AGV Material Movement Planning for Dynamic Factory Clearance
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Solution Overview
Problem
Automated guided vehicles face challenges in navigating and transporting materials efficiently in dynamic industrial environments due to changes in machine configurations and space requirements, leading to potential collisions with machines and human workers.
Innovation Solution
A computer-based method for generating a material movement plan that considers the dimensions of materials, stowage positions of vehicles, transport paths, and space requirements of machines, using machine learning models to optimize navigation and loading/unloading processes, ensuring safe and efficient transport.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated guided vehicles navigate through dynamic industrial environments with changing machine configurations, then material transport efficiency is improved, but collision risk with machines and workers increases
Solution Approach 1:
The system performs preliminary actions by generating a material movement plan before actual transport operations. The plan includes determining optimal transport paths, identifying space requirements of machines along the path, and calculating required clearance distances. This advance planning allows the vehicle to navigate efficiently while maintaining safe distances from dynamic obstacles, thus improving productivity without increasing collision risk.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring the dynamic industrial environment, including machine configurations and worker positions. The material movement plan is generated based on real-time notifications of space requirements and is adjusted according to feedback from the environment, enabling efficient navigation while maintaining safety through continuous adaptation.
2Reliability
If the computer generates a comprehensive material movement plan considering multiple constraints, then transport safety is improved, but computational complexity increases
Solution Approach 1:
The comprehensive material movement plan is segmented into multiple independent notification components: dimensions of material, stowage positions of vehicle, pickup and drop-off locations, and space requirements of machines. Each segment can be processed and validated independently, reducing computational complexity while maintaining the comprehensiveness needed for transport safety.
3Productivity
If the system optimizes stowage positions and transport paths, then material handling efficiency is improved, but planning time increases
Solution Approach 1:
The system performs preliminary optimization of stowage positions and transport paths by generating a material movement plan before execution. The plan includes pre-calculated optimal configurations based on material dimensions and vehicle capabilities, allowing efficient material handling during execution without time-consuming optimizations during operation.
Data Source
AI summary
A method, computer system, and a computer program product for material movement planning are provided. A computer receives a first notification of dimensions of a first material to be transported, a second notification of stowage positions of a first vehicle, a third notification of a pickup location and a drop-off location for the first material, and a fourth notification of space requirements of machines along a transport path. The computer generates a material movement plan for stowing the material on the first vehicle and for transporting the material along the transport path. The material movement plan is based on the dimensions of the material, the stowage positions of the first vehicle, the transport path, and the space requirements for the machines. The computer transmits the material movement plan for loading the first material into one of the stowage positions on the first vehicle according to the material movement plan.