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Process models for a sugar mill crystallisation stage knowledge based supervisory support system

conference contribution
posted on 2017-12-06, 00:00 authored by Roland DoddRoland Dodd, Ross Broadfoot, Xinghuo YuXinghuo Yu, Andrew ChiouAndrew Chiou
This paper discusses the core process models of a knowledge based supervisory control system designed to provide expert knowledge in the control and management of a sugar mill crystallization stage. Forecasting stock tank levels, within the sugar factory crystallization stage, is beneficial to ensure that there are sufficient quantities of materials in stock to allow completion of production schedules without disruption. Integration of projected vacuum pan feed rates with syrup rate production models and pan phase detection models allows forecasting of stock tank levels for liquor and molasses to forewarn of potential problems with the current operating strategies and advise corrective procedures. These models form an integral part of an overall pan stage knowledge based system to assist in providing a better decision-making strategy for crystallization stage operations.

Funding

Category 1 - Australian Competitive Grants (this includes ARC, NHMRC)

History

Start Page

1

End Page

6

Number of Pages

6

Start Date

2008-01-01

ISBN-10

1904445810

ISBN-13

9781904445814

Location

Online

Publisher

Whittles Publishing

Place of Publication

Caithness, Scotland

Peer Reviewed

  • Yes

Open Access

  • No

External Author Affiliations

Faculty of Business and Informatics; Not affiliated to a Research Institute; Queensland University of Technology; RMIT University;

Era Eligible

  • Yes

Name of Conference

Intelligent Production Machines and Systems Conference

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