Open Access
Subscription Access
Open Access
Subscription Access
Performance Measure of Resistance Spot Welding of Similar and Dissimilar Triple Thin Sheets by using AHP-ANN Hybrid Network
Subscribe/Renew Journal
The analytical hierarchy process or AHP is a useful decision-making tool, and it is applied in this work in resistance spot welding where two different types of triple thin sheets consisting of aluminium, galvanized iron and stainless steel are joined. Combining both the AHP and ANN, a hybrid network is developed to eliminate the complexity of the experimental results to predict. The AHP-ANN hybrid network successfully predicted output parameters with less error. Correlation coefficient has been more than 0.98 and the applicability of this method..
Keywords
ANN, AHP, Resistance Spot Welding, Welding, Dissimilar Welding, Hybrid Network
User
Subscription
Login to verify subscription
Font Size
Information
- T L Saaty, A Scaling Method for Priorities in Hierarchical Structures, Journal of Mathematical Psychology, Vol. 15, No.3, page. 234-281, 1977.
- A U Khan, and Y Ali, Analytical Hierarchy Process (AHP) and Analytic Network Process Methods and Their Applications: A Twenty Year Review from 2000–2019, International Journal of the Analytic Hierarchy Process, Vol 12, No 3, 2020.
- I Daniyan, K Mpofu and B Ramatsetse, The use of Analytical Hierarchy Process (AHP) decision model for materials and assembly method selection during railcar development, Cogent Engineering, Vol 7, No 1, 2020.
- O I Abiodun, M U Kiru, A Jantan, A E Omolara, K V Dada, A M Umar, O U Linus, H Arshad, A A Kazaure and U Gana, Comprehensive Review of Artificial Neural Network Applications to Pattern Recognition, IEEE Access, Vol 7, page. 158820– 158846, 2019.
- O I Abiodun, A Jantan, A E Omolara, K V Dada, N A Mohamed and H, Arshad, State-of-the-art in artificial neural network applications: A survey, Heliyon, Vol 4, No 11, e00938, 2018.
- N Akkaş, E İLhan, F Varol and S Aslanlar, Welding Time Effect on Mechanical Properties in Resistance Spot Welding of S235JR(Cu) Steel Sheets Used in Railway Vehicles, Acta Physica Polonica A, Vol 129, No 4, page. 541–543, 2016.
- W Li, S Cheng, S J Hu and J Shriver, Statistical Investigation on Resistance Spot Welding Quality Using a Two-State, Sliding-Level Experiment, Journal of Manufacturing Science and Engineering, Vol 123, No 3, page. 513–520, 2000.
- A S Baskoro, A Edyanto, M A Amat and H Muzaki, Study on Nugget Growth in Resistance Spot Welding of Thin Aluminum A1100 Using Welding Simulation, Materials Science Forum, Vol 929, page. 191–199, 2018.
- M Alenius, P Pohjanne, M Somervuori, and H Hanninen, Exploring the mechanical properties of spot welded dissimilar joints for stainless and galvanized steels, Welding Journal, Vol 85, No12, page. 305-s-313-s, 2006.
- H Oikawa, G Murayama, T Sakiyama, Y Takahashi and T Ishikawa, Resistance Spot Weldability of High Strength Steel(HSS) sheets for Automobiles, Nippon Steel Technical Report No 95, page. 39-45, 2007.
- V Ravisankar, V Balasubramanian and C Muralidharan, Selection of welding process to fabricate butt joints of high strength aluminium alloys using analytic hierarchic process, Materials and Design, Vol 27, No 5, page. 373–380, 2006.
- K Sabiruddin, S Das and A Bhattacharya, Application of the analytic hierarchic process for optimization of process parameters in GMAW, Indian Welding Journal, Vol 42, No 1, 38-46, 2009.
- X Lai, C Ji, X Luo &, L Deng, Application of AHP method of orthogonal trial to selection of parameters in resistance spot welding, Electric Welding Machine, Vol 49, page. 7-8, 2009.
- X Liuand SL Gong, Evaluation on the effect of weld shape on fatigue performance by analytic hierarchy process, Advanced Materials Research, Vols 146-147, page. 1839-1842, 2011.
- J Shah, G Patel, J Makwana, Optimization and Prediction of MIG Welding Process Parameters Using ANN, International Journal of Engineering Development and Research, Vol 5, No 2, page. 1487-1491, 2017.
- P Sreeraj, T Kannan, S Maji, Simulation and Parameter Optimization of GMAW Process Using Neural Networks and Particle Swarm Optimization Algorithm, International Journal of Mechanical Engineering and Robotic Research, Vol 2, No 1, page. 131-146, 2013.
- J Lee, K Um, A comparison in a back-bead prediction of gas metal arc welding using multiple regression analysis and artificial neural network, Journal of Optics and Lasers in Engineering, Vol 34, page. 149-158, 2000.
- H Ates, Prediction of gas metal arc welding parameters based on artificial neural networks, Materials and Design, Vol 28, page. 2015-2023, 2007.
- T Bera, S Das, Application of Artificial Neural Networks in Predicting Output Parameters of Gas Metal Arc Welding of Dissimilar Steels, Indian Science Cruiser, Vol 35, No 3, page. 26-30, 2021.
- DSNagesh, GL Datta, Modeling of fillet welded joint of GMAW process: integrated approach using DOE,
- ANN and GA, International Journal on Interactive Design Manufacturing, Vol 2, page. 127-136, 2008.
- BN Sreeharan, T Kannan, P Aravind, Process Optimization of GMAW Over AA6351 Aluminium Alloy Using ANN, Vol 8, No 9, page. 208-218, 2017.
- T Bera, S Das, Estimation of Geometry and Properties of Weld Bead Using Artificial Neural Networks, Reason- A Technical Journal, Vol 20, page. 46-56, 2021.
Abstract Views: 267
PDF Views: 0