Laboratory Instrument Log Data Anomaly Detection
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Solution Overview
Problem
The reliability of results from analyzing biological samples in automated laboratory systems is compromised due to errors in laboratory instruments, which are difficult to detect post-analysis due to the complexity and number of instruments.
Innovation Solution
A computer-implemented method that involves obtaining log data from laboratory instruments, constructing log data items by selecting relevant field-data from log file entries, and using this data to assess for anomalies in the instruments, thereby improving data correlation and anomaly detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated laboratory systems process a huge number of samples through multiple complex instruments, then productivity increases, but the difficulty of detecting and measuring errors in instruments worsens
Solution Approach 1:
The system performs preliminary actions by continuously collecting log data from instruments during sample processing and pre-processing this data into structured formats with relevant fields extracted. This preliminary data preparation enables subsequent anomaly detection without interrupting the high-volume sample processing workflow, thus maintaining productivity while enabling error detection capability.
Solution Approach 2:
The patent introduces an intermediary data processing layer that sits between the complex laboratory instruments and the anomaly detection system. This intermediary extracts and structures relevant log data into standardized formats with selected fields, making the data suitable for analysis without requiring direct access to or understanding of the complex instrument internals, thus facilitating error detection while preserving system independence.
2Reliability
If log data from laboratory instruments is processed to detect anomalies, then reliability of results improves, but the complexity of data processing increases
Solution Approach 1:
The system applies the extraction principle by selectively taking out only the relevant fields from comprehensive log data generated by laboratory instruments. Instead of processing entire log files containing all possible information, the system extracts and processes only specific fields that are indicative of anomalies, thus improving reliability while reducing processing complexity by filtering out irrelevant data.
Solution Approach 2:
The patent segments the complex log data into structured formats with distinct fields, each representing specific aspects of instrument operation. This segmentation organizes the data into manageable units that can be processed independently, reducing overall processing complexity while maintaining comprehensive monitoring capability for reliability assurance.
3Measurement precision
If comprehensive log data is collected from all instruments, then anomaly detection accuracy improves, but the loss of time for data processing increases
Solution Approach 1:
The system extracts only the essential fields from comprehensive log data that are most indicative of anomalies. By taking out and processing only these critical fields rather than analyzing entire log files, the system maintains high anomaly detection accuracy while significantly reducing the time required for data processing.
Solution Approach 2:
The patent applies partial action by processing a subset of the most relevant log data fields rather than performing exhaustive analysis of all available data. This partial processing approach achieves sufficient anomaly detection accuracy for practical purposes while avoiding the excessive time consumption that would result from complete data analysis.
Data Source
AI summary
An aspect of the present invention relates to a computer-implemented method comprising the steps of: obtaining, from or by a first computing device, log data, the log data comprising a first plurality of log data items; and obtaining anomaly data, the anomaly data comprising information indicative of the presence of an anomaly in a laboratory instrument, wherein the first computing device is configured to access a log file of the laboratory instrument, the log file comprising a first plurality of log file entries, each log file entry of the first plurality of log file entries comprising a plurality of fields, and to construct the log data, by, for each log data item of the first plurality of log data items: selecting first field-data of a first field of a respective log file entry, the first field of the respective log file entry specifying a respective event which has occurred in the laboratory instrument; selecting second field-data of a second field of the respective log file entry, the second field of the respective log file entry further describing the respective event occurred in the laboratory instrument, wherein the selecting of the respective second field is based on the first field-data of the respective first field of the respective log file entry; and constructing said each log data item by using the first field-data of the first field of the respective log file entry and the second field-data of the second field of the respective log file entry. Additional aspects of the present invention relate to further computer-implemented methods, a data processing system, a laboratory instrument, an automated laboratory system, a computer program product, and a computer-readable medium.