Factory Machine Scheduling with Two-Stage Task Optimization
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Solution Overview
Problem
Current scheduling methods in semiconductor wafer manufacturing factories result in suboptimal production performance due to ineffective task prioritization, leading to low velocity, long cycle times, and incomplete or damaged products.
Innovation Solution
A system and method for generating a schedule for a group of machines in a factory, utilizing a computer system to receive tasks, allocate them using a first method, and then optimize the schedule using a second method to improve resource allocation and task prioritization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If predetermined rules are used to schedule tasks at each machine, then the scheduling process is simple and easy to implement, but the manufacturing performance is suboptimal with low velocity and long cycle times
Solution Approach 1:
The scheduling problem is segmented into two distinct phases: a first method that generates an initial feasible schedule using predetermined rules, and a second method that optimizes this schedule. This segmentation allows the system to maintain operational simplicity while achieving improved manufacturing performance through the optimization phase.
Solution Approach 2:
The first method performs preliminary scheduling actions using predetermined rules to create an initial schedule before the optimization phase. This preliminary action establishes a baseline schedule that the second method can then improve upon, separating the simplicity of rule-based scheduling from the complexity of optimization.
2Device complexity
If predetermined rules are used to prioritize tasks, then the scheduling system is easy to implement, but task completion is delayed and products are damaged
Solution Approach 1:
The scheduling system is divided into two methods: the first method provides simple predetermined rules for initial scheduling, while the second method introduces optimization to reduce cycle times and prevent product damage. This segmentation maintains system simplicity while addressing time loss issues.
Solution Approach 2:
The second optimization method uses feedback from the initial schedule to identify and correct suboptimal task prioritization. By analyzing the preliminary schedule and adjusting task priorities accordingly, the system reduces cycle times and prevents product damage without increasing overall system complexity significantly.
3Reliability
If a comprehensive schedule for all machines is generated, then the optimization is thorough, but the computational complexity and time required increases significantly
Solution Approach 1:
The scheduling approach is segmented into two distinct methods that work in sequence. The first method generates an initial schedule using predetermined rules, and the second method optimizes this schedule. This segmentation reduces computational complexity compared to generating a fully optimized schedule from scratch, while still achieving reliable optimization results.
Solution Approach 2:
The first method performs preliminary scheduling to establish a baseline schedule before optimization. This preliminary action reduces the search space for the second optimization method, thereby reducing computational complexity while maintaining optimization quality.
4Productivity
If tasks are allocated using predetermined rules, then the allocation process is fast and efficient, but the schedule is suboptimal resulting in low number of wafer moves per unit time
Solution Approach 1:
The scheduling process is segmented into two phases: fast predetermined rule-based allocation followed by optimization. This segmentation allows the system to quickly generate an initial schedule and then improve it to increase wafer moves per unit time while reducing cycle time.
Solution Approach 2:
The predetermined rules perform preliminary task allocation quickly and efficiently, establishing a baseline schedule. The subsequent optimization phase then improves this preliminary schedule to achieve higher wafer moves per unit time and reduced cycle times.
Data Source
AI summary
A method and system for generating a schedule of tasks for a group of machines to perform in a factory. The method and system are particularly applicable in semiconductor manufacturing in manufacturing semiconductor wafers. A first method is used to generate a schedule for the group of machines comprising allocating one task or a time-ordered list of several tasks to each machine in a group of machines. The schedule is then optimised using a second method.