Abstract: Machining is an important manufacturing process used to produce a wide variety of metallic parts. Among various machining processes, turning is one of the most important one which is employed to shape cylindrical parts. In turning, the quality of finished product is measured in terms of surface roughness. In turn, surface quality is determined by machining parameters and tool geometry specifications. The main objective of this study is to simultaneously model and optimize machining parameters and tool geometry in order to improve the surface roughness for AISI1045 steel. Several levels of machining parameters and tool geometry specifications are considered as input parameters. The surface roughness is selected as process output measure of performance. A Taguchi approach is employed to gather experimental data. Then, based on signal-to-noise (S/N) ratio, the best sets of cutting parameters and tool geometry specifications have been determined. Using these parameters values, the surface roughness of AISI1045 steel parts may be minimized. Experimental results are provided to illustrate the effectiveness of the proposed approach.
Abstract: In this paper, a simulated annealing algorithm has been developed to optimize machining parameters in turning operation on cylindrical workpieces. The turning operation usually includes several passes of rough machining and a final pass of finishing. Seven different constraints are considered in a non-linear model where the goal is to achieve minimum total cost. The weighted total cost consists of machining cost, tool cost and tool replacement cost. The computational results clearly show that the proposed optimization procedure has considerably improved total operation cost by optimally determining machining parameters.
Abstract: The aim of this research is to evaluate surface
roughness and develop a multiple regression model for surface roughness as a function of cutting parameters during the turning of
flame hardened medium carbon steel with TiN-Al2O3-TiCN coated inserts. An experimental plan of work and signal-to-noise ratio (S/N)
were used to relate the influence of turning parameters to the
workpiece surface finish utilizing Taguchi methodology. The effects
of turning parameters were studied by using the analysis of variance (ANOVA) method. Evaluated parameters were feed, cutting speed,
and depth of cut. It was found that the most significant interaction among the considered turning parameters was between depth of cut and feed. The average surface roughness (Ra) resulted by TiN-Al2O3-
TiCN coated inserts was about 2.44 μm and minimum value was 0.74 μm. In addition, the regression model was able to predict values for surface roughness in comparison with experimental values within
reasonable limit.