Substrate Processing Task Scheduling with Dependency Graph Reordering
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Solution Overview
Problem
Conventional substrate processing systems experience significant delays and inefficiencies due to interruptions in tasks, as they follow a fixed order and halt all subsequent tasks when one task is delayed or fails, leading to prolonged start-up times and reduced productivity.
Innovation Solution
A dynamic scheduling method based on task dependencies is implemented, where a processing device determines and generates a dependency graph of tasks, allowing for topological sorting to create a flexible schedule that continues tasks not dependent on interrupted tasks, thereby minimizing delays and optimizing start-up times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a fixed order scheduling method is used, then task execution simplicity is maintained, but system productivity decreases due to delays propagating through all subsequent tasks
Solution Approach 1:
The patent implements dynamic scheduling by constructing a dependency graph that represents task relationships and using topological sorting to generate execution orders adaptively. This allows the system to dynamically adjust task execution based on completion status and dependencies, rather than following a rigid fixed order, thereby improving productivity without excessive complexity
Solution Approach 2:
The scheduling system segments tasks into independent units with defined dependencies, represented as nodes in a dependency graph. This segmentation allows individual tasks to be processed independently when their dependencies are met, preventing delay propagation and improving overall system productivity while maintaining manageable complexity through modular task organization
2Reliability
If all subsequent tasks are halted when one task is delayed, then task dependency correctness is maintained, but start-up time increases significantly
Solution Approach 1:
The system performs preliminary actions by pre-establishing the dependency graph and topologically sorting tasks before execution begins. This preliminary organization identifies which tasks can proceed independently and which must wait for dependencies, allowing the system to maintain dependency correctness while minimizing start-up time by immediately executing tasks that are ready
Solution Approach 2:
The patent enables continuity of useful action by allowing tasks that do not depend on delayed tasks to continue executing without interruption. The dependency graph and topological sort identify independent task chains that can proceed concurrently, ensuring that useful work continues throughout the system rather than halting entirely when one task is delayed, thus reducing start-up time while maintaining reliability
3Reliability
If a dynamic scheduling system with dependency graphs is implemented, then resilience to delays is improved, but computational complexity increases
Solution Approach 1:
The dynamic scheduling system uses dependency graphs to represent task relationships and applies topological sorting algorithms to determine execution orders adaptively. This dynamic approach allows the system to recalculate optimal schedules based on current task completion status, providing resilience to delays while managing computational complexity through efficient graph algorithms
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring task completion status and using this information to update the dependency graph and recalculate topological sorts. This feedback loop enables the system to adapt to delays dynamically, maintaining resilience while controlling computational complexity through incremental updates rather than complete recalculations
4Ease of operation
If tasks are executed in a fixed sequential order, then system control simplicity is maintained, but downtime increases when interruptions occur
Solution Approach 1:
The patent segments the task execution process into independent, dependency-defined units represented in a graph structure. This segmentation allows the system to identify and execute independent task chains separately, so that interruptions in one chain do not propagate to others, reducing downtime while maintaining operational simplicity through clear task boundaries and relationships
Data Source
AI summary
A method includes identifying a dependency graph of tasks of a substrate processing system. Responsive to determining that a first task of the tasks is unavailable, the method further includes determining an updated topological ordering of remaining tasks of a remaining subgraph of the dependency graph. The method further includes causing performance of the updated topological ordering of remaining tasks via the substrate processing system to produce one or more substrates.