Technical Library | 2016-08-02 06:12:05.0
The audio device industry is set to grow in parallel with the technology triggering across the globe. Also the entertainment and hospitality industry has created an increased demand of audio devices at large. With the enhancement coming up in consumer applications every other day, the recent trend of implementing wireless technology in audio devices has captivated the attention in the market with its growing popularities all over the electronics industry. The recent audio discoveries have marked cosmic developments in the new product launch, business partnership and acquisition globally. With this, the audio device makers are now in race to present a multi featured compact device with giving an appealing dimension experience to the end users in order to survive in the electronic market.
Technical Library | 2009-04-30 19:12:05.0
A brand is the most important strategic asset your business will ever possess. Yet ask even the most experienced marketer and they will struggle to communicate the concept in a single sentence. Furthermore, if you were to approach the majority of today's business-to-business organisations, they would probably tell you that branding finds little application in a market allegedly filled with dispassionate decision makers. However, an increasingly competitive market landscape is eroding this reality - if, indeed, it ever existed. B2B marketing must follow the example of its consumer-focused counterpart and embrace the notion that a strong brand has the power to differentiate, build and protect those it represents in the face of incessant commoditization.
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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