Equipment selection knowledge base system for industrial styrene process

Weimin Zhong; Shuming Liu; Feng Wan; Zhi Li

doi:10.1016/j.cjche.2017.10.009

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Equipment selection knowledge base system for industrial styrene process

Selected Papers from the Chinese Process Systems Engineering Annual Meeting 2017 | Updated：2026-01-06

- Equipment selection knowledge base system for industrial styrene process
- Equipment selection knowledge base system for industrial styrene process
- 中国化学工程学报（英文版） 2018年26卷第8期页码：1707-1712
- Affiliations：
  
  Key Laboratory of Advanced Control and Optimization for Chemical Processed of Ministry of Education, East China University of Science and Technology,Shanghai,China,200237
- Author bio：
- Funds：
- DOI：10.1016/j.cjche.2017.10.009
  中图分类号：
- 纸质出版：2018
- Accepted：
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Weimin Zhong, Shuming Liu, Feng Wan, 等. Equipment selection knowledge base system for industrial styrene process[J]. 中国化学工程学报（英文版）, 2018,26(8):1707-1712.

Weimin Zhong, Shuming Liu, Feng Wan, Zhi Li. Equipment selection knowledge base system for industrial styrene process[J]. Chin.J.Chem.Eng., 2018, 26(8): 1707-1712.
Weimin Zhong, Shuming Liu, Feng Wan, 等. Equipment selection knowledge base system for industrial styrene process[J]. 中国化学工程学报（英文版）, 2018,26(8):1707-1712. DOI： 10.1016/j.cjche.2017.10.009.

Weimin Zhong, Shuming Liu, Feng Wan, Zhi Li. Equipment selection knowledge base system for industrial styrene process[J]. Chin.J.Chem.Eng., 2018, 26(8): 1707-1712. DOI： 10.1016/j.cjche.2017.10.009.

摘要

Abstract

Equipment selection for industrial process usually requires the extensive participation of industrial experts and technologists

which causes a serious waste of resources. This work presents an equipment selection knowledge base system for industrial styrene process (S-ESKBS) based on the ontology technology. This structure includes a low-level knowledge base and a top-level interactive application. As the core part of the S-ESKBS

the low-level knowledge base consists of the equipment selection ontology library

equipment selection rule set and Pellet inference engine. The top-level interactive application is implemented using S-ESKBS

including the parsing storage layer

inference query layer and client application layer. Case studies for the industrial styrene process equipment selection of an analytical column and an alkylation reactor are demonstrated to show the characteristics and implementability of the S-ESKBS.

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