Doctor Roland Dodd Academic Learning Services Unit

Awards, Honours and Prestige

• CQUniversity, Faculty Award for Excellence in Learning and Teaching (2010);
• CQUniversity, Directors Award for Excellence in Learning and Teaching (2010);
• Australia Government, Australian Postgraduate Award for Industry (APAI);
• CQUniversity, Faculty of Informatics and Communications Honours Degree Scholarship;
• CQUniversity, Faculty of Informatics and Communications Vacational Research Scholarship;
• Commonwealth Government, Merit Based Equity Scholarship;
• North Rockhampton State High School, Runner Up Dux; and
• The Caves State School, Dux.

Sugar mill process crystal clear thanks to artificial intelligence, 23 June, 2011, http://uninews.cqu.edu.au/UniNews/viewStory.do?story=8383
 
Recognising those who inspire our students, 08 March, 2011, http://uninews.cqu.edu.au/UniNews/viewStory.do?story=7893

Education

• PhD (Information Systems Engineering), RMIT University, July 2009. Doctoral Dissertation: "A Knowledge Based Supervisory Support System for Pan Stage Operations in a Sugar Mill", which was commended as "strongly competitive at international levels".
• Bachelor of Information Technology Honours (First Class), CQ University, November 2007. Honours Dissertation: "Improving the Learning Capacity of Fuzzy Neural Networks", which was commended as "excellent".
• Bachelor of Information Technology (Software Engineering), CQ University, June 2001.

Academic and Research Employment History

• Senior Lecturer, Academic Learning Services, CQ University. January 2013 - present.
• Lecturer, Academic Learning Services, CQ University. January 2010 - December 2012.
• Associate Lecturer, Academic Learning Services, CQ University. February 2009 - December 2009.
• Learning Advisor, Nulloo Yumbah, CQ University. March 2007 - November 2007.
• Learning Advisor, Nulloo Yumbah, CQ University. March 2005 - November 2005.
• Academic Tutor, Faculty of Informatics & Communication, CQ University. March 2003 - October 2005.
• Academic Tutor, Faculty of Engineering, RMIT University. October 2002 - November 2002.
• Course Coordinator, Faculty of Informatics & Communication, CQ University. March 2002 - March 2005.
• Research Assistant, Faculty of Informatics & Communication, CQ University. January 2002.
• Research Assistant, Faculty of Informatics & Communication, CQ University. June 2001 - July 2001.
• Academic Tutor, IC-Assist, Faculty of Informatics & Communication, CQ University. March 2001 - March 2002.

Professional Service

• Editorial Board Member, International Academy, Research and Industry Association (IARIA), International Journal on Advances in Intelligent Systems.
• Editorial Board Member, International Academy, Research and Industry Association (IARIA), International Journal on Advances in Software.
• Member, Technical Program Committee, UBICOMM 2012, The Sixth International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies Technology, 23^rd - 28^th September 2012, Barcelona, Spain.
• Member, Technical Program Committee, UBICOMM 2011, The Fifth International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies Technology, 20^th - 25^th November 2011, Lisbon, Portugal.
• Special Session Organiser, 37th Annual Conference of the IEEE Industrial Electronics Society 7^th - 10^th November 2011, Melbourne, Victoria, Australia.
• Invited Session Chair, 37th Annual Conference of the IEEE Industrial Electronics Society 7^th - 10^th November 2011, Melbourne, Victoria, Australia.
• Member, Technical Program Committee, 37th Annual Conference of the IEEE Industrial Electronics Society 7^th - 10^th November 2011, Melbourne, Victoria, Australia.
• Member, Technical Program Committee, Computation Tools 2011, The Second International Conference on Computational Logics, Algebras, Programming, Tools, and Benchmarking, 25^th - 30^th September 2011, Rome, Italy.
• Member, Technical Program Committee, 23rd Australasian Joint Conference on Artificial Intelligence: AI 2010, 7^th - 10^th December 2010, Adelaide, South Australia, Australia.
• Member, Technical Program Committee, 22nd Australasian Joint Conference on Artificial Intelligence, 1^st - 4^th December 2009, Melbourne, Victoria, Australia.
• Member, Technical Program Committee, 35th Annual Conference of the IEEE Industrial Electronics Society, 3rd - 5th November 2009, Porto, Portugal.
• Member, Technical Program Committee, International Workshop on Intelligent Decision Support Systems and Applications in Networked and Distributed Systems 2009, 19^th - 21^st October 2009, Gold Coast, Queensland, Australia.
• Invited Session Chair, International Workshop on Intelligent Decision Support Systems and Applications in Networked and Distributed Systems 2009, 19th - 21st October 2009, Gold Coast, Queensland, Australia. 

