_________________________________________ *Corresponding author e-mail: pathiyasseril@yahoo.com ISSN: 2180-1053 Vol. 8 No. 2 July – December 2016 81 OPTIMIZATION OF RESISTANCE SPOT WELDING PROCESS PARAMETERS USING MOORA APPROACH P.Sreeraj1* 1Laxmi Department of Mechanical Engineering, YOUNUS College of Engineering and Technology, Kollam, Kerala, India- 691010. ABSTRACT Efforts Optimization of resistance spot welding (RSW) process parameters was carried out to obtain optimal parametric combination to yield favorable weld nugget diameter, heat affected zone (HAZ) and breaking load in AISI 316 L austenitic stainless steel plates. Taguchi’s L16 orthogonal array (OA) design and signal- to- noise ratio (S/N ratio) have been used in this study. Weld nugget diameter, heat affected zone (HAZ) and breaking load are selected as objective functions. In this case the multi objective optimization on the basis of ratio analysis (MOORA) is applied to solve this multi objective, problem. MOORA in combination with standard deviation (SDV) was used for optimization process. Standard deviation (SDV) was used to determine the weights that were used for normalizing the responses obtained from the experimental results. It was found that welding current of 14 kA, welding time 14 cycle, electrode force 200Kgf and holding time 10 cycle produced the weldment with the best mechanical properties. This method can be used successfully in other welding applications. KEYWORDS: RSW; SDV; Orthogonal array; MOORA; HAZ 1.0 INTRODUCTION Resistance spot welding (RSW) is a multi factor, multi objective metal joining process, in which several process control parameters interact in a complicated manner and influence quality of weld. In most resistance spot welding (RSW) the weld quality is judged by nugget size, heat affected zone (HAZ) and joint strength. So it is important to select the welding process parameters to get the desired quality of the weld. Usually, the selection of the desired process parameters is selected by trial and error. This is time consuming costly and may not be accurate. This does not ensure optimum weld nugget and other properties to ensure a proper weld. In order to overcome this problem various optimization techniques are used so that a perfect relationship between input and output variables can be developed using mathematical relationship so that desired output can be predicted. There are many research work done in modelling and process optimization in RSW and other welding process like gas metal arc welding (GMAW) flux cored arc welding (FCAW) and Tungsten inert gas welding (TIG). Thakur and Nandedkar presented a systematic approach to determine effect of process parameters on tensile shear strength of Journal of Mechanical Engineering and Technology 82 ISSN: 2180-1053 Vol. 8 No. 2 July– December 2016 resistance weld joining of austenitic stainless steel AISI 304 using Taguchi method (Thakur & Nandedkar, 2010). Joseph, William and Odinikuku (2015) optimized gas metal arc welding parameters using MOORA approach. Norasiah, Yupiter, Manurung and Hafidzi (2012) optimized resistance spot welding parameters towards development of weld nugget zone and heat affected zone (HAZ) using multi objective Taguchi method (MTM). In this study Taguchi method coupled with SDV-MOORA method was used to optimize the welding process parameters used for resistance spot welding on AISI 316 L austenitic steel plates. SDV was standard deviation method used for determining the weight attached to each mechanical property. The traditional Taguchi method cannot solve multi-objective optimization problems. In order to overcome this difficulty, the Taguchi method coupled with MOORA analysis used to solve the optimization problem in this study. 