NDLI: Target setting with consideration of target-induced operation variability for performance improvement of semiconductor fabrication

Content Provider	IEEE Xplore Digital Library
Author	Yu-Ting Kao Shi-Chung Chang Chun-Ming Chang
Copyright Year	2014
Description	Author affiliation: Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei, Taiwan (Shi-Chung Chang; Chun-Ming Chang) \|\| Grad. Inst. of Ind. Eng., Nat. Taiwan Univ., Taipei, Taiwan (Yu-Ting Kao)
Abstract	Production target setting is common in practice to guide operations such as machine allocation and lot dispatching to achieve master production schedule (MPS). As targets affect operations and hence wafer flows, wafer flow estimation under given daily production targets is a basis of adjusting targets and machine allocation. This paper presents an innovative design of target setting algorithm (TaSIV) that develops the target-tracking service model by characterizing target-induced mean and variability and designs a hybrid flow time approximation by exploiting transient tendon queue analysis between two stages to set targets for improving production performance. The design first adopts a Bernoulli trial with proportional-to-target probability to model the target-tracking machine allocation and FIFO dispatching and then characterize the target-induced variability (TIV). To capture the effect of TIV on wafer flows, the design then approximates the time for the last wafer in initial WIP of a stage to finish processing at the next stage, named two-stage penetration time approximation, APT-2, by using Markov chain analysis of tandem queues with given initial number of wafers. By Integrating APT-2 into a recursive algorithm, SOPEA, the design estimates penetration time of multiple stages and wafer flows in a fab. Finally, our design integrates APT-2/SOPEA into a fixed-point iteration between wafer flow estimation and capacity allocation for target setting with consideration of TIV. Over a mini-Fab example and given targets generated by TaSIV, simulation of proportional-to-target machine allocation and FIFO dispatching demonstrates that targets generated by TaSIV reduces over-optimism and close to actual moves by 30.7% of bottleneck machine groups as compared to a mean-value based scheme frequently adopted by practitioners of fab operation management. TaSIV also leads to reductions of 1.2% in mean cycle time and 15.4% in cycle time variance at 1.1% throughput increase.
Starting Page	774
Ending Page	779
File Size	449795
Page Count	6
File Format	PDF
e-ISBN	9781479952830
DOI	10.1109/CoASE.2014.6899413
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-08-18
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Resource management Production Estimation Dispatching Approximation methods Algorithm design and analysis Target tracking machine allocation variability Daily wafer flow estimation daily target setting
Content Type	Text
Resource Type	Article

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