Scheduling Tree-Like Multi-Cluster Tools
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Solution Overview
Problem
Scheduling a tree-like multi-cluster tool to generate an optimal one-wafer cyclic schedule is challenging due to the complexity of coordinating robot activities and determining robot waiting times in a process-dominant system with wafer residency time constraints.
Innovation Solution
A computer-implemented method using Petri Net modeling to determine robot waiting times and develop a CTC-Check algorithm for computing candidate values, ensuring a one-wafer cyclic schedule by minimizing robot waiting times and coordinating activities across multiple robots in a tree-like multi-cluster tool with a serial topology.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If robot waiting times are reduced to improve productivity, then cycle time decreases and throughput increases, but coordinating robot activities across multiple clusters becomes more complex and may violate wafer residency time constraints
Solution Approach 1:
The patent segments the tree-like multi-cluster tool into multiple cluster-tool-chains (CTCs), each representing a serial sequence of clusters. By decomposing the complex scheduling problem into smaller CTC segments, the patent enables independent analysis and optimization of each chain while maintaining coordination across the entire system. This segmentation allows for manageable scheduling complexity while achieving optimal throughput through coordinated robot waiting times across segments.
Solution Approach 2:
The patent calculates robot waiting times in advance by analyzing the processing times and transport times of each wafer through the cluster tool chains. By determining optimal waiting times before actual wafer processing begins, the system can coordinate robot activities to minimize cycle time while ensuring wafer residency time constraints are met. This preliminary calculation of waiting times allows the system to achieve maximum productivity without real-time complex coordination.
2Loss of time
If robot waiting times are minimized to achieve optimal cycle time, then manufacturing efficiency improves, but the risk of violating wafer residency time constraints increases
Solution Approach 1:
The patent incorporates feedback mechanisms by continuously monitoring wafer processing status and comparing actual timing against calculated optimal schedules. The system uses this feedback to adjust robot waiting times dynamically, ensuring that minimized cycle times do not violate wafer residency time constraints. This feedback loop maintains reliability while achieving near-optimal cycle times by making real-time corrections to the preliminary schedule.
Solution Approach 2:
The patent optimizes cycle time by systematically adjusting robot waiting time parameters across different cluster-tool-chains. By changing these timing parameters in a coordinated manner and analyzing their impact on both cycle time and constraint satisfaction, the system identifies optimal parameter sets that minimize loss of time while maintaining reliability. This parameter optimization ensures that wafer residency time constraints are met while achieving the shortest possible cycle time.
3Ease of operation
If a one-wafer cyclic schedule is implemented to simplify coordination, then scheduling ease improves, but the ability to handle process-dominant systems with residency constraints is limited
Solution Approach 1:
The patent develops a universal scheduling framework that can handle both simple and complex scenarios including process-dominant systems with wafer residency time constraints. The framework uses cluster-tool-chain decomposition and systematic waiting time calculation that works across different tool configurations and constraint types. This multi-functional approach maintains scheduling ease while significantly improving adaptability to handle various constraint scenarios through a unified methodology.
Solution Approach 2:
The patent adds the dimension of cluster-tool-chain decomposition to the traditional one-wafer cyclic scheduling approach. By organizing clusters into serial chains and analyzing waiting times across this additional dimensional structure, the system maintains the simplicity of cyclic scheduling while gaining the capability to handle complex constraints. This dimensional change allows the scheduling system to manage process-dominant systems with residency constraints without sacrificing operational ease.
Data Source
AI summary
The scheduling problem of a multi-cluster tool with a tree topology whose bottleneck tool is process-bound is investigated. A method for scheduling the multi-cluster tool to thereby generate an optimal one-wafer cyclic schedule for this multi-cluster tool is provided. A Petri net (PN) model is developed for the multi-cluster tool by explicitly modeling robot waiting times such that a schedule is determined by setting the robot waiting times. Based on the PN model, sufficient and necessary conditions under which a one-wafer cyclic schedule exists are derived and it is shown that an optimal one-wafer cyclic schedule can be always found. Then, efficient algorithms are given to find the optimal cycle time and its optimal schedule. Examples are used to demonstrate the scheduling method.