2.0 MOORA METHOD Since standard deviation is applied to this study for unbiased allocation of weights. The importance of weights in solving multi criteria decision making (MCDM) cannot be over emphasized .to determine the standard deviation the range standardization wad done using Equation (1) to transform different scales and units among various criteria in to common measurable units in order to compute weights. 𝑋𝑖𝑗 𝑖 = 𝑋𝑖𝑗−𝑚𝑖𝑛𝑋𝑖𝑗 𝑚𝑎𝑥𝑋𝑖𝑗−𝑚𝑖𝑛𝑋𝑖𝑗 (1) Where max Xij , min Xij are the maximum and minimum values of criterion (j) respectively. The standard deviation is calculated for every criterion using equation (2). SDVj =√ 1 𝑚 ∑ (𝑋𝑖𝑗 − 𝑋𝑗 𝑖̅̅ ̅)𝑚𝑖=1 2 (2) Where 𝑋𝑖𝑗 𝑖̅̅ ̅̅ is the mean of jth criterion after normalization and j=1, 2 ...n .After calculating for SDV for all criteria the next step is to determine the weights Wj of criteria considered using equation (3). Wj = 𝑆𝐷𝑉𝑗 ∑ 𝑆𝐷𝑉𝑗 𝑛 𝑗=1 (3) Where i=1...m; j=1 ...n. The multi objective optimization on the basis of MOORA method starts with a decision matrix as shown in equation (4): Optimization of Resistance Spot Welding Process Parameters Using Moora Approach ISSN: 2180-1053 Vol. 8 No. 2 July – December 2016 83 D = 𝐴1 𝐴2 𝐴3 ⋮ ⋮ 𝐴𝑛 1 2 3 11 12 13 1 21 22 23 2 31 32 33 3 1 2 3 n n n n m m m mn c c c c x x x x x x x x x x x x x x x x                    (4) Step 1: Compute the normalized decision matrix by vector method defined by equation (5) 𝑋𝑖𝑗 𝑖 = 𝑋𝑖𝑗 √∑ 𝑋𝑖𝑗 2𝑚 𝑖=1 (5) Where i=1.....m; j=1...m Step 2; calculate the composite score as expressed in equation (6) 𝑍𝑖 =∑ 𝑋𝑖𝑗 𝑖𝑏 𝑗=1 - ∑ 𝑋𝑖𝑗 𝑖𝑛 𝑗=𝑏+1 ; where i=1 ...m (6) Where ∑ 𝑋𝑖𝑗 𝑖𝑏 𝑗=1 and ∑ 𝑋𝑖𝑗 𝑖𝑛 𝑗=𝑏+1 are the benefit and non benefit criteria respectively .If there are some attributes more important than others, the composite score becomes as expressed in equation (7). 𝑍𝑖 = ∑ 𝑤𝑗 𝑏 𝑗=1 𝑋𝑖𝑗 𝑖 -∑ 𝑤𝑗 𝑛 𝑗=𝑏+1 𝑋𝑛 𝑖 i=1...m (7) Where, Wj is the weight of the Jth criterion. Step 3: Rank the alternatives in descending order. 3.0 EXPERIMENTATION The sheets were cut parallel to the rolling direction. The dimension of austenitic stainless steel plate of grade AISI 316 L sheet are 140 mm length (L), 40 mm width (w) and 1 mm thick (t) shown in Figure 1. Overlap is equal to width of the sheet as per AWS standard. Sheet surfaces were chemically cleaned by acetone before resistance spot welding to eliminate surface contamination. The properties of base metal are shown in Table 1. Figure 1 shows Kirperker RSW welding machine and Fig. 2 shows sample specimen. Journal of Mechanical Engineering and Technology 84 ISSN: 2180-1053 Vol. 8 No. 2 July– December 2016 Figure 1. Kirperker RSW welding machine Table 1 Chemical Composition of Base Metal Elements, Weight % Material C SI Mn P S Al Cr Mo Ni 316 L 0.030 0.75 2 0.045 0.03 - - - 0.1 Figure 2. Dimension of specimen 4.0 PLAN OF INVESTIGATION The research work is carried out in the following steps (Tarng & Yang, 1998). 1. Identifying the quality characteristics and process parameters to be evaluated. 2. Determine the number of levels for the process parameters and possible interactions between process parameters. 3. Select appropriate orthogonal array and assign process parameters to the orthogonal array. 4. Conduct experiment as per arrangement of orthogonal array. Optimization of Resistance Spot Welding Process Parameters Using Moora Approach ISSN: 2180-1053 Vol. 8 No. 2 July – December 2016 85 5. Define problem. 6. Selection of alternatives. 