Glass-box modeling for quality assessment of resistance spot welding joints in industrial applications

Autor: José Ignacio Santos, Óscar Martín, Virginia Ahedo, Pilar de Tiedra, José Manuel Galán
Rok vydání: 2022
Předmět:
Zdroj: The International Journal of Advanced Manufacturing Technology. 123:4077-4092
ISSN: 1433-3015
0268-3768
DOI: 10.1007/s00170-022-10444-4
Popis: Resistance spot welding (RSW) is one of the most relevant industrial processes in diferent sectors. Key issues in RSW are process control and ex-ante and ex-post evaluation of the quality level of RSW joints. Multiple-input–single-output methods are commonly used to create predictive models of the process from the welding parameters. However, until now, the choice of a particular model has typically involved a tradeof between accuracy and interpretability. In this work, such dichotomy is overcome by using the explainable boosting machine algorithm, which obtains accuracy levels in both classifcation and prediction of the welded joint tensile shear load bearing capacity statistically as good or even better than the best algorithms in the literature, while maintaining high levels of interpretability. These characteristics allow (i) a simple diagnosis of the overall behavior of the process, and, for each individual prediction, (ii) the attribution to each of the control variables—and/ or to their potential interactions—of the result obtained. These distinctive characteristics have important implications for the optimization and control of welding processes, establishing the explainable boosting machine as one of the reference algorithms for their modeling.
Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. The authors acknowledge fnancial support from the Spanish Ministry of Science, Innovation and Universities (Excellence Network RED2018‐102518‐T), the Spanish State Research Agency (PID2020-118906 GB-I00/AEI/https://doi.org/10. 13039/501100011033), and the Fundación Bancaria Caixa D. Estalvis I Pensions de Barcelona, La Caixa (2020/00062/001). In addition, we acknowledge support from the Santander Supercomputación group (University of Cantabria) that provided access to the Altamira Supercomputer—located at the Institute of Physics of Cantabria (IFCACSIC) and member of the Spanish Supercomputing Network—to perform the diferent simulations/analyses.
Databáze: OpenAIRE
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