Investigating the effect of tensile shear strength of resistance spot welding using a neuro fuzzy control system
International Journal on Interactive Design and Manufacturing, ISSN: 1955-2505
2024
- 3Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
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Article Description
Resistance spot welding (RSW) stands out as a widely adopted method, especially in the automotive sector, for joining thin sheets of various materials. This study focuses on optimizing RSW strength by controlling both dynamic and static parameters in which fuzzy logic-based model can forecast the RSW reaction to the tensile shear strength, and nugget size. The process factors for the RSW process include welding current, electrode force, steel thickness, welding time, and tensile shear strength. A fuzzy logic model that forecasts the impact of the input factors on the replies was built using the experimental data. As a result, the proposed model is significantly reducing the energy consumption to 5253.8 J, marking a substantial improvement over the reference study’s energy expenditure of 26,000 J and the tensile strength of the weld to 594 N, surpassing the reference study’s result 350 N.
Bibliographic Details
Springer Science and Business Media LLC
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