Development of a distributed process mining system for reactive ion etching enhancement

K. F. Tsang; Henry C. W. Lau; S. K. Kwok

doi:10.1109/INDIN.2006.275794

Development of a distributed process mining system for reactive ion etching enhancement

K. F. Tsang
, Henry C. W. Lau
, S. K. Kwok

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

4 Citations (Scopus)

Abstract

A Distributed Process Mining System (DPMS) is discussed in this paper which aims to optimize the process in order to offer shorter production time, easier quality defect identification and higher customer satisfaction. This proposed system is equipped with the idea of "distributed process mining" discovering the hidden relationships between each working decision in distributed manner. This method incorporates the On-line Analytical Processing (OLAP) and the decision tree-based Artificial Neural Networks (ANNs) algorithms into decision making for ensuring "doing the right things" within the process and relevant workflow. A case study of using Reactive Ion Etching (RIE) in a magnetic head manufacturer is included. © 2006 IEEE.

Original language	English
Title of host publication	2006 IEEE International Conference on Industrial Informatics, INDIN'06
Pages	282-287
DOIs	https://doi.org/10.1109/INDIN.2006.275794
Publication status	Published - 2007
Externally published	Yes
Event	2006 IEEE International Conference on Industrial Informatics, INDIN'06 - Singapore, Singapore Duration: 16 Aug 2006 → 18 Aug 2006

Conference

Conference	2006 IEEE International Conference on Industrial Informatics, INDIN'06
Place	Singapore
City	Singapore
Period	16/08/06 → 18/08/06

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10.1109/INDIN.2006.275794

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@inproceedings{5515a4afe62d4eb7b92a06937b529c8f,

title = "Development of a distributed process mining system for reactive ion etching enhancement",

abstract = "A Distributed Process Mining System (DPMS) is discussed in this paper which aims to optimize the process in order to offer shorter production time, easier quality defect identification and higher customer satisfaction. This proposed system is equipped with the idea of {"}distributed process mining{"} discovering the hidden relationships between each working decision in distributed manner. This method incorporates the On-line Analytical Processing (OLAP) and the decision tree-based Artificial Neural Networks (ANNs) algorithms into decision making for ensuring {"}doing the right things{"} within the process and relevant workflow. A case study of using Reactive Ion Etching (RIE) in a magnetic head manufacturer is included. {\textcopyright} 2006 IEEE.",

author = "Tsang, \{K. F.\} and Lau, \{Henry C. W.\} and Kwok, \{S. K.\}",

year = "2007",

doi = "10.1109/INDIN.2006.275794",

language = "English",

isbn = "0780397010",

pages = "282--287",

booktitle = "2006 IEEE International Conference on Industrial Informatics, INDIN'06",

note = "2006 IEEE International Conference on Industrial Informatics, INDIN'06 ; Conference date: 16-08-2006 Through 18-08-2006",

}

Development of a distributed process mining system for reactive ion etching enhancement. / Tsang, K. F.; Lau, Henry C. W.; Kwok, S. K.
2006 IEEE International Conference on Industrial Informatics, INDIN'06. 2007. p. 282-287 4053401.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Development of a distributed process mining system for reactive ion etching enhancement

AU - Tsang, K. F.

AU - Lau, Henry C. W.

AU - Kwok, S. K.

PY - 2007

Y1 - 2007

N2 - A Distributed Process Mining System (DPMS) is discussed in this paper which aims to optimize the process in order to offer shorter production time, easier quality defect identification and higher customer satisfaction. This proposed system is equipped with the idea of "distributed process mining" discovering the hidden relationships between each working decision in distributed manner. This method incorporates the On-line Analytical Processing (OLAP) and the decision tree-based Artificial Neural Networks (ANNs) algorithms into decision making for ensuring "doing the right things" within the process and relevant workflow. A case study of using Reactive Ion Etching (RIE) in a magnetic head manufacturer is included. © 2006 IEEE.

AB - A Distributed Process Mining System (DPMS) is discussed in this paper which aims to optimize the process in order to offer shorter production time, easier quality defect identification and higher customer satisfaction. This proposed system is equipped with the idea of "distributed process mining" discovering the hidden relationships between each working decision in distributed manner. This method incorporates the On-line Analytical Processing (OLAP) and the decision tree-based Artificial Neural Networks (ANNs) algorithms into decision making for ensuring "doing the right things" within the process and relevant workflow. A case study of using Reactive Ion Etching (RIE) in a magnetic head manufacturer is included. © 2006 IEEE.

UR - https://www.scopus.com/pages/publications/38949085203

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-38949085203&origin=recordpage

U2 - 10.1109/INDIN.2006.275794

DO - 10.1109/INDIN.2006.275794

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 0780397010

SN - 9780780397019

SP - 282

EP - 287

BT - 2006 IEEE International Conference on Industrial Informatics, INDIN'06

T2 - 2006 IEEE International Conference on Industrial Informatics, INDIN'06

Y2 - 16 August 2006 through 18 August 2006

ER -

Development of a distributed process mining system for reactive ion etching enhancement

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