HANGZHOU, China

Xuxia Zhang

USPTO Granted Patents = 1 

Average Co-Inventor Count = 7.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):

Title: Innovations by Xuxia Zhang in Aluminum Alloy Casting

Introduction

Xuxia Zhang is a notable inventor based in Hangzhou, China. He has made significant contributions to the field of aluminum alloy casting through his innovative approaches and methodologies. His work focuses on enhancing production quality and efficiency in manufacturing processes.

Latest Patents

Xuxia Zhang holds a patent for a data mining-based method for real-time production quality prediction of aluminum alloy casting. This patent includes several key components: first, it involves installing sensors on a casting mold based on mold flow analysis results. These sensors consist of at least one temperature sensor, one pressure sensor, one contact sensor, and a multi-functional gas sensor. During the casting production process, the system collects real-time data on temperatures, pressures, and contact times of the aluminum liquid at various locations within the casting mold. Additionally, it monitors the pressure, composition, humidity, and temperature of gas in the mold cavity. This data is then used to construct an aluminum alloy casting process parameter set, which is input into a production quality prediction model. This model assesses whether the production quality meets the required standards by analyzing the relationship between historical casting process parameters and casting quality data.

Career Highlights

Xuxia Zhang is affiliated with Hangzhou City University, where he contributes to research and development in the field of materials science and engineering. His work has garnered attention for its practical applications in improving manufacturing processes.

Collaborations

Xuxia Zhang collaborates with colleagues such as Weipeng Liu and Tao Peng, who share his commitment to advancing technology in aluminum alloy casting.

Conclusion

Xuxia Zhang's innovative methods in aluminum alloy casting demonstrate the potential for data-driven approaches to enhance production quality. His contributions are paving the way for advancements in manufacturing technologies.

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