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 inInformation (Basel) Vol. 13; no. 9; p. 424
Main Authors Tu, Yonghui, Tang, Haoye, Gong, Hua, Hu, Wenyou
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 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.
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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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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