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Study on intelligent control method of pharmaceutical production quality based on chromatographic fingerprint

Liyuan Zhang et al.

International Journal of Manufacturing Technology and Management2025https://doi.org/10.1504/ijmtm.2025.144115article
AJG 1
Weight
0.37

What the paper says

Aiming at the problems of low control accuracy and long control time in traditional intelligent control methods of drug production quality, an intelligent control method of drug production quality based on chromatographic fingerprint was proposed. Extract the chromatographic fingerprint of drug production quality, and use wavelet transform to de-noise the obtained fingerprint. According to the preprocessing results, use the real-time mean method to calculate the mean value of the real-time converted chromatographic fingerprint data. Through the tolerance zone of the fingerprint, convert the drug chromatographic fingerprint data. Based on the data conversion results, grade the drug production quality through fuzzy classification. The interval hesitation fuzzy control chart is constructed to carry out intelligent control of drug production quality. The experimental results show that the proposed method has higher precision and shorter control time for drug production quality intelligent control.

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https://doi.org/https://doi.org/10.1504/ijmtm.2025.144115

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@article{liyuan2025,
  title        = {{Study on intelligent control method of pharmaceutical production quality based on chromatographic fingerprint}},
  author       = {Liyuan Zhang et al.},
  journal      = {International Journal of Manufacturing Technology and Management},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1504/ijmtm.2025.144115},
}

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Study on intelligent control method of pharmaceutical production quality based on chromatographic fingerprint

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.