Abstract: Mechanical components as well as different structures exposed to hostile environment get corroded over a period of operation. To prevent failure of them, appropriate servicing and maintenance need be undertaken involving related cost to incur. Among different steps usually adopted to protect components or structures from the adverse effect of their surroundings, cladding is used widely maintaining economy. In the present work, an MCDM (multi-criteria decision making) technique, namely the Analytic Hierarchy Process (AHP), is employed for optimizing cladding process using duplex stainless steel electrode to clad low alloy steel flats utilizing Gas Metal Arc Welding (GMAW) under different heat input values. To achieve both high corrosion resistance and productivity, the AHP is applied, and optimal process parameters are evaluated that may be recommended for practice.
Keywords: welding, cladding, GMAW, duplex stainless steel, corrosion resistance, MCDM, AHP, Analytic Hierarchy Process.
1. Introduction
Cladding is a well established surface treatment process for modifying surface of a component or structure exposed to harmful environment by applying a layer of a wear-resistive alloy on it. These alloys are rich in some elements that promote growth of certain phases to resist the effect of hostile environment, thereby increasing their service life and reducing cost of maintenance or replacement. Among various processes which are used for cladding, arc welding is used frequently by welding industries [1,2]. And, Gas Metal Arc Welding is widely employed for cladding.
There is a considerable impact of various process parameters, specially heat input, on weld bead attributes which decide the standard of the clad layer obtained. Hence, proper selection of process parameters is the key for obtaining a defect free good quality clad layer. Optimal selection of process parameters in GMAW was tried by many researchers [1-8] to obtain good quality weld.
Use of austenitic stainless steel [9-12] as well as duplex stainless steel [13-16] as clad material was explored regarding their effect on anti-corrosive property. Duplex stainless steel was reported to impart superior corrosion resistance compared to different grades of austenitic stainless steels.
MCDM (multi-criteria decision making) techniques are well used to find out optimal solutions to various types of problems having two or more criteria that often put some difficulty to optimize. Among different MCDM techniques, the Analytic Hierarchy Process (AHP) is a simple, but powerful tool to solve such problems as introduced by Saaty [17,18]. After its introduction, the AHP was applied [5,8,19-25] in varying areas including different welding processes successfully.
In this work, the objective is to optimize duplex stainless steel cladding process employing gas metal arc welding with 100% CO2 gas shield. The Analytic Hierarchy Process is used to find out the optimum cladding considering corrosion resistance and productivity.
2. Experimental Work
Experiment is done in using an ESAB, India made GMAW machine under 100% CO2 gas shield. The welding gun is mounted on a motor driven vehicle. Flow rate of CO2 is kept at 18 litre/min. Low alloy steel flats of the size 100mm× 50mm× 6mm are taken as the base metal. The overlap of two successive beads is taken as 50%. The base metal used had 0.076%C, 0.138%Si and 0.343%Mn, while duplex stainless steel filler wire (E2209T0-1) had 0.020%C, 22.52%Cr, 9.09%Ni, 2.91%Mo, 1.01%Mn, 0.76%Si and 0.125%N. Duplex stainless steel has almost equal proportion of ferrite and austenite phases and it is known to provide good corrosion resistance under hostile atmosphere. Thus under severe corrosive atmosphere, electrode wire material is expected to offer much resistance against general and pitting corrosion compared to that of the base plate.
Accelerated corrosion test is done on the cladding using a solution of anhydrous ferric chloride, hydrochloric acid, and distilled water. Only the clad portions of the test specimens are exposed to the solution and the rest is masked with teflon. Each sample is immersed in 33ml of the solution for 24 hours.
3. Results and Discussion
In Table 1, process parameters with the respective heat input for the experiments conducted are shown. Table 2 indicates that experiment run 4 gives lower corrosion rate than the other runs. This corresponds to a moderate heat input of 0.38 kJ/mm. At the heat input of lower and higher values than this, corrosion rate is found to be higher. At a high heat input of 0.45 kJ/mm, quite a high rate of corrosion (0.499 kJ/mm) is observed. Overheating due to high input may have resulted in this low corrosion resistance than that at somewhat low heat input. Again, at a quite low heat input, there may be insufficient heating leading not to have favourable duplex phases of austenite and ferrite in the clad portion.
Table 1 Heat input used for weld cladding with 6 passes.
