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From process experts to a real‐time knowledge‐based system
Author(s) -
Ranjan Anubhav,
Glassey Jarka,
Montague Gary,
Mohan Pankaj
Publication year - 2002
Publication title -
expert systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.365
H-Index - 38
eISSN - 1468-0394
pISSN - 0266-4720
DOI - 10.1111/1468-0394.00192
Subject(s) - bottleneck , computer science , process (computing) , knowledge base , knowledge management , process management , data science , artificial intelligence , engineering , embedded system , operating system
This paper describes the development and implementation of a real‐time knowledge‐based system (RTKBS) carried out in collaboration with Eli Lilly in the UK. The RTKBS was developed in order to provide consistent advice to the operators of a large‐scale antibiotic production plant in real time. The ultimate objective was to reduce variability and improve the process yield. A wealth of process information exists in the experience of the process operators, engineers and scientists, and it was capitalized upon in this application. However, this information tends primarily to be qualitative in nature and its elicitation traditionally represents a bottleneck in developing an RTKBS. The paper demonstrates that this type of process knowledge can be effectively and rapidly captured and then coded within an RTKBS. The project was undertaken in two stages. During the knowledge elicitation stage the specific application area was identified in consultation with the industrial partner and qualitative knowledge in the selected area was extracted from experts/operators using KAT™ (a structured technique for knowledge elicitation). Subsequently this knowledge was converted into a rule base and implemented within G2, which then acted as an advisory/decision support system.