Intelligent sampling decision scheme based on the AVM system

Wafer inspection plays a significant role in monitoring the quality of wafers production for continuous improvement. However, it requires measuring tools and additional cycle time to do real metrology, which is costly and time-consuming. Therefore, reducing sampling rate to as low as possible is a h...

Full description

Saved in:
Bibliographic Details
Published in:International journal of production research 2015-04, Vol.53 (7), p.2073-2088
Main Authors: Cheng, Fan-Tien, Chen, Chun-Fang, Hsieh, Yao-Sheng, Huang, Hsuan-Heng, Wu, Chu-Chieh
Format: Article
Language:English
Subjects:
Continuous improvement
Cycle time
Industrial engineering
Inspection
intelligent sampling decision (ISD) scheme
Metrology
Monitoring
Monitors
performance analysis
Production costs
Production management
production systems
Quality control
Sampling
Sampling techniques
Studies
virtual metrology
Wafers
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Wafer inspection plays a significant role in monitoring the quality of wafers production for continuous improvement. However, it requires measuring tools and additional cycle time to do real metrology, which is costly and time-consuming. Therefore, reducing sampling rate to as low as possible is a high priority to reduce production cost. Several sampling methods in the literature were proposed to achieve this goal. They utilised real sampling inspections as the representatives for the other related wafers to monitor the whole production process. Under the condition of stable manufacturing process, virtual metrology (VM) may be applied to monitor the quality of wafers, while real metrology is unavailable. Therefore, the sampling rate may further be reduced with a sampling decision scheme being designed according to reliable VM. Nevertheless, once a new production variation occurs between planned samplings and no real metrology is available during this period for updating the VM models, un-reliable VM predictions may be produced. The authors have developed the automatic virtual metrology (AVM) system for various VM applications. Therefore, this paper focuses on applying various indices of the AVM system to develop an intelligent sampling decision scheme for reducing sampling rate, while VM accuracy is still sustained.
ISSN:0020-7543
1366-588X
DOI:10.1080/00207543.2014.955924