Table 2 Corrosion rate of clad portion
4. Application of the AHP for Appropriate Selection of Process Parameters to Obtain Optimum Cladding
4.1 The Analytic Hierarchy Process
The analytical hierarchy process (AHP) is an MCDM (multicriteria decision making) technique introduced by T.L. Saaty. It is a simple but powerful optimizing tool. In the analytical hierarchy process (AHP), the hierarchy structure is first constructed. At the top level of the hierarchy, the goal or the objective of the decision is kept. Next the criteria and decision alternatives are put in descending levels [17,18]. In an exampleof hierarchy structure, as shown in Fig. 1, the goal is selected first. The chosen alternatives are placed at the bottom. There are different criteria based on which the suitable alternatives are to be selected.
Fig. 1: An example of hierarchy structure.
The pair wise comparison matrices are constructed by comparing an element with the elements of the next higher level. This helps to find out the local priority weights. A typical pair wise comparison matrix is shown in Equation (1).
Here, aij (for i,j = 1,2,3……..n) is the strength of preferences for the alternative Ei over Ej corresponding to the criterion (C), aji = 1/aij and aii = 1 for all values of i and j.
The numerical values of aij are obtained from the ratio scale (Table 3). When all the elements of the matrix are selected, it is checked if the matrix is consistent or not. A comparison matrix is known as consistent if
aij*ajk= aik, for all values of i, j and k. (2)
Table 3: Ratio Scale of Comparison Matrix.
For all consistent matrix, aij= wi/wj (3)
for all the values of i and j, where w is the priority weight.
If alternative E1 is equally or moderately preferred over alternative E2, and E2 has a strong preference over E3, then the strength of preference of E1 alternative over E3 alternative, a13 is given by,
a13 = w1/w3 = (w1/w2)*(w2/w3) = a12*a23. (4)
Hence, a13 = 2*5 = 10, where a12 = 2 and a23 = 5. But the value of a13 cannot be 10 as the highest value in this scale is 9 (Table 3). So, these elements in the comparison matrix and also the matrix as well are inconsistent.
In reality, matrix A is hardly found to be consistent. In that case the priority weight is calculated by solving the equation as given:
Aw = λm*w (5)
where w = (w1, w2, w3,………)T, λm ≤ n and λm is the largest eigen
value of the matrix A.
On the other hand, if the matrix become inconsistent, Eq.(5) would be simplified to
Aw = n*w. (6)
For an inconsistent matrix, the inconsistency is measured by consistency index (CI).
CI = (λm-n)/(n-1). (7)
A random index (RI) is also evaluated which is consistency index of a matrix, the elements of which are selected randomly from (1/9, 1/8, 1/7, ……..1.……..7, 8, 9) scale. The ratio (CI/RI) is known as consistency ratio (CR). A consistency ratio of 10% or less is acceptable.
Local weights, wi can be evaluated by solving the equation:
If Pj (j = 1,2,3,…….m) are the priority weights of n alternatives with respect to the jth criterion, then global weights (ri) of the alternatives are determined as
The largest value of the global weight is usually considered the optimum value, and the corresponding alternative is the decision [5,8,17,18].
4.2. Finding out the Optimal Condition for Weld Cladding
The data from the experiments on cladding performance of flux cored duplex stainless steel wire electrodes using GMAW on base plate of low alloy carbon steel are utilized to find out the optimum parametric condition. The AHP is applied for this purpose.
Here the goal is to find out the condition for obtaining the best corrosion resistant cladding maintaining productivity represented by torch travel speed, or also known as weld speed. Weld speed (S), heat input (HI), and pitting corrosion rate (C) are chosen as the selection criteria. Here it is considered that it would be better to have a lesser welding speed, more heat input and lesser pitting corrosion rate. There are 4 alternatives as 4 sets of experimental results are there. The hierarchy structure chosen for this work is shown Fig. 2.
Fig. 2: The hierarchy structure.
Now the pair-wise comparison matrix for the three criteria with respect to the goal is constructed in a similar way as done before. Strength of preferences is taken from the ratio scale as shown in Table 3. Local weights are obtained by normalising the geometric means of strength of preferences of each criterion over the other with respect to the goal. Table 4 shows pair-wise comparison matrix for crireria corresponding to the goal considered. Maximum Eigen value calculated, λm is 3.087982 and consistency ratio, CR is found out to be 0.013674 which is quite less than 10% indicating this matrix to have acceptable extent of consistency.
Table 4: Pair-wise comparison matrix for crireria
λm= 3.087982, CR= 0.013674.
