l818 G Mohanty et al. /Materials Research Bulletin 43(2008)1814-1828 Table 2 Experimental matrix(according to standard order Standard Experiment Concentration Electrode separation tion Weight deposited order potential (V) Actual Coded Coded Actual Coded 6 150 16 150 23456789 0 4.15 0 18 11 - 5835 300 43.975 0 18975 10 123456789 37240857429 000000000000 1111111110000 3113311332222 150 150 150 3333332 63.225 38.025 28525 0000 11110000 0000 38.025 Error in repeating experimental trials from the same suspension Suspension Weight deposited %o Difference in deposit Deposit 1 38.02 38.125 0.100 0.26 39.32 1625 response data and are generally used for three purposes: (i) stabilizing response variance, (ii) making the distribution of the response variable closer to the normal distribution, and (iii) improving the fit of the model to the data [27 Transforming the response will make a difference only if the ratio of the maximum response to the minimum response is large. A ratio greater than 10 usually indicates that a transformation is required. Since the ratio of the maximum response to the minimum within the design space was 38.85, we applied a square transformation as suggested by the Box-Cox plot The EFFECT of a factor is the change in the response produced by a change in the level of the factor. The total number of effects in a 2 factorial design is 15. There are four main effects namely A-D which are due to variation of a single factor at a time. There are ll interaction effects namely AB, AC, AD, BC, BD, CD, ABC, ABD, CD, BCD and ABCD that are due to variation in two or more factors, simultaneously. An interaction occurs when the effect of one factor depends on the level of another factor. The interaction effects are generally different from sum of the effects expected from either factor alone. The effects along with their contribution towards the response is summarized in Tables 4a and 4b. Concentration contributes more towards the weight of the alumina deposited than all other effects combined together (more than 50%0). Other major contributing factors are deposition time, applied potential andresponse data and are generally used for three purposes: (i) stabilizing response variance, (ii) making the distribution of the response variable closer to the normal distribution, and (iii) improving the fit of the model to the data [27]. Transforming the response will make a difference only if the ratio of the maximum response to the minimum response is large. A ratio greater than 10 usually indicates that a transformation is required. Since the ratio of the maximum response to the minimum within the design space was 38.85, we applied a square transformation as suggested by the Box–Cox plot. 2.5. Effects The EFFECT of a factor is the change in the response produced by a change in the level of the factor. The total number of effects in a 24 factorial design is 15. There are four main effects namely A–D which are due to variation of a single factor at a time. There are 11 interaction effects namely AB, AC, AD, BC, BD, CD, ABC, ABD, CD, BCD and ABCD that are due to variation in two or more factors, simultaneously. An interaction occurs when the effect of one factor depends on the level of another factor. The interaction effects are generally different from sum of the effects expected from either factor alone. The effects along with their contribution towards the response is summarized in Tables 4a and 4b. Concentration contributes more towards the weight of the alumina deposited than all other effects combined together (more than 50%). Other major contributing factors are deposition time, applied potential and 1818 G. Mohanty et al. / Materials Research Bulletin 43 (2008) 1814–1828 Table 2 Experimental matrix (according to standard order) Standard order Experiment order Concentration (% w/v) Electrode separation (cm) Applied potential (V) Deposition time (min) Weight deposited (mg/cm2 ) Actual (x1) Coded (X1) Actual (x2) Coded (X2) Actual (x3) Coded (X3) Actual (x4) Coded (X4) 1 6 10 1 1 1 150 1 1 1 10.45 2 16 30 1 1 1 150 1 1 1 37.425 3 3 10 1 3 1 150 1 1 1 4.15 4 9 30 1 3 1 150 1 1 1 24.175 5 18 10 1 1 1 300 1 1 1 14.7 6 11 30 1 1 1 300 1 1 1 58.35 7 5 10 1 3 1 300 1 1 1 9.975 8 13 30 1 3 1 300 1 1 1 43.975 9 7 10 1 1 1 150 1 3 1 18.975 10 12 30 1 1 1 150 1 3 1 99.9 11 4 10 1 3 1 150 1 3 1 14.15 12 10 30 1 3 1 150 1 3 1 63.225 13 8 10 1 1 1 300 1 3 1 38.025 14 15 30 1 1 1 300 1 3 1 161.225 15 17 10 1 3 1 300 1 3 1 28.525 16 14 30 1 3 1 300 1 3 1 106.85 17 2 20 0 2 0 225 0 2 0 38.125 18 19 20 0 2 0 225 0 2 0 40.95 19 1 20 0 2 0 225 0 2 0 38.025 20 20 20 0 2 0 225 0 2 0 39.325 Table 3 Error in repeating experimental trials from the same suspension Suspension Weight deposited Difference % Difference in deposit Deposit 1 Deposit 2 Suspension 1 38.025 38.125 0.100 0.26 Suspension 2 40.95 39.325 1.625 3.96 Maximum difference between replicates = 7.14%.