7. Selection of the criteria describing alternatives. 8. Determination of criteria values. 9. Normalization of Matrix. 10. Determination of complex rationality. 11. Ranking alternatives. 4.1 Identification of factors and responses The weld nugget size, HAZ and breaking load has a significant effect on quality of resistance spot welding. The properties of the welding is the significantly influenced by diameter of weld nugget obtained. Hence control of nugget diameter is important in resistance spot welding where a low diameter is highly desirable. The chosen factors have been selected on the basis to get minimal weld nugget diameter, low HAZ and higher breaking load. These are current, hold time; weld time and electrode force. The responses chosen were weld nugget diameter, HAZ and breaking load. The responses were chosen based on the impact of parameters on final composite model (Gunaraj & Murugan, 1999). 4.2 Finding the limits of process variables Working ranges of all selected factors are fixed by conducting trial run. This was carried out by varying one of factors while keeping the rest of them as constant values. Working range of each process parameters was decided upon by inspecting the smooth appearance without any visible defects. The chosen level of the parameters with their units and notation are given in Table 2. Table 2. Welding Parameters and their Levels Parameters Factor Levels Unit Notation 1 2 3 4 Welding Current KA I 8 10 12 14 Welding Time cycle T 10 12 14 16 Electrode Force Kgf F 180 200 220 240 Holding Time cycle C 10 20 30 40 Journal of Mechanical Engineering and Technology 86 ISSN: 2180-1053 Vol. 8 No. 2 July– December 2016 4.3 Development of orthogonal array Design matrix chosen to conduct the experiments was Taguchi’s orthogonal design. The design matrix comprises of L16 orthogonal array. Sixteen experimental trails were conducted that make the estimation of nugget diameter, HAZ and breaking load (Vermal et al., 2014). Figure 3. Scanned specimens Table 3. Design Matrix Trial Number Design Matrix I T F C 1 1 1 1 1 2 1 2 2 2 3 1 3 3 3 4 1 4 4 4 5 2 1 2 3 6 2 2 1 4 7 2 3 4 1 8 2 4 3 2 9 3 1 3 4 10 3 2 4 3 11 3 3 1 2 12 3 4 2 1 13 4 1 4 2 14 4 2 3 1 15 4 3 2 4 16 4 4 1 3 Optimization of Resistance Spot Welding Process Parameters Using Moora Approach ISSN: 2180-1053 Vol. 8 No. 2 July – December 2016 87 I - Welding current; T - Welding time; F – Electrode force; C – Hold time 4.4 Conducting experiments as per orthogonal array In this work sixteen experimental run were allowed as per orthogonal array correspond to each treatment combination of parameters on weld nugget diameter, HAZ and breaking load as shown Table 3 at random. At each run settings for all parameters were disturbed and reset for next deposit. This is very essential to introduce variability caused by errors in experimental set up. Figure 4. Welded specimen 4.5 Recording of Responses For measuring the weld nugget diameter, Toolmakers microscope is used. For conducting tensile test specimens were prepared as per ASI 40 and specimen figure is shown in Fig 2. The tensile test is conducted in a UTM at Younus College of engineering technology, kollam, Kerala India. The observed values are shown in Table 4. The tensile-shear test is the most widely used test for evaluating the spot weld mechanical behaviours in static condition. Peak load, obtained from the tensile-shear load displacement curve, describes mechanical behaviour of spot welds. Figure 3 shows scanned specimen and Fig. 4 shows welded specimen. Journal of Mechanical Engineering and Technology 88 ISSN: 