Now, the pair-wise comparison matrices (Table 5 through Table 7) for all the four alternatives for each criterion are constructed by choosing suitable degree of preference of one alternative over the other for a particular criterion. Strength of preferences is taken from the ratio scale as shown in Table 3 similar to that of criteria matrix. Local weight for each alternative is calculated corresponding to a criterion. In each of the three pair-wise comparison matrices for alternatives, consistency ratio, CR is found out to be quite less than 10% (0.10) indicating this matrix to have acceptable level
Table 5: Pair-wise comparison matrix for alternatives for criterion 1 (Weld speed)
λm= 4.13422, CR= 0.008817.
Table 6: Pair-wise comparison matrix for alternatives for criterion 2 (Heat input)
λm= 4.212665, CR= 0.014848.
of consistency. After evaluating the pair-wise comparison matrix for criteria and pair-wise comparison matrices for alternatives, global weights for each alternative are to be calculated.
Table 7: Pair-wise comparison matrix for alternatives for criterion 3 (Pitting corrosion rate)
λm= 4.128346, CR= 0.009665.
The alternatives considered in the present case are arranged in a decreasing order according to their global weights and are shown in Table 8.
Table 8: Global weights for alternatives
It can be seen that the global weight of alternative 4 (A4) is the maximum. So, it can be said that this is the optimum condition to obtain a good corrosion resistant cladding using duplex stainless steel electrode maintaining good productivity, though it can be said that priority weights might vary according to the consideration of an individual. As a result, there might be a change in the selection of alternative as well from the selection of relative preferences made by a person to another. In the present case, a moderate heat input of 0.38 kJ/mm and corresponding weld voltage of 28V, weld current of 145A and weld speed of 516mm/min is evaluated to be the condition giving optimal corrosion resistance through cladding using duplex stainless steel electrode as well as good productivity.
5. Conclusion
Following conclusion may be drawn on the basis of the present experimental investigation:
At a moderate heat input of 0.38 kJ/mm corresponding to weld voltage of 28V, weld current of 145A and weld torch speed of 516mm/min, corrosion test shows occurrence of quite a less rate of corrosion. While carrying out the optimization work using the AHP also, the global weight of alternative 4 (A4) comes out to be the maximum in conformity with the experimental results. Therefore, this condition may be recommended to adopt for cladding low alloy steel components with duplex stainless steel electrodes using gas metal arc welding employing 100% CO2 gas shield maintaining productivity. At the same time, it can be stated that the AHP can easily be applied for solving multi-criteria decision making problems related to welding and weld cladding effectively.
REFERENCE
1. Manas Kumar Saha and Santanu Das, A Review on Different Cladding Techniques Employed to Resist Corrosion, Journal of the Association of Engineers, India, Vol. 86, No.1&2, pp-51-63, 2016.
2. M. K. Saha, S. Das, Gas Metal Arc Weld Cladding and its Anti-Corrosive Performance- A Brief Review, Athens Journal of Technology and Engineering, Vol. 5, No. 2, pp. 155-174, 2018.
3. N. Murugan, R.S. Parmar, Effect of MIG Process Parameters on the Geometry of the Bead in the Automatic Surfacing of Stainless Steel, Journal of Materials Processing Technology, Vol. 41, pp.381s-398s, 1994.
4. V.V. Murugan, V. Gunaraj, Effect of process parameters on Angular Distortion of Gas Metal Arc Weld Structural Steel Plates, Indian Welding Journal, Vol. 38, pp.165-171, 2005.
5. K. Sabiruddin, S. Das, A. Bhattacharya, Application of Analytical Hierarchy Process for Optimization of Process Parameters in GMAW, Indian Welding Journal, Vol. 42, No.1, pp.38-46, 2009.
6. T. Kannan, J. Yoganandh, Effect of Process Parameters on Clad Bead Geometry and its Shape Relationships of Stainless Steel Claddings Deposited by GMAW, International Journal of Advanced Manufacturing Technology, Vol. 47, pp.1083-1095, 2010.
7. V. Kumar, G. Singh, M.Z.K. Yusufzai, Effect of Process Parameters of Gas Metal Arc Welding on Dilution in Cladding of Stainless Steel on Mild Steel, MIT International Journal of Mechanical Engineering, Vol. 2, pp.127-131, 2012.
8. K. Sabiruddin, S. Bhattacharya, S. Das, Selection of Appropriate Process Parameters for Gas Metal Arc Welding of Medium Carbon Steel Specimens, International Journal of Analytical Hierarchy Process, Vol. 5, No.2, pp.252-267, 2013.
