Bottleneck Prediction Method Based on Improved Adaptive Network-based Fuzzy Inference System (ANFIS) in Semiconductor Manufacturing System<sup>*</sup>

曹政才; 邓积杰; 刘民; 王永吉

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Bottleneck Prediction Method Based on Improved Adaptive Network-based Fuzzy Inference System (ANFIS) in Semiconductor Manufacturing System^*

Updated：2026-01-06

- Bottleneck Prediction Method Based on Improved Adaptive Network-based Fuzzy Inference System (ANFIS) in Semiconductor Manufacturing System^*
- Bottleneck Prediction Method Based on Improved Adaptive Network-based Fuzzy Inference System (ANFIS) in Semiconductor Manufacturing System^*
- 中国化学工程学报（英文版） 2012年20卷第6期页码：1081-1088
- Affiliations：
  
  1. College of Information Science and Technology, Beijing University of Chemical Technology,Beijing,China,100029
  2. Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, Southeast University,Nanjing,China,210096
  3. Tsinghua National Laboratory for Information Science and Technology,Beijing,China,100084
  4. State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences,Beijing,China,100190
- Author bio：
- Funds：
  
  Supported by the National Key Basic Research and Development Program of China (2009CB320602);the National Natural Science Foundation of China (60834004;61025018);the Open Project Program of the State Key Lab of Industrial ControlTechnology (ICT1108);the Open Project Program of the State Key Lab of CAD & CG (A1120);the Foundation of Key Laboratory of System Control and Information Processing (SCIP2011005);Ministry of Education;China
- DOI：
  中图分类号：
- 纸质出版：2012
- Accepted：
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曹政才, 邓积杰, 刘民, 等. Bottleneck Prediction Method Based on Improved Adaptive Network-based Fuzzy Inference System (ANFIS) in Semiconductor Manufacturing System^*[J]. 中国化学工程学报（英文版）, 2012,20(6):1081-1088.

[J]. Chinese Journal of Chemical Engineering, 2012, 20(6): 1081-1088.
曹政才, 邓积杰, 刘民, 等. Bottleneck Prediction Method Based on Improved Adaptive Network-based Fuzzy Inference System (ANFIS) in Semiconductor Manufacturing System^*[J]. 中国化学工程学报（英文版）, 2012,20(6):1081-1088. DOI：

[J]. Chinese Journal of Chemical Engineering, 2012, 20(6): 1081-1088. DOI：

摘要

Abstract

Semiconductor manufacturing (SM) system is one of the most complicated hybrid processes involved continuously variable dynamical systems and discrete event dynamical systems.The optimization and scheduling of semiconductor fabrication has long been a hot research direction in automation.Bottleneck is the key factor to a SM system

which seriously influences the throughput rate

cycle time

time-delivery rate

etc

.Efficient prediction for the bottleneck of a SM system provides the best support for the consequent scheduling.Because categorical data (product types

releasing strategies) and numerical data (work in process

processing time

utilization rate

buffer length

etc

.) have significant effect on bottleneck

an improved adaptive network-based fuzzy inference system (ANFIS) was adopted in this study to predict bottleneck since conventional neural network-based methods accommodate only numerical inputs.In this improved ANFIS

the contribution of categorical inputs to firing strength is reflected through a transformation matrix.In order to tackle high-dimensional inputs

reduce the number of fuzzy rules and obtain high prediction accuracy

a fuzzy c-means method combining binary tree linear division method was applied to identify the initial structure of fuzzy inference system.According to the experimental results

the main-bottleneck and sub-bottleneck of SM system can be predicted accurately with the proposed method.

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