A Flexible Data Evaluation System for Improving the Quality and Efficiency of Laboratory Analysis and Testing
In a chemical analysis laboratory, sample detection via most analytical devices obtains raw data and processes it to validate data reports, including raw data filtering, editing, effectiveness evaluation, error correction, etc. This process is usually carried out manually by analysts. When the sampl...
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Published in | Information (Basel) Vol. 13; no. 9; p. 424 |
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Language | English |
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01.09.2022
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Abstract | In a chemical analysis laboratory, sample detection via most analytical devices obtains raw data and processes it to validate data reports, including raw data filtering, editing, effectiveness evaluation, error correction, etc. This process is usually carried out manually by analysts. When the sample detection volume is large, the data processing involved becomes time-consuming and laborious, and manual errors may be introduced. In addition, analytical laboratories typically use a variety of analytical devices with different measurement principles, leading to the use of various heterogeneous control software systems from different vendors with different export data formats. Different formats introduce difficulties to laboratory automation. This paper proposes a modular data evaluation system that uses a global unified management and maintenance mode that can automatically filter data, evaluate quality, generate valid reports, and distribute reports. This modular software design concept allows the proposed system to be applied to different analytical devices; its integration into existing laboratory information management systems (LIMS) could maximise automation and improve the analysis and testing quality and efficiency in a chemical analysis laboratory, while meeting the analysis and testing requirements. |
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AbstractList | In a chemical analysis laboratory, sample detection via most analytical devices obtains raw data and processes it to validate data reports, including raw data filtering, editing, effectiveness evaluation, error correction, etc. This process is usually carried out manually by analysts. When the sample detection volume is large, the data processing involved becomes time-consuming and laborious, and manual errors may be introduced. In addition, analytical laboratories typically use a variety of analytical devices with different measurement principles, leading to the use of various heterogeneous control software systems from different vendors with different export data formats. Different formats introduce difficulties to laboratory automation. This paper proposes a modular data evaluation system that uses a global unified management and maintenance mode that can automatically filter data, evaluate quality, generate valid reports, and distribute reports. This modular software design concept allows the proposed system to be applied to different analytical devices; its integration into existing laboratory information management systems (LIMS) could maximise automation and improve the analysis and testing quality and efficiency in a chemical analysis laboratory, while meeting the analysis and testing requirements. |
Author | Tang, Haoye Hu, Wenyou Gong, Hua Tu, Yonghui |
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Cites_doi | 10.1016/j.copbio.2017.02.011 10.1016/j.chroma.2007.10.086 10.1109/I2MTC.2015.7151518 10.1016/j.copbio.2019.07.002 10.1002/pmic.200900420 10.3390/su12218769 10.1002/mas.21414 10.3390/info13020085 10.1039/c2ay25083g 10.1007/978-3-319-23144-0_16 10.1016/j.drudis.2010.07.007 10.1016/S0003-2670(01)84177-5 10.1016/j.biotechadv.2020.107637 10.6023/A20070306 10.2174/157016412800786248 10.1109/CAC48633.2019.8996837 10.1109/MCSE.2012.34 |
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SubjectTerms | Analytical chemistry Artificial intelligence Automation Chemical analysis Chemical research Customers data formats Data processing Efficiency Electronic devices Error correction evaluate quality Evaluation heterogeneous system Laboratories Laboratory information management systems Mathematical analysis Modular design Modular systems Quality control raw data sample detection Software Soil sciences |
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