Knowledge discovery from process operational data for assessment and monitoring of operator's performance

Citation
Ym. Sebzalli et al., Knowledge discovery from process operational data for assessment and monitoring of operator's performance, COMPUT CH E, 24(2-7), 2000, pp. 409-414
Citations number
14
Categorie Soggetti
Chemical Engineering
Journal title
COMPUTERS & CHEMICAL ENGINEERING
ISSN journal
00981354 → ACNP
Volume
24
Issue
2-7
Year of publication
2000
Pages
409 - 414
Database
ISI
SICI code
0098-1354(20000715)24:2-7<409:KDFPOD>2.0.ZU;2-N
Abstract
This contribution describes a knowledge discovery system that can be integr ated with a modern computer control environment to continuously and automat ically capture, characterise and assess the skills and behaviour of operati onal personnel. The system is developed and tested based on a joint simulat ion framework of human-process interactions. The operator's performance is modelled using a knowledge-based system, which is a collection of rules rep resenting operator's perception and interpretation of on-line signals as we ll as subsequent planning and sequence of actions. The process behaviour is represented by dynamic simulators. An important component of the knowledge discovery system is a clustered fuzzy digraph that can be used to qualitat ively/quantitatively simulate the temporal behaviour of joint human-process interactions. A case study is also given which demonstrates the feasibilit y of assessing operator's performance through analysis of operational data. (C) 2000 Elsevier Science Ltd. All rights reserved.