Platform Lift Usage Monitoring for Predictive Maintenance
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Solution Overview
Problem
Existing platform lifts, particularly stairlifts, lack a systematic approach for determining when maintenance is needed, often relying on fixed intervals rather than usage-based criteria, which can miss abnormal conditions or misuse.
Innovation Solution
A method and arrangement that collect usage data, analyze it for abnormalities, and generate maintenance requests based on detected anomalies, using predefined definitions or historical data, employing self-learning algorithms and artificial intelligence to identify issues such as mechanical or electrical faults, misuse, and wear.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If fixed maintenance intervals are used, then maintenance scheduling is simple, but maintenance needs may be missed or performed unnecessarily
Solution Approach 1:
The maintenance system transitions from static fixed intervals to dynamic usage-based scheduling. The control unit continuously monitors usage data (number of trips, usage duration, load conditions) and dynamically adjusts maintenance timing based on actual wear patterns, ensuring maintenance is performed when truly needed rather than on a rigid schedule
Solution Approach 2:
The system implements feedback loops where usage data is continuously collected from sensors, analyzed by the control unit, and used to update maintenance schedules. The system provides feedback about maintenance status to users and can automatically generate maintenance requests when abnormal wear patterns are detected, creating a closed-loop system that adapts to actual equipment conditions
2Measurement precision
If usage data collection and analysis systems are implemented, then maintenance accuracy improves, but system complexity increases
Solution Approach 1:
The control unit serves multiple functions: it controls the platform lift operation, collects usage data from various sensors, analyzes the data for wear patterns, and generates maintenance schedules. By making the control unit multi-functional rather than adding separate dedicated systems for each function, the patent reduces overall system complexity while maintaining high measurement precision
Solution Approach 2:
The system performs self-monitoring and self-diagnosis of wear conditions. The control unit automatically analyzes usage data, detects abnormal wear patterns, and generates maintenance requests without requiring external monitoring systems or manual inspection, allowing the system to serve its own maintenance needs
3Reliability
If abnormality detection through usage data analysis is implemented, then operational safety improves, but data processing requirements increase
Solution Approach 1:
The system continuously monitors usage data and detects wear patterns before they lead to actual failures. By performing preliminary detection of abnormal conditions and generating maintenance requests in advance, the system prevents safety issues from developing, addressing the problem proactively rather than reactively
Data Source
Figure 1a~1b
Figure 2~3b
Figure 4a~4c
AI summary
Method for generating a maintenance request in connection with the use of a platform lift (1), in particular using a platform lift (1) for generating a maintenance request, in particular the platform lift is a stairlift (1), the lift comprising - a rail (2), - a drive unit (6) having a platform (8), in particular a chair (8), for driving along the rail (2), - at least one control unit (13) arranged at the drive unit (6), the method comprising the following steps: collecting a plurality of usage data (UD) of the platform lift (1); analyzing said collected usage data (UD) and detecting an abnormality in the current usage data (UD); generating a maintenance request (MR) in case that an abnormality has been detected during analyzing.