CHAPTER 5 OPTIMIZATION OF GREEN SAND CASTING PROCESS PARAMETERS USING TAGUCHI S METHOD

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1 66 CHAPTER 5 OPTIMIZATION OF GREEN SAND CASTING PROCESS PARAMETERS USING TAGUCHI S METHOD 5.1 PROCESS PARAMETERS OF GREEN SAND CASTINGS In this work, the robustness of the green sand casting process optimization using Taguchi s method and the basic steps for achieving the above target are summarized below, as explained by Sycros (2002): 1. Casting defects have been selected as the most representative quality characteristic in the green sand casting process, as it is related to many internal defects (shifts, sand inclusion, blow holes, sand drop, slag etc.). The target of the green sand casting process is to achieve lower casting defects by minimizing the effect of uncontrollable parameters. 2. The most critical parameters that cause variations in the quality characteristics are selected by using cause-and-effect matrix. 3. The green sand casting process is carried out under the experimental conditions, dictated by the chosen orthogonal array and parameter levels. Based on the experimental conditions, data are collected. 4. An analysis of variance (ANOVA) table is generated to determine the statistical significance of the parameters. Response graphs are plotted to determine the preferred levels for each parameter.

2 67 5. The optimum settings of the control parameters and the results of each of the parameters at their new optimum levels are predicted. 6. The effect of optimized settings in the predicted reduction in the casting defects is verified. A cause-and-effect matrix is drawn to identify the casting process parameters with respect to KPIV that may influence green sand casting defects, as shown in Table 4.3, Chapter 4. Cause-and-effect matrix relates the key inputs to the key outputs (customer requirements). The process parameters can be listed in six categories as follows: 1. Mould-machine-related parameters 2. Cast-metal-related parameters 3. Green-sand-related parameters 4. Mould-related parameters 5. Shake-out-related parameters 6. Man- process related parameters To visualize the effect of process parameters on the casting defects of cast iron flywheel castings, following parameters are selected: A. Moisture content B. Permeability C. Loss on ignition D. Compressive strength E. Volatile content F. Vent holes G. Pouring time H. Pouring temperature I. Mould pressure.

3 68 (A) The range of moisture content is taken as %, (B) the range of permeability , (C) the range of loss on ignition %, (D) the range of compressive strength number kg/cm 2, (E) the range of volatile content %, (F) the range of vent holes 8 10,(G) the range of pouring time sec,(h) the range of pouring temperature o C, and (I) the range of mould pressure 5 7kg/cm 2. The number of levels for each control parameter defines the experimental region. For each control factor, three levels are selected, out of which, one level is usually the starting level. The levels should be chosen sufficiently far to cover a wide experimental region because sensitivity to noise factors does not usually change with small changes in control factor settings. Therefore, each parameter is analyzed at different levels based on the behavior of the process parameters. From the selected parameters, the significant interaction between them is also considered. The selected green sand casting process parameters, along with their ranges, are given in Table 5.1. Table 5.1 Process parameters with their ranges and values at three levels Parameter designation Process parameters Range Level 1 Level 2 Level 3 A Moisture content (%) B Permeability C Loss on Ignition (%) D Compressive strength (kg/cm 2 ) E Volatile content (%) F Vent holes (No s) G Pouring Time (sec) H Pouring temperature ( C) I Mould pressure (kg/cm 2 )

4 TAGUCHI ANALYSIS Selection of Orthogonal Array Experience reveals that nonlinear behavior among the parameters of a sand casting process can only be determined if more than two levels of parameters are used, as explained by Masters et al (1999). Before selecting a particular OA to be used for conducting the experiments, two points must be considered. (1) The number of parameters and interaction of interest. (2) The number of levels for the parameters of interest From the selected parameters, the significant interactions between them are to be considered. As per the study conducted to know the parameter interactions by Ross (1988), it is inferred that there are significant interactions of moisture content with permeability and moisture content with loss on ignition. Therefore, based on the literatures and the synthesized data of the foundry with the foundry man experience, moisture content variation with the permeability of the sand (A B), and the moisture content variation with the loss on ignition of the sand (A C) are taken to investigate the two factor interaction effects on casting rejection. The total Degree of Freedom (DOF) for nine parameters each at three levels and two second order interaction is 26 = (9 (3 1) + 2(2 2)). Hence, a three level OA, with at least 26 DOFs, has to be selected. The L27 OA having 26 DOFs is selected for this work. The results indicate that the selected process parameters significantly affected the casting defects of cast iron flywheel castings. A confirmation run is used to verify the results, which indicated that this method is more efficient in determining the best casting parameters for flywheel castings.

5 70 The parameters and parameter generations are assigned to a particular column of the selected OA. The assigned experimental array is shown in Table 5.2. The castings of flywheel are made as per the trial conditions given in Table 5.2. The experiments are conducted thrice for the same set of parameters using single repetition randomization technique given by Ross (1988) and Montgomery (1997). The percentage of defect for each repetition and average casting defects are calculated for each trial condition. Table 5.2 Experimental L27 orthogonal array Trail No. Moisture content (%) Permeability Loss on Ignition (%) Compressive strength (kg/cm 2 ) Volatile content (%) Vent holes (No s) Pouring Time (sec) Pouring temp ( 0 C) Mould pressure (kg/cm 2 )

6 71 The casting defects are the lower the better type of quality characteristics. Lower the better S/N ratios are computed for each of the 27 trials given in Table 5.3. Taguchi method uses the S/N ratio instead of the average to convert the trial result data into a value for the characteristic in the optimum setting analysis. The S/N ratio replicates both the average and the variation of the quality characteristics. For the case of minimizing the performance characteristic, S/N ratio can be calculated as given in Equation (5.1): N I 2 i 10log i / i I 1 SN Y N (5.1) where Y i is the response value of observation in ith test and N i the number of trials in ith test. For example, for trial no. 1, the S/N ratio is: S/N ratio = -10 log [( )/ 3)] = The mean response referring to the average value of the performance characteristics for each parameter at different levels is calculated and given in Table 5.4. Table 5.3 Average casting defects and S/N ratio against trail numbers Sl.No Trial 1 Trial 2 Trial 3 Average S/N Ratio

7 72 Table 5.3 (Continued) Sl.No Trial 1 Trial 2 Trial 3 Average S/N Ratio Table 5.4 Average values of casting defects and S/N ratios at different levels Level 1 Level 2 Level 3 Factors Casting defects S/N Ratios Casting defects S/N Ratios Casting defects S/N Ratios A B C D E F G H I

8 SUMMARY The Taguchi process optimization procedures and casting process parameters are given in this chapter. The parameter range and levels are given for Taguchi analysis. The selection of orthogonal array and Experimental L27 orthogonal array table using by Minitab software are given. The Average casting defects and S/N ratio against trail numbers and Average values of casting defects and S/N ratios at different levels for the parameters are also given. The detailed result analysis given in the chapter 10.