Using Artificial Neural Networks to Build a Quality Control System of SMT Stencil Printing Process
碩士 === 國立成功大學 === 製造工程研究所碩博士班 === 90 === Surface Mount Technology (SMT) assembly is the placement and attachment of electronic components to the surface of a printed circuit board, and it has become the key technology to transform manufacturing in the electronics industry to continuously respond to...
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| Format: | Others |
| Language: | zh-TW |
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2002
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| Online Access: | http://ndltd.ncl.edu.tw/handle/nq7ac8 |
| Summary: | 碩士 === 國立成功大學 === 製造工程研究所碩博士班 === 90 === Surface Mount Technology (SMT) assembly is the placement and attachment of electronic components to the surface of a printed circuit board, and it has become the key technology to transform manufacturing in the electronics industry to continuously respond to the needs of the global market. The relationship between the input/output variables in SMT acts nonlinearly and severely. The stencil printing is one of the most critical stages and accounts for 52~71% of overall soldering defects.
This research will help in understanding the solder paste stencil printing process and identifying the critical variables that influence the volume of deposited solder paste. Through design of experiment and neural networks, a quality control system of stencil printing is established that helps engineers in troubleshooting the malfunctioned process and to improve solderability.
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