2180-1053 Vol. 8 No. 2 July– December 2016 Table 4. Design Matrix and Observed Values of Weld Nugget Diameter, HAZ and Max breaking load Table 5. Weights assigned to criteria Property SDVj Wj Weld Nugget Diameter(mm) 0.28739 0.199576 Max breaking load in KN 0.56175 0.390104 HAZ (mm) 0.59278 0.411653 Trial No. Design Matrix Bead Parameters I T F C Weld Nugget Diameter(mm) Max breaking load in KN HAZ (mm) 1 1 1 1 1 7.306 18.81 1.072 2 1 2 2 2 8.243 19.54 0.8734 3 1 3 3 3 7.731 20.67 1.125 4 1 4 4 4 8.925 21.93 0.9238 5 2 1 2 3 8.792 18.44 0.8475 6 2 2 1 4 8.415 19.77 1.2581 7 2 3 4 1 6.777 19.18 0.8945 8 2 4 3 2 8.614 20.59 0.9765 9 3 1 3 4 8.908 21.53 1.1498 10 3 2 4 3 7.371 19.39 0.805 11 3 3 1 2 8.087 18.43 1.1689 12 3 4 2 1 8.112 20.52 0.986 13 4 1 4 2 9.125 19.42 1.0255 14 4 2 3 1 8.753 17.56 1.072 15 4 3 2 4 8.971 20.69 0.8734 16 4 4 1 3 8.807 19.24 1.125 Optimization of Resistance Spot Welding Process Parameters Using Moora Approach ISSN: 2180-1053 Vol. 8 No. 2 July – December 2016 89 Table 6. The square value of Xij Table 7. Normalized weld parameters Bead Parameters Weld Nugget Diameter(mm) Max breaking load in KN HAZ(mm) 1 53.37764 353.8161 1.787569 2 67.94705 381.8116 1.505529 3 59.76836 427.2489 0.880219 4 79.65563 480.9249 1.149184 5 77.29926 340.0336 0.762828 6 70.81223 390.8529 1.265625 7 45.92773 367.8724 0.853406 8 74.201 423.9481 0.718256 9 79.35246 463.5409 1.582816 10 54.33164 375.9721 0.80013 11 65.39957 339.6649 0.953552 12 65.80454 421.0704 1.32204 13 83.26563 377.1364 0.648025 14 76.61501 308.3536 1.366327 15 80.47884 428.0761 0.972196 16 77.56325 370.1776 1.05165 ∑ 𝑿𝒊𝒋 𝟐 𝒏 𝒊=𝟏 1111.8 9468.941 17.6193 √∑ 𝑋𝑖𝑗 2 𝑛 𝑖=1 33.343 97.308 4.1975 Bead Parameters Weld Nugget Diameter Max breaking load HAZ 1 0.219116 0.193304 0.318523 2 0.247218 0.200806 0.292317 3 0.231863 0.212418 0.223514 4 0.267672 0.225367 0.25539 5 0.263684 0.189501 0.208076 6 0.252377 0.203169 0.268017 7 0.203251 0.197106 0.220083 8 0.258345 0.211596 0.201906 Journal of Mechanical Engineering and Technology 90 ISSN: 2180-1053 Vol. 8 No. 2 July– December 2016 Table 8. Clustered weld properties according to criteria 9 0.267163 0.221256 0.299726 10 0.221066 0.199264 0.213103 11 0.24254 0.189399 0.232638 12 0.243289 0.210877 0.273925 13 0.273671 0.199572 0.191781 14 0.262514 0.180458 0.278475 15 0.269052 0.212624 0.234902 16 0.264133 0.197723 0.244312 Weights wj 0.333844 0.66155 0.411653 NUMBERS (Maximum) (Minimum) (Minimum) Max breaking load in KN Weld Nugget Diameter(mm) HAZ (mm) 1 0.12788 0.073159 0.131121 2 0.132843 0.082542 0.120333 3 0.140525 0.077415 0.09201 4 0.149092 0.089371 0.105132 5 0.125364 0.08804 0.085655 6 0.134406 0.084265 0.11033 7 0.130395 0.067862 0.090598 8 0.139981 0.086257 0.083115 9 0.146372 0.089201 0.123383 10 0.131823 0.07381 0.087725 1 0.125297 0.08098 0.095766 12 0.139506 0.08123 0.112762 13 0.132027 0.091374 0.078947 14 0.119382 0.087649 0.114635 15 0.140661 0.089832 0.096698 16 0.130804 0.08819 0.100572 Optimization of Resistance Spot Welding Process Parameters Using Moora Approach ISSN: 2180-1053 Vol. 8 No. 2 July – December 2016 91 Table 9 Ranking step 5.0 RESULT ANALYSIS In this study the weight allocation for each output parameters, that is, the weld mechanical properties were determined. In determining the weights the range of standardized decision matrix is determined using equation (1). Table 5 shows allocated weight. By applying the equation (5) Table 6 and Table 7 created. Next step is to multiply the allocated weights to the values in Table 7.This leads to the creation of table 8.The last step is to sum the