Evaluation of Soldering Skill Using Fuzzy Inference

This study addresses the challenge of manual soldering skill evaluation and transfer in the context of small and medium-sized enterprises where automation is less prevalent. Recognizing the limitations of current single-factor evaluation models, which primarily consider the soldering iron holding method, this research aims to develop a multifactor evaluation model incorporating additional aspects of the soldering process. The proposed model includes the general theory of time spent in soldering, focusing on the heating time of the base metal and the solder melting time as key factors. By integrating these statistical characteristics into a fuzzy inference model, alongside the traditional factor of soldering iron handling, a more comprehensive evaluation approach is achieved. This multifaceted model allows for a nuanced assessment of soldering skills and proposes improvement methods. Future work will involve verifying the model's accuracy with larger data sets and developing a system to facilitate skill evaluation and knowledge transfer, addressing the industry's labor shortage and the decline in skilled workers.