9. A.K. Verma, B.C. Biswas, P. Roy, S. De, S. Saren, S. Das, Exploring Quality of Austenitic Stainless Steel Clad Layer Obtained by Metal Active Gas Welding, Indian Science Cruiser, Vol. 27, No.4, pp.24-29, 2013.
10. B. Khara, N.D. Mandal, A. Sarkar, M. Sarkar, B. Chakrabarti, S. Das, Weld Cladding with Austenitic Stainless Steel for Imparting Corrosion Resistance, Indian Welding Journal, Vol. 49, No.1, pp.74-81, 2016.
11. A.K. Verma, B.C. Biswas, P. Roy, S. De, S. Saren, S. Das, An Investigation on the Anti-Corrosion Characteristics of Stainless Steel Cladding, Indian Welding Journal, Vol. 50, No.3, pp.52-63, 2017.
12. S. Bose, S. Das, Effect of heat input on corrosion resistance of 316 austenitic stainless steel cladding on low-carbon steel plate, Lecture Notes in Mechanical Engineering: Advances in Micro and Nano Manufacturing and Surface Engineering, Chapter 15, pp.163-176, 2022.
13. B. Chakraborty, H. Das, S. Das, T.K. Pal, Effect of Process Parameters on Clad Quality of Duplex Stainless Steel Using GMAW Process, Transactions of Indian Institute of Metals, Vol. 66, No.3, pp.221-230, 2013.
14. M.K. Saha, J. Mondal, A. Mondal, S. Das, Influence of Heat input on Corrosion Resistance of Duplex Stainless Steel Cladding Using Flux Cored Arc Welding on Low Alloy Steel Flats, Indian Welding Journal, Vol. 51, No. 3, pp.66-72, 2018.
15. M.K. Saha, A. Mondal, R. Hazra, S. Das, Anticorrosion performance of FCAW cladding with regard to the influence of heat input, Journal of Welding and Joining, Vol.36, No.5, pp.61-69, 2018.
16. M.K. Saha, A. Mondal, R. Hazra, S. Das, Influence of heat input on corrosion resistance of duplex stainless steel cladding on low alloy steel by FCAW, Advances in Micro and Nano Manufacturing and Surface Engineering in the Series: Lecture Notes on Multidisciplinary Industrial Engineering, Chapter 51, pp.571-581, 2019.
17. T.L. Saaty, Decision Making with the Analytic Hierarchy Process, International Journal of Services Sciences, Vol. 1, No. 1, pp. 83-98, 2008.
18. T.L. Saaty, A Scaling Method for Priorities in Hierarchical Structures, Journal Mathematical Psychology, Vol. 15, pp. 234-281, 1977.
19. L. G. Vergas, An Overview of the Analytical Hierarchy Process and Its Application, European Journal of Operations Research, Vol. 48, pp. 2-8, 1990.
20. C. Mondal, S. Bhattacharya, S. Das, Parametric optimization of spot welding of 17-4 PH stainless steels using the analytic hierarchy process, Indian Welding Journal, Vol.44, No.4, pp.69-78, 2011.
21. N. Biswas, S. Das, Selection of process parameters for welding P91 steel pipes using the analytic hierarchy process, Reason- A Technical Magazine, Vol.10, pp.7-12, 2011.
22. S. Das, The analytic hierarchy process based optimal parameter selection for cladding low grade steel with corrosion resistant stainless steel, Proceedings of the 1st International Conference on Emerging Trends in Computer Science and Information Technology (ETCSIT 15), Kalyani, West Bengal, India, January 05-07 2015, p.32, 2015
23. S. Bhattacharya, K. Sabiruddin, S. Das, Optimal selection of metal active gas welding parameters in joining high carbon steel: though the AHP, Indian Science Cruiser, Vol. 35, No.5, pp. 27-36, 2021.
24. A. Das, S. Das, Selection of Appropriate Welding Process for Joining Nodular Cast Iron through the AHP, Proceedings of the National Seminar on ‘Welding Science and Technology- Present Status & Future Direction’ (NSWEST 2021), Chennai, July 23-24 2021 pp.77-78, 2021.
25. T. Bera, S. Santra, S. Das, Performance Measure of Resistance Spot Welding of Similar and Dissimilar Triple Thin Sheets by Using AHP-ANN Hybrid Network, Vol. 36, No.2, pp.35-41, 2022.
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