Self-Driving Vehicle Conveyance for In-Transit Assembly Operations
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Solution Overview
Problem
Traditional industrial assembly processes are inefficient due to fixed conveyance infrastructure and complex scheduling of mobile-transport units, which lead to uncertainties in production time, especially when unique sequences of finished goods are required.
Innovation Solution
The implementation of a flexible conveyance system using self-driving vehicles that transport assemblies between workstations, planning paths and speeds based on mission instructions, and utilizing sensors to navigate and manage obstacles, while performing operations on the assemblies in transit.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If fixed conveyance infrastructure (conveyor belts, chain conveyors) is used, then assembly line stability is improved, but adaptability to different production sequences deteriorates
Solution Approach 1:
The patent replaces static fixed conveyor infrastructure with dynamic mobile-transport units that can autonomously navigate the facility. These vehicles dynamically adjust their paths, speeds, and destinations based on real-time production requirements, enabling the system to adapt to different production sequences while maintaining operational stability through coordinated control
Solution Approach 2:
Mobile-transport units serve multiple functions: they transport workpieces between workstations, navigate around obstacles, adapt to changing production sequences, and coordinate with various work cells. This multi-functionality replaces the need for dedicated fixed conveyors for each transport path, providing both stability and adaptability
2Adaptability or versatility
If mobile-transport units make separate round trips for each work cell operation, then adaptability to unique production sequences is improved, but device complexity deteriorates
Solution Approach 1:
The control system implements feedback mechanisms where mobile-transport units report their status, location, and workload to the central controller, which adjusts scheduling in real-time. This feedback loop enables complex multi-vehicle coordination without requiring centralized micromanagement of each round trip, reducing scheduling complexity while maintaining adaptability
Solution Approach 2:
Mobile-transport units are equipped with autonomous navigation and obstacle detection capabilities, allowing them to self-manage their transport tasks without constant human intervention. The vehicles independently plan paths, avoid obstacles, and coordinate with work cells, reducing the operational complexity of managing multiple round trips
3Adaptability or versatility
If workpieces are stored at work cells until availability, then production sequence flexibility is improved, but production time uncertainty deteriorates
Solution Approach 1:
Mobile-transport units maintain continuous motion and coordination with work cells, eliminating idle waiting time. Instead of storing workpieces and creating gaps in production, the system continuously transports workpieces to the next available workstation, maintaining flow continuity while adapting to sequence changes through real-time scheduling adjustments
Data Source
AI summary
Systems and methods for flexible conveyance in an assembly-line or manufacturing process are disclosed. A fleet of self-driving vehicles and a fleet-management system can be used to convey workpieces through a sequence of workstations at which operations are performed in order to produce a finished assembly. An assembly can be transported to a first workstation using a self-driving vehicle, where an operation is performed on the assembly. Subsequently, the assembly can be transported to a second workstation using the self-driving vehicle. The operation can be performed on the assembly while it is being conveyed by the self-driving vehicle.