Doctors Roland Dodd and Andrew Chiou of CQU, Professor Xinghuo Yu (RMIT) and Professor Ross Broadfoot (QUT), were granted a Sugar Research and Development Corporation research grant to be undertaken between July 2011 to December 2014. The grant supports implementation of a supervisory control system for pan and fugal stations operations in Australian sugar mills. This system is based on an intelligent industrial decision support platform and industrial process models, developed by Dr Roland Dodd during his PhD research, with the grant focusing on implementation and commercialisation aspects of this technology within the sugar mill environment.

This project aims to demonstrate the viability of the developed framework through improved sugar productivity and quality, reduction of production costs, increasing equipment utilisation and improving the decision making process undertaken by factory staff within the sugar mill crystallisation stage and fugal operational areas. Live factory trials are to demonstrate the merits of the proposed technology with expected benefits conservatively estimated at $10,000,000 per annum when implemented in Australian sugar mills.

Sugar Research and Development Corporation, National Competitive Research Grant

This research project aims to implement a knowledge based supervisory support system (KBSSS) for pan and fugal station operations and to demonstrate and evaluate its effectiveness and acceptability by factory operators, supervisors and management.  The pan and fugal stations are considered to be an ideal location in the factory to initiate progress towards a factory wide supervisory/advisory system. This software development is based upon extension of PhD research prototyping.

The KBSSS will provide advice to supervisors and operators so that early decisions, such as changes to steam rates or allocation of pans to different duties, result in improved outcomes with respect to avoiding production rate difficulties, and maintaining good operational performance with respect to sugar quality, sugar recovery and minimisation and smoothing of steam consumption on the pan stage.

Industry implementation is being undertaken at Macknade sugar mill located in Ingham QLD with the support of Sucrogen industry partner.

PhD (Information Systems Engineering), RMIT University

PhD research led to the development of a prototype knowledge based supervisory support system (KBSSS) for pan stage operations in a sugar mill to demonstrate proof of concept. To demonstrate the viability of the proposed KBSSS framework a prototype system was developed in accordance with the proposed framework. As a result of research and development carried, the KBSSS's test results demonstrated the viability of the proposed KBSSS framework and highlight the forecasting capabilities of the system resulting in favourable outcomes compared to data from pan stage operations. As a result of the research undertaken a prototype KBSSS, for pan stage operations, based upon the three core supporting intelligent system technologies, supporting the overall industrial control system framework, was developed.

Bachelor of Information Technology Honours (First Class), CQ University

Honours degree research led to the development of a fuzzy neural network for intelligent adaptive learning control of an inverted pendulum system. The research focused on examining outcomes for improving the learning capabilities of a fuzzy neural network system. The research proposed a modified adaptive rule importance learning algorithm based upon a fuzzy hierarchical error approach. A modified network structure that is more intuitive, powerful and melds directly into the fuzzy neural network system was developed. This system allows for fast online adaptive control while simultaneously performing system learning with the considerable feature of no offline training required. Furthermore, genetic algorithm optimisation of fuzzy rule neural network rule base and learning parameters was also undertaken.

