Endoscope Sensor Data Capture for Abnormality Reproduction
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Solution Overview
Problem
Existing endoscope systems face challenges in efficiently reproducing abnormalities for timely and effective repairs, as existing methods rely on insufficient operational data, leading to time-consuming and inefficient maintenance processes.
Innovation Solution
An endoscope system equipped with sensors that detect and store operational and sensor data, allowing for efficient abnormality reproduction and prediction, including an internal memory to store information and a processor to manage and transmit this data to a server for centralized management and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If only operating status and error number are transmitted to server, then data transmission is simple, but abnormality cannot be reproduced and repair efficiency is low
Solution Approach 1:
The system performs preliminary action by storing sensor information from a predetermined period before abnormality detection in internal memory. This prepares comprehensive data in advance, enabling efficient abnormality reproduction and repair when the abnormality actually occurs, thus improving repair efficiency while maintaining information completeness.
2Ease of repair
If comprehensive sensor information is stored in internal memory, then abnormality can be reproduced efficiently, but device complexity increases
Solution Approach 1:
The system extracts only the necessary sensor information related to abnormality occurrence and stores it in internal memory, separating this critical data from other operational data. This selective extraction enables efficient abnormality reproduction while avoiding the complexity of storing and managing all possible sensor data comprehensively.
Solution Approach 2:
The internal memory acts as an intermediary between the sensors and the server, storing preprocessed sensor information locally. This intermediary function enables efficient abnormality reproduction by providing ready-access data without requiring complex real-time data collection and transmission infrastructure.
3Productivity
If maintenance is performed periodically, then maintenance schedule is simple, but maintenance timing may be inappropriate and resources are wasted
Solution Approach 1:
The system implements feedback by transmitting sensor information and operating information to the server, which analyzes this data to determine appropriate maintenance timing. This feedback loop enables maintenance to be performed based on actual device condition rather than fixed schedules, improving maintenance efficiency while optimizing timing to avoid resource waste.
Data Source
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AI summary
Provided are an endoscope system (10, 100, 200, 300, 400) and a method of operating an endoscope system (10, 100, 200, 300, 400) capable of efficiently performing a repair. An endoscope system (10, 100, 200, 300, 400) includes an endoscope 12 and a processor device 20. The processor device 20 functions as an abnormality detection unit 76, an abnormality information generation unit 80, and an abnormality information management unit 82. The abnormality detection unit detects an abnormality of the endoscope 12 by using information detected by an image sensor 60 of the endoscope 12. The abnormality information generation unit 80 generates abnormality information including sensor information detected by the image sensor 60 at a time of abnormality detection and in a predetermined period before and after the abnormality detection and operating information of the endoscope 12. The abnormality information management unit 82 stores the abnormality information in a memory 70.