Decentralized Material Flow Control via Self-Simulators
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Solution Overview
Problem
Centralized material flow systems are prone to bottlenecks and single points of failure, leading to reduced performance and reliability, as they cannot adapt to changing load conditions without a standby system, and decentralized approaches are inflexible and not performant due to high communication loads.
Innovation Solution
A decentralized material flow system with autonomous components that include self-simulators to predict future occupancy states, allowing modules to simulate their own future states and communicate with neighbors, enabling distributed forecasting and adaptive control without a central material flow computer.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a centralized material flow computer is used to manage occupancy status and predict future states, then system-wide forecast accuracy is improved, but system reliability deteriorates due to single point of failure and performance bottlenecks
Solution Approach 1:
The patent divides the centralized simulation function into distributed self-simulators integrated into each component. Each self-simulator independently predicts future occupancy states for its local component based on current status data and control parameters, eliminating the single point of failure while maintaining system-wide forecast capability through distributed intelligence
Solution Approach 2:
The self-simulators use current occupancy status data and control parameters as feedback inputs to continuously predict future states. This feedback mechanism allows each component to adaptively forecast its future occupancy and enable proactive material flow control decisions to prevent traffic jams and unbalanced loads
2Reliability
If a decentralized material flow system without central instance is implemented, then system reliability is improved by eliminating single point of failure, but forecast capability deteriorates due to lack of overall overview
Solution Approach 1:
Each component is equipped with a self-simulator that enables it to independently perform simulation and prediction functions. The self-simulator uses locally available current occupancy status and control parameters to forecast future states without requiring centralized coordination, allowing each component to serve its own forecasting needs autonomously
3Adaptability or versatility
If decentralized approaches with Internet routing mechanisms are used, then system flexibility is improved, but performance deteriorates due to high communication loads and lack of adaptability to route changes
Solution Approach 1:
The self-simulators perform preliminary simulation of future occupancy states before actual material flow decisions are made. By predicting future traffic conditions in advance, the system can proactively adjust control parameters and routing decisions to prevent traffic jams and unbalanced loads, improving throughput without requiring high communication overhead during critical decision moments
Data Source
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AI summary
The invention relates to a component of a material flow system for transporting goods, said component comprising a mechatronics arrangement with transport elements, sensors and actuators for transporting the goods, a control device for controlling the mechatronics arrangement, interfaces to adjacent components and the surroundings, and an internal simulator for determining the future state of the component. The internal simulator co-operates with internal simulators of other components of the material flow system, for determining a prognosis of the future state of the installation of the material flow system. The decentralised internal simulators can be synchronously or asynchronously activated.