Roland Dodd

A Smart Supervisory Control System framework for a sugar mill crystallisation stage

This paper discusses the framework of an expert advisory system designed to provide expert knowledge in the control and management of a sugar mill crystallization stage. The Smart Supervisory Control System (SSCS) is fundamentally a hybrid fuzzy logic based expert system that incorporates fuzzy logic, explanatory capabilities and dynamic interrelational process models of the crystallisation stage. The primary topic of this paper will be a description of the framework of the SSCS system with focus on: (1) modular design, (2) system layering, and (3) system features.

Pan stage steady state flow model for integration within a knowledge based supervisory support system

This paper covers the development of a core industrial process model of an expert advisory system and its integration within a knowledge based supervisory support system (KBSSS) for the control and management of a sugar mill crystallization stage. The pan stage steady state flow model predicts the long term steady state flow rates and purities of process materials within the pan stage. The primary topic of this paper will be a description of the steady state flow model for the knowledge based supervisory support system. This paper will focus on: (1) design features, (2) implementation, and (3) results of the proposed model.

A novel decision support framework for industrial processes

In this paper, a novel industrial decision support framework is discussed. This framework takes consideration of special features of industrial processes and makes use of intelligent and complex systems technologies to facilitate quality decision-making in industrial setting. The structure of the framework is described in details with some case studies used to illustrate its use.

Dynamic allocation of predicted quantities to forecast intervals for pan stage supervisory support system process models

This paper describes a critical feature for the industrial process models of an expert advisory system and their integration within a knowledge based supervisory support system (KBSSS) for advice on best practices and management of a sugar mill crystallization stage. This functionality works cooperatively to translate pan stage industrial process models, used during the forward prediction of pan stage operating conditions, to a time scale basis by dynamically allocating forecast processing quantities to predefined intervals over the prediction horizon. The innovative dynamic allocation procedure outlined underpins the prediction ability of the process models, acting in a backbone capacity, to establish forecasting capabilities for the system. The primary topic of this paper will be a description of the approach and how it supports the predictive modelling with focus on: (1) design features, (2) implementation and (3) application to the prediction of syrup quantities to the pan stage from cane receival and juice processing information.

Industrial Process Model Integration Using a Blackboard Model within a Pan Stage Decision Support System

This paper describes the critical features for information sharing and exchange between industrial pan stage process models within a knowledge based supervisory support system (KBSSS), for pan stage operations in a sugar mill. The innovation outlined underpins the integration of the industrial process models working cooperatively with a blackboard system to provide system forecasting of future pan stage operating conditions. The primary topic of this paper will be a description of the approach and how it supports information exchange during the forecast process undertaken by the pan stage industrial process models with a focus on: (1) design features, (2) implementation and (3) application to the prediction process.

Functional Characteristics and Proposed Deployment Infrastructure of an Industrial Decision Support System within a Sugar Mill Crystallisation Stage

This paper describes a deployment proposal and functional characteristics of a knowledge based supervisory support system (KBSSS) to provide expert knowledge in the control and management of the pan stage within a sugar mill. This decision support system utilises fragmented and diverse sources of information and unifies these into a cohesive structure to solve an important industrial control problem. Given the functional system characteristics, a deployment proposal for the embedding of the KBSSS within existing sugar mill infrastructure is presented. The primary topic of this paper will be a description of: (1) the deployment proposal, (2) system process flows and (3) operational levels of the KBSSS.