Zhilian Xintong Technology Granted Patent for "Production Process Traceability Method Based on Blockchain in the Field of Intelligent Manufacturing"

Zhilian Xintong Technology Granted Patent for "Production Process Traceability Method Based on Blockchain in the Field of Intelligent Manufacturing"On August 7, 2024, Financial learned from Tianyancha intellectual property information that Zhilian Xintong Technology Co., Ltd

Zhilian Xintong Technology Granted Patent for "Production Process Traceability Method Based on Blockchain in the Field of Intelligent Manufacturing"

On August 7, 2024, Financial learned from Tianyancha intellectual property information that Zhilian Xintong Technology Co., Ltd. was granted a patent titled "A Production Process Traceability Method Based on Blockchain in the Field of Intelligent Manufacturing", with authorization announcement number CN118195641B, and application date in May 2024.

This patent aims to address the monitoring data quality issues in the production process traceability in the field of intelligent manufacturing, thereby improving the accuracy of traceability. Its core technology is to employ a blockchain-based traceability method, analyzing the monitoring data from multiple dimensions, ultimately determining the optimal smoothing level for each independent component, obtaining a processed high-quality monitoring data sequence, and realizing efficient and accurate production traceability.

The patent abstract describes the specific steps of this method in detail:

1. Obtain each independent component of the monitoring data sequence to be processed: This step first identifies the independent components in the monitoring data sequence, such as monitoring data from different production stages.

2. Process each independent component with different smoothing levels: Different smoothing methods are applied to each independent component to obtain smoothed results with varying levels of smoothness.

3. Evaluate the rationality of different smoothing levels: The results under different smoothing levels are evaluated, analyzing their rationality to determine the optimal smoothing level.

4. Judge the degree of non-abnormality of each data point: By analyzing the degree of non-abnormality of each data point under different smoothing levels, further accurate data is filtered out.

5. Compare the distribution differences between independent components under different smoothing levels and the corresponding original data: By comparing the distribution differences between independent components under different smoothing levels and the corresponding original data, the optimal smoothing level for each independent component is finally determined.

6. Obtain the processed monitoring data sequence: Based on the above steps, the optimal smoothing level for each independent component is determined, and the processed monitoring data sequence is obtained.

This patent effectively improves the quality of monitoring data by analyzing and optimizing monitoring data from multiple dimensions, thereby enhancing the accuracy of production traceability. This blockchain-based production process traceability method in the field of intelligent manufacturing can not only provide enterprises with more reliable production data but also provide effective assurance for product quality control and safety traceability, helping enterprises achieve digital transformation and intelligent upgrade.

Zhilian Xintong Technology Co., Ltd. has always been committed to promoting technological innovation in the field of intelligent manufacturing. The granting of this patent marks a new breakthrough in its production process traceability technology, and it is expected to provide enterprises with more advanced and comprehensive intelligent manufacturing solutions in the future. At the same time, this patent also provides new technical support for promoting the digital transformation and high-quality development of the intelligent manufacturing industry, further enhancing the overall competitiveness of China's intelligent manufacturing industry.