parameters comparing higher the better and smaller the better values and Table 9 is created and then parameters are ranked. Rank Number one determines the optimized condition. The nugget diameter considered in this study range from 6.7 mm to 9.2 mm. Applying MOORA method the selected parameters produced a weld with nugget diameter 7.7 mm. Breaking load considered in this study is within the range of 17.5 KN to 22 KN .By applying The MOORA method penetration is found to be 20.6 KN. HAZ considered in this study range from 1.2 mm to 0.8 mm. Applying MOORA method the selected parameters produced a weld with HAZ 1.072 mm. Bead Parameters No ∑ 𝒎𝒂𝒙 ∑ 𝒎𝒊𝒏 ∑ 𝒎𝒂𝒙 -∑ 𝒎𝒊𝒏 Rank 1 0.12788 0.20428 -0.0764 16 2 0.132843 0.202875 -0.07003 15 3 0.140525 0.169425 -0.0289 3 4 0.149092 0.194503 -0.04541 9 5 0.125364 0.173695 -0.04833 8 6 0.134406 0.194595 -0.06019 13 7 0.130395 0.15846 -0.02807 2 8 0.139981 0.169372 -0.02939 4 9 0.146372 0.212584 -0.06621 14 10 0.131823 0.161535 -0.02971 5 11 0.125297 0.176746 -0.05145 10 12 0.139506 0.193992 -0.05449 11 13 0.132027 0.170321 -0.03829 6 14 0.119382 0.202284 -0.0829 1 15 0.140661 0.18653 -0.04587 7 16 0.130804 0.188762 -0.05796 12 Journal of Mechanical Engineering and Technology 92 ISSN: 2180-1053 Vol. 8 No. 2 July– December 2016 Figure 5. Weld structure of optimized model For this study weld sample 14 produced optimum weld. From Table 3 It was found that welding current of 14 kA, welding time 14 cycle, electrode force 200Kgf and holding time 10 cycle produced the weld with the best mechanical properties. I4T2F3C1 is the optimum process parameters obtained from this study.Fig 5 represents the optimized condition. 6.0 CONCLUSIONS In this study, a detailed methodology of MOORA technique has been presented for evaluating the nugget diameter, maximum breaking load and, HAZ and parametric combinations in resistance spot welding process. For achieving optimal parametric combination to get minimum nugget diameter, minimum HAZ and maximum breaking load of the weldment produced by resistance spot welding a multi objective optimization process is used. Taguchi method coupled with MOORA analysis is very popular and efficient method for optimization that can be performed with limited number of runs. However standard deviation was used to determine the weights allocated to each value of mechanical property utilized in the course of running MOORA process. It is here by concluded that MOORA method has successfully optimized the process parameters considered in this study and microstructure of the optimized weldment agree that optimization result produced confirm the quality of the weldment. Optimization of Resistance Spot Welding Process Parameters Using Moora Approach ISSN: 2180-1053 Vol. 8 No. 2 July – December 2016 93 ACKNOWLEDGEMENTS Authors sincerely acknowledge the help and facilities extended to them by the Department of Mechanical Engineering, YOUNUS college of Engineering and Technology, Kollam, India. REFERENCES Gunaraj, V. & Murugan, N. (1999). Prediction and comparison of the area of the heat effected zone for the bead on plate and bead on joint in SAW of pipes, Journal of Material Processing Technology, 95, 246 - 261. 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(2014). Resistance Welding of Austenitic Stainless Steels (AISI 304 with AISI 316) 3, The 5th International & 26th All India Manufacturing Technology, Design and Research Conference (AIMTDR 2014) December 12th -14th, 2014, IIT Guwahati, Assam, India. Journal of Mechanical Engineering and Technology 94 ISSN: 2180-1053 Vol. 8 No. 2 July– December 2016