Elevator Predictive Maintenance via Real-Time Current Analysis
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Solution Overview
Problem
Conventional elevator maintenance methods fail to predictively maintain elevator operation units effectively, leading to safety accidents and inefficient operation due to infrequent inspections and lack of consideration for floor-specific operation frequencies and passenger loads, resulting in unreasonable electricity rate settlements.
Innovation Solution
A method for predictive maintenance and high efficiency operation through elevator analysis, which collects and analyzes operation information in real-time, sets threshold levels based on normal and pre-failure data, and controls door-closing times based on digitized floor-specific operation frequencies and passenger data to detect abnormal symptoms and optimize elevator operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If regular inspection with equal or less than 2 years interval is performed, then safety accidents can be prevented to some extent, but predictive maintenance of operation unit failure cannot be effectively achieved
Solution Approach 1:
The system performs preliminary actions by collecting operation information (current values) during normal operation phases and storing them as baseline data before failures occur. Threshold levels are established in advance based on this normal operation data, enabling the system to predict failures before they happen by comparing real-time measurements against these pre-established thresholds.
Solution Approach 2:
The system implements continuous feedback by monitoring operation unit current values in real-time during elevator operation. The detected current values are continuously compared against stored threshold levels, and when abnormalities are detected, the system provides feedback signals to alert operators and initiate maintenance actions, creating a closed-loop monitoring system that improves reliability beyond periodic inspections.
2Ease of operation
If manual operation without automated control is used, then operation flexibility is maintained, but floor-specific operation frequency and passenger load optimization cannot be achieved
Solution Approach 1:
The system enables self-service operation by automatically analyzing operation information to extract floor-specific operation frequencies, time zones, and passenger load patterns without requiring manual intervention. The control unit autonomously determines optimal door-closing times based on extracted operation patterns, allowing the elevator system to optimize its own operation efficiency while maintaining ease of use through automated decision-making.
Solution Approach 2:
The system dynamically changes operational parameters such as door-closing time based on extracted operation information. By analyzing floor-specific operation frequencies and passenger loads, the control unit adjusts door-closing times to match actual usage patterns, optimizing elevator efficiency and energy consumption without requiring manual reconfiguration or loss of operational flexibility.
3Ease of manufacture
If general electricity rate settlement without floor-specific analysis is applied, then administrative simplicity is maintained, but reasonable rate distribution based on actual usage cannot be achieved
Solution Approach 1:
The system segments electricity rate settlement by floor based on extracted operation information. Instead of applying a uniform rate, the control unit divides the building into multiple floors and calculates separate operation frequencies and usage patterns for each floor. This segmentation enables precise, usage-based rate distribution that reflects actual elevator utilization by different floors while maintaining automated calculation simplicity.
Data Source
AI summary
The present disclosure relates to a method for predictive maintenance and high efficiency operation through elevator analysis, and the method includes: a predictive maintenance step of collecting operation information of an operation unit in a normal state and operation information of the operation unit, which appears before a failure occurs, and detecting an abnormal symptom of the operation unit operating in real time based on the collected operation information so as to induce stable predictive maintenance of the operation unit of the elevator; and a high efficiency operation step of analyzing the operation information of the elevator operation unit in real time based on the operation information of the operation unit in the normal state to extract the operation information of an elevator, and controlling a door-closing time for the elevator based on the extracted operation information so as to induce efficient operation of the elevator.