Technical Library | 2023-09-18 03:37:30.0
Revolutionize your PCB stenciling process with our cutting-edge SMT fully automatic stencil printer. Achieve unparalleled precision and efficiency. Explore our advanced stencil printing solutions today!
Technical Library | 2021-06-28 20:50:35.0
The automatic stencil wiper –first line of defense 2 • The Printing process and why we need to focus on the wiping function • Frequency of wiping • Wiping options • Wiper profiles • Event driven wiping • Advanced options • Materials – Paper • Materials – Solvent • Preventive maintenance • Random stuff
Technical Library | 2021-11-10 19:59:15.0
The automatic stencil wiper - first line of defense * The Printing process and why we need to focus on the wiping function * Frequency of wiping * Wiping options * Wiper profiles • Event driven wiping * Advanced options * Materials – Paper * Materials – Solvent * Preventive maintenance * Random stuff
Technical Library | 2023-09-18 03:40:02.0
Our SMT intelligent solder paste supply system is the perfect solution for businesses that need to improve the accuracy and consistency of their SMT paste printing. Our system uses the latest technology to automatically dispense the correct amount of solder paste to each stencil opening, ensuring that your SMT assemblies are consistently high-quality.
Technical Library | 2023-06-12 18:33:29.0
This paper presents a real-time predictive approach to improve solder paste stencil printing cycle decision making process in surface mount assembly lines. Stencil cleaning is a critical process that influences the quality and efficiency of printing circuit board. Stencil cleaning operation depends on various process variables, such as printing speed, printing pressure, and aperture shape. The objective of this research is to help efficiently decide stencil printing cleaning cycle by applying data-driven predictive methods. To predict the printed circuit board quality level, a recurrent neural network (RNN) is applied to obtain the printing performance for the different cleaning aging. In the prediction model, not only the previous printing performance statuses are included, but also the printing settings are used to enhance the RNN learning. The model is tested using data collected from an actual solder paste stencil printing line. Based on the predicted printing performance level, the model can help automatically identify the possible cleaning cycle in practice. The results indicate that the proposed model architecture can predictively provide accurate solder paste printing process information to decision makers and increase the quality of the stencil printing process.
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