Reports Summarize Intelligent Systems Study Results from National Taipei University of Technology (Process optimization of SnCuNi soldering material using artificial parametric design)
By a News Reporter-Staff News Editor at Robotics & Machine Learning -- New research on Intelligent Systems is the subject of a report. According to news reporting originating from Taipei, Taiwan, by VerticalNews correspondents, research stated, "The European Union has implemented the directive restriction of hazardous substances (RoHS) prohibiting the uses of tin-lead solder. SAC305 (Sn96.5/Ag3.0/Cu0.5) has come into widespread use as a candidate soldering material in the electronics manufacturing industry."
Our news editors obtained a quote from the research from the National Taipei University of Technology, "Nevertheless, the price of silver has increased dramatically in recent years. This study evaluates the feasibility of replacing the commonly used SAC305 with low cost SnCuNi (Sn99.25/Cu0.7/Ni0.05/Ge; SCN) solder alloy in wave soldering for high layer count printed circuit board. However, the melting temperature of SCN alloy is 227, 10 higher than SAC305. The objective of this research is to investigate manufacturing issues and propose an optimal process. Process parameters such as soldering temperature and dwell time are determined to achieve the desired quality levels. Multiple quality characteristics, namely assembly yield and solder joint pull strength, are considered. Thus, this study compares two approaches, integration of principal component analysis/grey relational analysis and artificial neural networks (ANN) combined with genetic algorithms (GA), to resolve the problems of multiple quality characteristics. The results of verification test shows that samples prepared with the process scenario suggested by the ANN combined with GA are superior."
According to the news editors, the research concluded: "The process scenario with maximum desirability value is 268.64 soldering temperature and 7.42 s dwell time, indicating the recommended manufacturing process."
For more information on this research see: Process optimization of SnCuNi soldering material using artificial parametric design. Journal of Intelligent Manufacturing, 2014;25(4):813-823. Journal of Intelligent Manufacturing can be contacted at: Springer, Van Godewijckstraat 30, 3311 Gz Dordrecht, Netherlands. (Springer - www.springer.com; Journal of Intelligent Manufacturing - www.springerlink.com/content/0956-5515/)
The news editors report that additional information may be obtained by contacting C.Y. Huang, National Taipei University of Technology, Dept. of Ind Engn & Management, Taipei 10608, Taiwan.
Keywords for this news article include: Asia, Taipei, Taiwan, Intelligent Systems
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