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As the environmental concern is being raised over residues of lead, the trend of transferring from the conventional lead-based soldering to lead-free soldering is overwhelming. Lead-free solders require the peak temperature to be about 30 degrees Celsius higher than lead-based solders, which induce a narrower margin between the highest melting temperatures of lead-free solders and the heat-resistant temperatures of electronic components. As a result, the accuracy of temperature control of reflow systems needs to meet a higher standard to maintain the solder quality. Whereas, the conventional control process of the onboard temperature is open-loop, which cannot achieve the required accuracy. A closed-loop method by using an array of thermal image cameras for temperature monitoring is too expensive. In order to provide a low-cost and accurate temperature control solution for reflow systems, a cost-effective non-contact temperature approximation and control system is proposed in this article. The proposed temperature approximation is achieved based on a machine learning method with multiple-input single-output strategies to get a relationship between the temperatures near the PCBs and the onboard temperature. The proposed system controls the temperature in a real-time fuzzy logic algorithm to achieve a more accurate control result. The experiment results reveal the feasibility of the proposed temperature approximation and control system.

Low-Cost Non-Contact PCBs Temperature Monitoring and Control in a Hot Air Reflow Process Based on Multiple Thermocouples Data Fusion