Hoisting Speed Control for Predictive Maintenance Accuracy
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Solution Overview
Problem
Existing methods for predictive maintenance in hoisting appliances face challenges in efficiently covering all operating points due to high computational costs and operational burdens, leading to inaccurate predictions and decreased productivity when isolating motions, which hampers fully automated systems.
Innovation Solution
A method and apparatus for optimizing hoisting appliance operations by selecting speed parameters that minimize travel time while ensuring predictive maintenance accuracy by identifying and operating within zones with sufficient known operating points, using a digital twin model and speed synchronizing curves to synchronize movable parts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a digital twin model is used for predictive maintenance with comprehensive data collection across all operating points, then prediction accuracy is improved, but computational cost and operational burden increase significantly
Solution Approach 1:
The patent segments the continuous operating space into discrete operating zones based on data density thresholds. Instead of attempting to cover all possible operating points uniformly, the system divides the parameter space (speeds, loads, temperatures) into zones where sufficient data exists for reliable predictions, eliminating the need for computationally expensive comprehensive coverage.
Solution Approach 2:
The patent changes the approach from collecting data across all parameter combinations to identifying zones where data density meets minimum thresholds. The system transforms the problem from exhaustive sampling to selective zone identification, where only operating zones with sufficient data density are utilized for predictive maintenance decisions.
2Productivity
If the hoisting appliance operates at high speeds to maintain productivity, then production performance is improved, but predictive maintenance accuracy deteriorates due to insufficient data density
Solution Approach 1:
The patent implements dynamic speed parameter selection that adapts to the identified operating zones. Instead of maintaining constant high speeds, the system dynamically adjusts speed parameters to keep the hoisting appliance within zones where data density thresholds are met, allowing high productivity when conditions permit while ensuring prediction accuracy when data is sufficient.
Solution Approach 2:
The system incorporates feedback mechanisms where the control device continuously monitors the current operating point against the map of identified zones. Based on this feedback, the system adjusts speed parameters in real-time to maintain operation within zones of sufficient data density, creating a closed-loop control system that balances productivity and prediction accuracy.
3Measurement precision
If speed parameters are restricted to maintain operation within zones of sufficient data density, then predictive maintenance accuracy is improved, but travel time increases and productivity decreases
Solution Approach 1:
The patent performs preliminary identification of operating zones with sufficient data density before actual operation. The control device pre-maps the operating space, identifying which zones meet data density thresholds. This preliminary action allows the system to plan optimal paths through identified zones, minimizing travel time while ensuring operation remains within regions suitable for accurate predictive maintenance.
Solution Approach 2:
The system applies partial action by selecting speed parameters that are sufficient to maintain operation within valid zones rather than requiring maximum speeds at all times. The control device chooses speed values that are adequate for productive operation within the constraints of identified zones, rather than imposing excessive speed restrictions that would unnecessarily reduce productivity.
Data Source
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AI summary
The invention relates to a method for operating a hoisting appliance spanning a hoisting area, the hoisting appliance comprising N≥2 movable parts (2, 3, 4) for the transport of a load (6) from a starting point to a destination point, the N movable parts being configured for a linear movement along any of three X, Y and Z orthogonal axes or for an angular movement. The method comprises choosing speed parameters for displacement of the N movable parts for transporting the load from the starting point to the destination point, by, in a control device: determining (S1, S2) a set of speed parameters for displacement of said N movable parts belonging to an operating zone (71, 72, 73) for which a predictive maintenance function of said hosting appliance yields results which are above a determined accuracy threshold; selecting (S3), among said set, speed parameters which minimize a travel time of said load from said starting point to said destination point.