Semiconductor Lot Dispatching With Shortest-Idle-Time Tool Allocation
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Solution Overview
Problem
Automated material handling systems in semiconductor fabrication facilities face inefficiencies in processing super hot run (SHR) wafers due to incorrect tool allocation, leading to reduced production capacity and process efficiency, especially when manual re-assignment is required during tool events.
Innovation Solution
A system with a forecast engine and execution engine that pre-assigns tools based on arrival and process durations, utilizing a database to optimize tool allocation and dynamically re-assign tools during events, ensuring efficient processing of SHR wafers by identifying and utilizing tools with the shortest idle times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual re-assignment of tools is performed during tool events, then flexibility in handling tool events is improved, but production capacity and process efficiency deteriorate due to delays and incorrect tool allocation
Solution Approach 1:
The system performs preliminary action by pre-calculating and pre-assigning tools to process stages before tool events occur. The forecast engine predicts future tool requirements and makes assignments in advance, so that when tool events happen, the re-assignment can be executed immediately without manual intervention or production delays.
Solution Approach 2:
The system implements self-service by enabling automatic tool re-assignment without human intervention. When a tool event occurs, the execution engine automatically detects the event and re-assigns tools based on pre-calculated forecasts, eliminating the need for manual re-assignment and its associated delays.
2Productivity
If tools are pre-assigned based on forecasted arrival and process durations, then production capacity is improved, but device complexity increases due to the forecast and execution engine system
Solution Approach 1:
The system applies segmentation by dividing the complex tool allocation problem into two independent modules: a forecast engine that calculates optimal tool assignments based on arrival and process durations, and an execution engine that implements the assignments and handles re-assignment during tool events. This modular structure manages complexity while maintaining high production capacity.
3Productivity
If correct tool allocation is implemented through forecast and execution engines, then process efficiency is improved, but loss of time increases due to real-time monitoring and re-assignment operations
Solution Approach 1:
The forecast engine performs preliminary calculations of tool arrival and process durations before production begins. By pre-determining optimal tool assignments, the system eliminates the need for time-consuming real-time decision-making during tool events, thus improving process efficiency without adding significant cycle time.
Data Source
AI summary
A method is disclosed that includes the operations below: determining, by a processing unit, that arrival times of a lot arrived at N process stages are less than processing times of the lot predetermined to be processed at the N process stages, N being a positive integer; comparing, by the processing unit, idle times of multiple tools in the N process stages; and processing the lot with a first tool of the tools at each one of the N process stages, wherein the first tool of the tools has a shortest idle time.