Semiconductor Demand Data Mining and Knowledge Discovery for Optimization of Capacity Allocation
Date Issued
2004
Date
2004
Author(s)
DOI
922213E002021
Abstract
The demand signal is the most unreliable source of
information that plagues the operation effectiveness in a
demand-supply network. Moreover, the demand uncertainty
is not only propagated but also magnified over the network
and causes a chain effect on the operation quality of the
entire supply chain. Semiconductor manufacturing network is
one of the most complicated demand-supply networks and
thus suffers greatly from the untrustworthy demand
information. To manage the demand variability, appropriate
demand grouping and statistical forecasting approaches are
known to be effective. In the first year of this research, we
have analytically studied the effect of grouping and
forecasting interrelated demands and derived useful
knowledge to help practitioners make quality demand
planning decisions. In this year’s research, demand-grouping
strategies for capacity allocation will be developed based on
the knowledge discovered in the first year. The effect on the
overall equipment effectiveness (OEE) is then explored. The
effects of demand grouping for equipment capacity allocation
are then modeled mathematically. The model is aimed to help
practitioners comprehend how demand plans work together
with capacity allocation to affect the OEE.
Subjects
Demand Planning
Capacity Allocation
Overall
Equipment Effectiveness (OEE)
Equipment Effectiveness (OEE)
Publisher
臺北市：國立臺灣大學工業工程學研究所
Type
report
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