recent past, various advanced precise surface finishing processes have been reported which control the finishing forces. Few of these processes are magnetic float polishing,[1] magneto-rheological abrasive flow finishing,[2] abrasive flow machining,[3] magneto-rheological jet finishing,[4] and magneto-rheological finishing (MRF).[5] The magnetic flux in these processes plays a major role in controlling finishing forces. However, these processes have limited applications bound by specific geometries of the components, i.e. regular shaped surfaces such as concave, convex, flat, and symmetrically spherical shapes.