Additive Manufacturing Task Assignment for Adaptive Build Volumes
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Solution Overview
Problem
Additive manufacturing systems face inefficiencies in resource utilization and object generation throughput due to the inability to dynamically reassign object generation tasks across multiple apparatus, leading to incomplete objects and significant material waste when a build volume is canceled.
Innovation Solution
A method is introduced to assign object generation tasks to additive manufacturing apparatus based on status indicators that include adaptable build volume information, priority levels, and post-processing capabilities, allowing for reconfiguration of virtual build volumes to accommodate new tasks and optimize resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If object generation tasks are assigned to additive manufacturing apparatus without dynamic reassignment capability, then task allocation is simple, but resource utilization is low and productivity decreases
Solution Approach 1:
The patent implements dynamic task assignment by allowing tasks to be reassigned between additive manufacturing apparatus based on real-time status indicators. The system transitions from static task allocation to dynamic reassignment, where tasks can be moved between apparatus that become available, thereby improving resource utilization and productivity without requiring complex manual intervention.
Solution Approach 2:
The system employs feedback mechanisms by continuously monitoring status indicators of additive manufacturing apparatus and using this information to make informed task assignment decisions. The feedback loop enables the system to adapt task allocation based on current system state, improving productivity while maintaining manageable complexity through automated decision-making.
2Loss of time
If build volume processing is canceled when delays occur, then time delay is reduced, but material waste increases significantly
Solution Approach 1:
The system performs preliminary actions by proactively detecting delays and reassigning tasks before cancellation becomes necessary. By implementing early intervention through task reassignment to available apparatus, the system avoids the need to cancel entire build volumes, thereby reducing material waste while still addressing time delays effectively.
Solution Approach 2:
Instead of discarding entire build volumes when delays occur, the system recovers by reassigning affected tasks to other available apparatus. This approach salvages the build material by continuing production through alternative resources, transforming what would be waste into productive output.
3Productivity
If multiple objects are processed in a single build volume, then productivity increases, but the system becomes less adaptable to new tasks
Solution Approach 1:
The patent applies dynamics by enabling flexible reassignment of tasks within the multi-object build volume context. When new tasks arrive or priorities change, the system dynamically adjusts task allocation among apparatus, maintaining both high productivity from batch processing and adaptability to new requirements through real-time task management.
Solution Approach 2:
The task assignment system achieves universality by being capable of handling multiple object generation tasks simultaneously across different apparatus while remaining adaptable to new task types and priorities. The system functions as a multi-functional task management platform that can accommodate diverse manufacturing requirements within a unified framework.
4Loss of substance
If build volume processing continues without interruption, then material utilization is maximized, but loss of time increases due to inability to respond to new tasks
Solution Approach 1:
The system resolves this contradiction through dynamic task assignment that allows flexible response to new tasks while maintaining continuous build volume processing. When new high-priority tasks arrive, the system dynamically reassigns tasks between apparatus rather than canceling builds, thereby responding quickly to new requests while maximizing material utilization in ongoing builds.
Data Source
AI summary
In an example, a method includes receiving object model data at a processor, the object model data characterising an object to be generated using additive manufacturing. The method may further include receiving a status indicator for each of a plurality of additive manufacturing apparatus, the status indicator comprising, for each apparatus, an indication of an adaptable build volume. The processor may assign an object generation task corresponding to the received object model data to one of the plurality of additive manufacturing apparatus based on the status indicators.


