Intelligent Service Assistant Inference Engine for IVD Troubleshooting
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Solution Overview
Problem
Conventional methods for troubleshooting in vitro diagnostic instruments are complex, time-consuming, and inefficient, relying heavily on operator knowledge and manual searches for error codes or expert assistance.
Innovation Solution
An intelligent service assistant (ISA) inference engine dynamically identifies issues and solution strategies using an expert system approach, with a rules engine that encodes customer service knowledge and provides automated reasoning to determine the best corrective actions across a fleet of instruments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If conventional troubleshooting methods are used (manual error code lookup, operator knowledge, telephone support), then operator flexibility and adaptability are maintained, but troubleshooting time and complexity increase significantly
Solution Approach 1:
The IVD instrument performs self-diagnosis by automatically detecting errors and generating error codes, eliminating the need for operators to manually identify problems. The system serves itself by monitoring its own operational parameters and triggering appropriate error conditions.
Solution Approach 2:
The processor acts as an intermediary between the instrument's operational components and the operator. It translates complex instrument states into simplified error codes and communicates solution information to the operator, reducing the cognitive burden on the operator.
2Productivity
If conventional troubleshooting methods are used, then operator knowledge and experience are utilized, but operator workflow and efficiency are reduced
Solution Approach 1:
The system prepares troubleshooting information in advance by pre-programming solution protocols associated with each error code. When an error occurs, the corresponding solution is immediately retrieved and presented to the operator, eliminating the need for real-time problem-solving and manual information search.
Solution Approach 2:
The patent replaces the mechanical/cognitive process of operator problem-solving with an automated information retrieval system. The processor automatically matches error codes with pre-stored solution information, substituting operator mental effort with computational processing.
3Loss of time
If automated reasoning systems are implemented, then troubleshooting time is reduced, but system complexity increases
Solution Approach 1:
The troubleshooting system is segmented into distinct modular components: error detection modules that monitor specific instrument parameters, a error code generation module, a solution database with pre-programmed protocols, and an information delivery module. Each segment handles a specific aspect of troubleshooting, making the overall system manageable despite its automation capabilities.
Data Source
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AI summary
A method of providing dynamic analysis for troubleshooting in vitro diagnostics instrument issues includes receiving, at a second computing device in communication with a plurality of instruments, identification of an issue associated with a portion of an instrument of the plurality of instruments, the identification received from a first computing device in communication with the instrument. A central computing device accesses data from one or more databases and determines an ordering of one or more corrective actions for resolving the issue by applying the data to a probabilistic model based on at least one of: patterns from the plurality of instruments; and operator input. The central computing device provides the one or more corrective actions in the determined order to the first computing device to be displayed via a user interface at the instrument.