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A dynamic system regulation measure for increasing effective capacity: the X-factor theory

Authors: D. Delp; J. Si; Y. Hwang; B. Pei;

A dynamic system regulation measure for increasing effective capacity: the X-factor theory

Abstract

Due to the complex nature of semiconductor manufacturing it is evident that a single scheduling or regulation technique cannot best optimize the system dynamics for reducing cycle time and increasing throughput. The throughput of the system can increase to the effective capacity level of the system. When the throughput of the system approaches the effective capacity the product cycle time can dramatically increase. The "knee" of the performance curve indicates an operating point for fabs to maximize throughput while keeping the product cycle time relatively low. By increasing the effective capacity, i.e. adding a machine or improving a process, the product cycle time can be lowered or the system throughput increased by producing a shift in the "knee" of the performance curve. The bottleneck, typically defined as the most heavily utilized machine group, is often the target for increasing the system effective capacity. We will analyze the bottleneck along with other system capacity regulation measures to systematically study the relationship between bottleneck, X-factor, cycle time, and throughput measurements.

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Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
10
Average
Top 10%
Top 10%
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