Dodd, R. and Broadfoot, R., (2012). Milestone Report 5: Implement supervisory/advisory control of pan and fugal stations, Australian Government Sugar Research and Development Corporation, Project Number QUT038. 

Dodd, R. and Broadfoot, R., (2012). Milestone Report 4: Implement supervisory/advisory control of pan and fugal stations, Australian Government Sugar Research and Development Corporation, Project Number QUT038. 

Dodd, R. (2011). Pan Stage Sucrose and Impurity Loadings: Macknade Sugar Mill 2006-2009 Seasons, internal report, CQUniversity.

Dodd, R. and Broadfoot, R., (2011). Milestone Report 3: Implement supervisory/advisory control of pan and fugal stations, Australian Government Sugar Research and Development Corporation, Project Number QUT038.

Dodd, R. and Broadfoot, R., (2010). Milestone Report 2: Implement supervisory/advisory control of pan and fugal stations, Australian Government Sugar Research and Development Corporation, Project Number QUT038.

Industrial Decision Support System Framework  

PhD degree research led to the development of an industrial knowledge based supervisory support system (KBSSS) framework for the control and management of sugar mill crystallisation stage operations for the Australian sugar industry. A summary of this industrial framework is as follows:

The recent downturn in world sugar prices has placed even greater demands upon the Australian sugar industry to reduce the costs of sugar manufacture and increase the consistency of producing high quality sugar. One of the proposed approaches in increasing the consistency of very high quality sugar production and leveraging further avenues for cost saving is in the development of a computer based advisory system. This system is able to provide expert knowledge in the area of pan stage management and best practices in the absence of human experts. This framework focuses upon the design, key features and outcomes in providing cooperative decision support in the area of pan stage operations within a sugar mill.

The KBSSS industrial design utilises three core innovative system technologies that form the core components of the KBSSS framework. These technologies are: 1) Dynamic industrial pan stage process models for identifying the dynamic relationships between sections of pan stage operations to allow for future forecasting of pan stage operating conditions, 2) Integration techniques for the merging of the developed pan stage process models into the hybrid fuzzy logic expert system rule base to provide localisation adjustment to match with local real world factory operational conditions, and 3) Explanatory capabilities to provide justification and support of system advice and recommendations.

R. Dodd, "A Knowledge Based Supervisory Support System for Pan Stage Operations in a Sugar Mill", PhD
dissertation, Royal Melbourne Institute of Technology University, Melbourne, Victoria, Australia, December 2008.

R. Dodd, "Improving the Learning Capacity of Fuzzy Neural Networks", Honours dissertation, Central Queensland University, Rockhampton, Queensland, Australia, November 2007.

I am one of the Chief Investigators in a major Australian Sugar Research Development Corporation (SRDC) national competitive research grant (QUT038), worth $671,002 ($326,116 SRDC funding; $344,886 in-kind support) and titled "Implement supervisory/advisory control of pan and fugal stations" for the July 2011 to December 2014 period. This grant allows commercialisation of the industrial decision support system, that I developed during PhD research, for the control and management of sugar mill crystallisation stage operations for the Australian sugar factory operations.

I am the Chief Investigator in a CQUniversity Seed Grant (RDIS1111), worth $39,608 ($9,963 CQUniversity funding; $29,645 in-kind support), and titled "Scheduling of Batch/Continuous Sugar Mill Crystallisation Stage Operations for Quality, Productivity and Performance Enhancement" for the January 2011 to December 2011 period.

• Artificial intelligence;
• Information systems engineering;
• Industrial decision support systems;
• Industrial process modelling;
• Supervisory control systems in expert environments; and
• Complex systems.

Dodd, R. and Broadfoot, R. (2012). Implement Supervisory/Advisory Control of Pan and Fugal Stations. Macknade sugar mill (24 May 2012). Ingham, Queensland, Australia.