Conveyor Drive Configuration for Dynamic Package Merging Control
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Solution Overview
Problem
The control engineering of dynamic gapper systems in intralogistics is complex due to multiple parallel conveyor sections and conveyor sub-belts, requiring sophisticated adjustments for different package sizes and mechanical designs, and is challenging to optimize dynamically while preventing malfunctions like collisions.
Innovation Solution
A computer-implemented method using machine learning techniques, specifically supervised learning and reinforcement learning, to determine configuration data for conveyor subsection drives, allowing for automated optimization of conveyor speeds and intervals, thereby improving throughput and regularity of package delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple parallel conveyor sections and conveyor sub-belts are used to achieve dynamic gapper function, then package merging and defined interval placement are improved, but control engineering complexity increases significantly
Solution Approach 1:
The patent replaces traditional mechanical control systems with a computer-based control system that uses sensors to detect package positions and a computing unit to calculate and control drive speeds. This substitution of mechanical control with electronic/computer-based control reduces control engineering complexity while maintaining the ability to merge packages and maintain defined intervals.
Solution Approach 2:
The patent dynamically adjusts drive parameters (speeds of conveyor sub-belts) based on real-time package positions detected by sensors. The computing unit calculates optimal speed parameters to achieve package merging and defined interval placement, allowing the system to adapt to varying package sizes and positions without complex mechanical reconfiguration.
2Productivity
If conveyor subsections are accelerated and decelerated independently to optimize throughput dynamically, then productivity is improved, but adjustment complexity for different mechanical designs increases
Solution Approach 1:
The patent implements dynamic control where the computing unit continuously adjusts the speeds of individual conveyor sub-belts based on real-time package positions and desired throughput. This dynamic parameter adjustment allows optimization of throughput while the computer-based system automatically handles the complexity of coordinating multiple independent drives, eliminating manual adjustment complexity for different mechanical designs.
3Reliability
If sophisticated control algorithms are used to prevent collisions and optimize package intervals, then reliability is improved, but system complexity increases
Solution Approach 1:
The patent employs a feedback control system where sensors continuously detect package positions and feed this information to the computing unit. The computing unit processes this feedback to adjust drive speeds in real-time, preventing collisions and maintaining defined package intervals. This closed-loop feedback mechanism improves reliability while the automated computational process manages the control complexity.
Data Source
AI summary
A method for configuration of a controlled drive application of a logistics system. The logistics system includes parallel conveying paths for piece goods. Each conveying path includes sub-conveying paths which are each accelerated or delayed to merge the piece goods on a single output conveying path with defined spacing. A system model of the logistics system is firstly determined by operating data of the logistics system which include sensor values of the logistics system and changes to control variables. A control function is determined, which includes configuration data for the drives, with at least one control action being performed on the precondition of one or more performance features that are to be achieved in the system model, during which control action the operating data is simulated for a plurality of time steps.