Abstract
Dual heat treatment (DHT) effect is analyzed using the machining of Al6061-T6 alloy, a readily available material for quickly finding the machining properties. The heat treatments are conducted twice over the specimen by the furnace heating before processing through CNC machining. The HSS and WC milling cutters are preferred for the diameter of 10 mm for the reviewed rotational speeds of 2000 rpm and 4000 rpm, and the constant depth of cut of 0.5 mm is chosen based on various reviews. Worthy roughness could be provided mostly by the influence of feed rates preferred here as 0.05 mm/rev and 0.1 mm/rev. The influencing factors are identified by the Taguchi, genetic algorithm (GA), and Artificial Neural Network (ANN) techniques and compared within it. The simulation finding also helps to clarify the relationship between influenced machining constraints and roughness outcomes of this project. The average values of heat treated and nonheat treated Al6061-T6 are compared and it is to be evaluated that 41% improvement is obtained with the lower surface roughness of 1.78975 µm and it shows good surface finish with the help of dual heat treatment process.
Highlights
By the identification of influencing factors on any machining outcomes this will be very useful by its interpreted data for the product improvement in the factory floor
Paper [2] has discussed the tool wear and surface roughness of steel specimen machined with coated inserts with the involvement of austenitizing and tempering heat treatments. e hardness becomes more due to lowering the tempering temperature. ermally heat treated steel specimen with coated carbide inserts have proven effective wear mechanism with the improved tool life. e discussion is about the closeness of the predicted values of particle swarm optimization (PSO) technique which exactly coincide with the experimental roughness values
It can be observed that the roughness becomes poor due to the factors of higher cutting speed. e lesser value of feed rate can boost up the surface quality [3]. ̇Irfan Ucun et al [4] have conducted the finite element simulation for various chip formation related with the surface roughness of machined areas
Summary
By the identification of influencing factors on any machining outcomes this will be very useful by its interpreted data for the product improvement in the factory floor. Paper [2] has discussed the tool wear and surface roughness of steel specimen machined with coated inserts with the involvement of austenitizing and tempering heat treatments. E authors have evaluated that the air cooled specimen attained higher hardness with the ascription of homogeneous lamellar α + β Ti–6Al–4V microstructure with the absence of α′ secondary precipitate which helped for the improved performance Paper [16] has discussed the performance over the tool life and the reduction of cutting forces by using cryogenic cooling lubricants on H13 steel. Paper [18] has discussed the consequence of tool coatings and holder coating in CNC milling influenced by surface roughness with some optimized outcomes verified with the experimental results. Paper [19] has discussed the surface roughness improvement that was good during the machining with lower and higher cutting speeds. The surface quality can be measured over the heat treated and nonheat treated specimens based on the influencing machining parameters and simulated predictions. e optimized outcome plays an important role of finding the optimal solution of surface roughness. e effective stress variation and deflections should reach the satisfied level with the comparison of experimental results through this machining process
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