A Case Study in Industrial Bioprocess Advisory System Development

Abstract

This paper describes the background and motivation for the construction of a fault detection and advisory system for an industrial fermentation process plant. The need to utilise both algorithmic and rule based fault detection methods is discussed. Following this, the implementation strategy based on the use of G2 from Gensym is outlined. The KAT knowledge elicitation method was used to efficiently capture the fault detection rule set. Examples of the method of elicitation, form of the rules and ease of implementation are given. Finally, the integration with multivariate data-based methods for fault detection and process application of the combined system is described.