IVD Instrument Condition Monitoring for Predictive Maintenance

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Solution Overview

Problem

In vitro diagnostic instruments often experience failures that are diagnosed only after they occur, leading to excessive repair downtime and labor costs due to reactionary maintenance approaches.

Innovation Solution

A method and apparatus that monitor condition-based maintenance parameters to predict impending failures, using sensors and a failure prediction engine to compare measured parameters against a pattern library, allowing for proactive maintenance and scheduling of repairs.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If reactionary maintenance is used (diagnosing failures after they occur), then the instrument can operate without monitoring systems, but repair downtime and labor costs increase

Engineering Contradiction:
Improveinstrument availabilityVSAvoidrepair downtime
Core Design Contradiction:
ReliabilityVSLoss of time

Solution Approach 1:

The patent applies preliminary action by monitoring condition-based maintenance parameters continuously to detect early signs of component deterioration before actual failure occurs. The system performs maintenance actions in advance based on predicted failure timelines, allowing scheduling of repairs during convenient times rather than reacting to unexpected failures, thus reducing repair downtime and improving instrument availability

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The patent implements feedback by continuously monitoring condition-based parameters (vibration, temperature, pressure, flow, electrical signals) and comparing them against baseline values and failure patterns. This feedback loop enables the system to detect deviations indicating component deterioration, predict impending failures, and trigger maintenance actions before complete failure occurs, thereby reducing unplanned downtime

Inventive Principle:
Principle #23Feedback

2Measurement precision

If comprehensive monitoring of condition-based parameters is implemented, then failure prediction accuracy improves, but device complexity increases

Engineering Contradiction:
Improvefailure prediction accuracyVSAvoidmonitoring system complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The patent applies segmentation by dividing the monitoring system into modular components: multiple sensors monitoring different condition-based parameters (vibration, temperature, pressure, flow, electrical signals), a microprocessor-based control unit, and a database system. Each sensor monitors specific parameters independently, and the control unit processes data from individual components separately, making the complex monitoring system manageable and scalable while maintaining high prediction accuracy

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent implements universality by designing a multi-functional monitoring system where a single control unit processes data from multiple sensor types (vibration, temperature, pressure, flow, electrical). The system can monitor various instrument components (pumps, motors, valves, heaters) using the same control architecture and analysis methods, reducing overall system complexity despite comprehensive monitoring capabilities

Inventive Principle:
Principle #6Universality (Multi-functionality)

Data Source

PatentEP3488307B1Methods for predicting and preventing failure of in vitro diagnostic instruments
Publication Date: 2021.10.06 SIEMENS HEALTHCARE DIAGNOSTICS INC
  • EP3488307B1 patent drawingFigure 1
  • EP3488307B1 patent drawingFigure 2
  • EP3488307B1 patent drawingFigure 3

AI summary

Methods of predicting failures of in vitro diagnostic instruments. The methods include monitoring with one or more monitoring devices associated with one or more components of the in vitro diagnostic instrument, one or more condition-based maintenance (CBM) parameters of the in vitro diagnostic instrument, providing the one or more condition-based maintenance parameters to a local database, transmitting condition-based maintenance data to a remote service location, storing the condition-based maintenance data at the remote service location, analyzing the condition-based maintenance data according to a failure prediction engine including failure prediction criteria, and performing an action based on predefined deviation from the failure prediction criteria. Apparatus configured to carry out the methods are provided, as are other aspects.