Carla Ferreira Andrade Cunha
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Jefferson de Oliveira Gomes
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Hugo Marcelo Bezerra de Carvalho
Abstract
Actions aiming to reduce energy consumption directly contribute to the reduction of manufacturing costs and carbon footprint while supporting manufacturing processes’ productivity. Resistance spot welding is relevant in the automotive sector. Due to its operational characteristics, this process has high energy consumption. Despite this fact, few studies have found to guide solutions for its reduction. In this sense, this study proposes a method to improve the resistance spot welding process’s energy performance without compromising its quality. This study applies statistical analysis (ANOVA) to support predictive models that characterize energy and quality performance. The statistical analyses confirmed and quantified the influence of the control factors in energy and quality performance indicators. The predictive models made it possible to anticipate energy consumption and quality behaviour from adjustments in the welding line process parameters studied in this paper. To fit the best compromise between energy consumption and quality, energy labels to classify the process’s energy performance were proposed. The best compromise solution for the studied process parameter ranges in this work was: \({C}_{wel}\): 8 kA, \({T}_{wel}\): 8 cycles and \({F}_{ele}\): 343 kgf. This parameter combination results in a consumption of approximately 2 Wh per spot weld. Approximately 33% less than the average estimated consumption per spot weld in the automotive industry.