Manufacturing Time-Constraint Scheduling via Substrate Simulation
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Solution Overview
Problem
Manufacturing systems face challenges in managing time constraints across multiple operations, leading to difficulties in scheduling substrates to meet these constraints, which can result in substrates becoming unusable due to delays.
Innovation Solution
A method involving a processing device that receives requests to initiate operations with time constraints, determines candidate substrates, runs simulations to predict successful processing, and initiates operations to process the predicted number of substrates within the given time constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual scheduling methods are used to account for all time constraints and tool capacities, then scheduling accuracy may be maintained, but the complexity of the scheduling process increases significantly and becomes NP-hard
Solution Approach 1:
The patent creates a virtual copy of the manufacturing system through simulation models that replicate tool capacities, time constraints, and operation sequences. This virtual model allows scheduling decisions to be tested and validated without affecting the actual system, converting the NP-hard scheduling problem into a manageable simulation-based decision process.
Solution Approach 2:
The system performs preliminary simulation runs before actual production to predict substrate completion times and identify potential time constraint violations. By conducting these simulations in advance, the system proactively identifies scheduling issues and adjusts schedules before substrates are processed, preventing unusable substrates rather than reacting to problems after they occur.
2Reliability
If operators delay operations to satisfy time constraints, then substrate quality is maintained, but system throughput decreases and latency increases
Solution Approach 1:
The simulation system continuously monitors predicted substrate completion times against time constraint deadlines and provides feedback to the scheduling system. When violations are predicted, the system automatically adjusts operation schedules and substrate routing decisions, creating a closed-loop control system that balances time constraint satisfaction with throughput optimization rather than simple delay-based approaches.
Solution Approach 2:
The scheduling system dynamically adjusts operation timing and substrate routing based on real-time simulation results and actual system state. Instead of static delay schedules, the system continuously optimizes timing decisions based on current tool availability, substrate priorities, and predicted completion times, allowing flexible adaptation to changing conditions while maintaining time constraint compliance.
3Reliability
If simulations are run for significant time periods (6-24 hours) to account for all time constraints, then comprehensive scheduling decisions can be made, but computational time and resources increase
Solution Approach 1:
The patent divides the simulation time period into smaller discrete time steps or intervals, allowing the simulation to process scheduling decisions incrementally rather than as a single monolithic calculation. This segmentation enables the system to evaluate time constraints and tool capacities in manageable chunks, reducing computational complexity while maintaining comprehensive coverage of all constraints throughout the full production horizon.
Data Source
AI summary
A method for time constraint management at a manufacturing system is provided. A first request to initiate a set of operations to be run at the manufacturing system is received. The set of operations include one or more operations that each have one or more time constraints. A first set of candidate substrates to be processed during the set of operations is determined. A first simulation of the set of operations for the first set of candidate substrates is run over a first period of time. The simulation generates a first simulation output indicate a first number of candidate substrates that were successfully processed during each of the simulated set of operations to reach the end of the first time period. The set of operations is initiated at the manufacturing system to process the first number of candidate substrates over the first time period.