Investigation of the machining process of GG25 cast iron material

Machining is the most commonly used manufacturing method in the industry. A lot of products are finalized with machining method after casting or forging. Unwanted chip is removed by the cutting tool on a rotating workpiece or a rotating cutting tool removes unwanted chips on the stationary workpiece. When the workpiece rotates it is named turning operation, when the cutting tool rotates it is named milling operation. The common goal of different machining methods is to remove the chips on the raw material with the help of the cutting tool and to provide the desired dimensions. During these operetions, required energy is provided by CNC machines. Machining method involves a lot of difficulties. To overcome the difficulties and to procure correct part, machining process paremeters must be selected correctly. In addition dimensional features the designer requires a precision on certain surfaces of the product according to the features of the product. This surface precision is defined as surface quality. There are many factors that effect the desired surface quality value in machining method. These factors can be process parameters and factors independent of the process, depending on the cutting tool and machine used. Main process paremeters are cutting speed, revolutions per minute, feed rate and cutting depth. On the other hand, the desired tolerances and part quality may change depending on the cutting tool feature, the clamping pressure of the workpiece and the machine feature. The purpose of this study is having knowledge based on experimental data and to determine optimum process parameters values for mass production conditions. For this purpose, by using design of experiment method, both the optimum levels were determined and relationship between the parameters were examined on the surface quality. The goal is to minimize the surface roughness value on the machined surfaces. A better surface has a possitive effect on the fatigue strength and corrosion resistance of the material. Especially for powertrains, slide bearings, pistons, sealing surfaces and control gauges a higher surface quality is desired. The desired surface roughness for the milling surface is Ra 3.2. Sampling length (l) and measurement length (ln) were selected as 5 and as 12.5 respectively. Measuring speed was selected as 1mm/sn. Apart from the process parameters, the rigidity of machine, the clamping pressure of the raw material, cutting tool geometry, run out of tool holder, wearing of cutting inserts, cutting method (tool path), cutting fluid are effective on the surface roughness. Another important factor for surface roughness is to determine the process parameters according to the hardness of the cutting tool. For example, higher cutting speeds are required with ceramic cutting tools, while using lower cutting speed with carbide cutting tools provides a better surface quality. In this study, experimental studies were carried out on the process parameters that effect the surface quality in machining. Cutting direction, cutting speed, feed per revolution and cutting depth were used as process parameters. As cutting direction; climbing and conventional milling, as cutting speed; 282 m/min, 314 m/min and 342 m/min as feed per revolution; 0.15 mm/rev, 0.40 mm/rev and 0.65 mm/rev as cutting depth; 0.2 mm, 0.5 mm and 0.8 mm were used. The selected values were taken from the used cutting tools catalog. Since finish milling is the last operation, experimental studies were carried out by changing machining parameters of Ø50 cutting tool. For rough milling operation, fixedly 1500 rpm and 0,8 mm/rev were selected as cutting conditions. Experiment parts were machined both in rough milling operations and in finish milling operations under dry condition. GG25 cast iron material was used as test material. In order to minimize effect of wearing cutting inserts on experiment results, rough and finish cutting inserts were changed before each experiment. Before the experiments, the run out of rough and finish tool was controlled with the help of the comprator. The Taguchi method was used in the experimental studies. Taguchi method aims the best results with minimum number of experiments and considers S/N ratios. Numerical experiment results are converted to S/N ratio. S means that, it can be controlled parameters such as cutting direction, cutting speed, feed rate and cutting depth for machining method. N means that, it can not be controlled parameters such as temperature, vibration and dust. The goal in Taguchi method is to minimize N values. Totally, Taguchi method involves 3 fuctions according to output type. These are larger is better, nominal is best and smaller is better. Since surface roughness output is desired to be minimum on the part, Taguchi's smaller is better function was used for this study. According to mixed Taguchi design (2^1x3^3) totally 18 experiments were performed at different levels of different factors. For all levels of all parameters, S/N ratios were found and the biggest S/N ratios were admitted optimum values. ANOVA was carried out in order to investigate the statistical significance of the factors and their effect on the experimental output. For every parameters, P value was found. Parameters of P value that is smaller than 0,05 were admitted statistically significant. The smaller P value, the more to reject the H0 hypothesis. H0 hypothesis means that, the parameter is not statistical significance on the experiment output. Additionally, the percentage effects of the parameters on the experiment output were determined. Depending on the cutting direction and feed per revolution, the regression equations were obtained. The estimated results of each experiment were calculated by Minitab 19 and the validity of the experimental model was investigated by comparing the estimated results with the actual experimental results. According to the optimum process parameters obtained by the Taguchi method, 10 validation experiments were carried out and the average results of the validation experiments were compared with the average estimated value obtained by Minitab 19, and the validity of the optimization study was investigated at the 95% confidence interval. Conventional cutting direction, 282 mm/min cutting speed, 0.15 mm/rev and 0.5 mm cutting depth were found as optimum results according to the Taguchi method. According to the ANOVA results, the most effective parameter on the surface quality was found feed per revolution as %53,11. All process parameters except cutting speed were found statistical significance on surface quality. As a result of the comparison of the estimated experimental results with the actual test results, the validity of the experimental model was found as %91.4. According to the results of the validation experiments performed with the optimum parameter values, the optimization study was found valid at the %95 confidence interval.Experiment results show that, the most important parameter on surface roughness is feed rate. As feed rate value decreases, lower surface roughness values are found. However, low feed rate value causes more wear on cutting inserts because inserts contact the workpiece longer time which means that, cost of cutting insert and machining time increase. Therefore, in order to determine process parameters for serial conditions, technical drawings must be analyzed well.