Process Chemistry for Distributed Manufacture of Nitric Acid. This project will benefit Australia by enabling a new approach to the manufacture of explosives for the country's mining industry which will provide the entire explosives supply chain with greater safety and security. Development of this technology will enhance Orica's competitive position as the largest manufacturer of mining explosives in the world and will produce wealth for the country through the continued success of this ASX Top ....Process Chemistry for Distributed Manufacture of Nitric Acid. This project will benefit Australia by enabling a new approach to the manufacture of explosives for the country's mining industry which will provide the entire explosives supply chain with greater safety and security. Development of this technology will enhance Orica's competitive position as the largest manufacturer of mining explosives in the world and will produce wealth for the country through the continued success of this ASX Top 50 company and the export of the technology.Read moreRead less
Distributed nonlinear control based on differential dissipativity. This project aims to investigate the process control methodologies crucial to smart manufacturing It aims to develop a distributed optimisation-based nonlinear control approach for plant-wide flexible manufacturing, which can achieve time-varying operational targets including production rates and product specifications to meet dynamic market demands. This includes a contraction-based nonlinear distributed control framework that e ....Distributed nonlinear control based on differential dissipativity. This project aims to investigate the process control methodologies crucial to smart manufacturing It aims to develop a distributed optimisation-based nonlinear control approach for plant-wide flexible manufacturing, which can achieve time-varying operational targets including production rates and product specifications to meet dynamic market demands. This includes a contraction-based nonlinear distributed control framework that ensures plant-wide stability at any feasible set-points or references and a distributed economic model predictive control approach that coordinates autonomous controllers to achieve plant-wide economic objectives in a self-organising manner. The outcomes of this project are expected to form a process control framework for next-generation smart plants.Read moreRead less
Dynamic Controllability Analysis for Plantwide Process Design and Control. World-wide chemical plants represent many billions of dollars of investment. Improvements to the process designs in terms of controllability would have the potential to provide large economic benefits, as it implies improved productivity, reduced operating costs and product variability. This proposed research will be a step towards integration of process design and control, which has been widely recognized as the key to t ....Dynamic Controllability Analysis for Plantwide Process Design and Control. World-wide chemical plants represent many billions of dollars of investment. Improvements to the process designs in terms of controllability would have the potential to provide large economic benefits, as it implies improved productivity, reduced operating costs and product variability. This proposed research will be a step towards integration of process design and control, which has been widely recognized as the key to this improvement. The outcomes from this project may be readily implemented in process design practice, and therefore have a direct impact to the Australian and world-wide process industries, helping to build a more efficient and environmental conscious Australian process industries.Read moreRead less
Dissipativity based distributed model predictive control for complex industrial processes. This project will extend and improve the model predictive control technology, which is the most widely used advanced control approach in process industries. The results will potentially benefit the Australian mineral processing industry where many processes are geographically distributed, leading to more cost-effective operation.
Integrated Approach to Plantwide Fault Diagnosis and Fault-tolerant Control. This project aims to develop a new approach to detect and reduce the impact of faults in industrial plants. Operations of modern industrial processes increasingly depend on automatic control systems, which can make the plants susceptible to faults such as sensor/actuator failures. Based on the concept of dissipative systems, the project aims to develop a novel integrated approach to distributed fault diagnosis and fault ....Integrated Approach to Plantwide Fault Diagnosis and Fault-tolerant Control. This project aims to develop a new approach to detect and reduce the impact of faults in industrial plants. Operations of modern industrial processes increasingly depend on automatic control systems, which can make the plants susceptible to faults such as sensor/actuator failures. Based on the concept of dissipative systems, the project aims to develop a novel integrated approach to distributed fault diagnosis and fault-tolerant control for plant-wide processes. It aims to capture the key dynamic features of normal and abnormal processes by their dissipativity properties, and to use these to develop an efficient online fault diagnosis approach based on process input and output trajectories.Read moreRead less
A System Behavioral Approach to Big Data-driven Nonlinear Process Control. This project aims to develop a novel process control approach that utilises big process data to improve the cost-effectiveness of industrial processes. Existing monitoring systems in the industry have been collecting a tremendous amount of process operation data but little effort has been made to use the big process data to enhance process operations. Based on the system behavioural approach and dissipativity theory, inte ....A System Behavioral Approach to Big Data-driven Nonlinear Process Control. This project aims to develop a novel process control approach that utilises big process data to improve the cost-effectiveness of industrial processes. Existing monitoring systems in the industry have been collecting a tremendous amount of process operation data but little effort has been made to use the big process data to enhance process operations. Based on the system behavioural approach and dissipativity theory, integrated with machine learning techniques, this project expects to develop a novel framework for data-driven control using big process data. The outcomes are expected to benefit the Australian process industry, where many processes are controlled by inadequate logic controllers, by improving their operational efficiency.Read moreRead less
A fundamental study of milk ultrafiltration. The Dairy Industry is one of Australia's largest domestic and export industries. The fundamental knowledge and models developed in this project will be used to optimise dairy membrane processing. This will reduce water and energy use to improve the global competitiveness and reduce the environmental impact of the Australian Dairy Industry.
Data-based Control of Process Feature Dynamics through Latent Behaviours. This project aims to develop a novel data-based approach to control the feature dynamics of complex industrial processes. The dynamic features of desired process operations (leading to high energy and material efficiencies and good product quality) are often not directly measured but can be distilled from high-dimensional big process data. However, little effort has been made to develop process control approaches to achiev ....Data-based Control of Process Feature Dynamics through Latent Behaviours. This project aims to develop a novel data-based approach to control the feature dynamics of complex industrial processes. The dynamic features of desired process operations (leading to high energy and material efficiencies and good product quality) are often not directly measured but can be distilled from high-dimensional big process data. However, little effort has been made to develop process control approaches to achieve desired dynamic features. This project aims to develop such a data-based approach by controlling latent variable dynamics, using the behavioural systems framework integrated with big data analytics and artificial neural networks. The outcomes are expected to help build a cornerstone for future smart manufacturing.Read moreRead less
A coupled finite volume method for viscoelastic flow problems on highly-skewed unstructured meshes: a computational rheology revolution. Commercial tools are unavailable for 21st century industry to analyse complex flow processes involving viscoelastic materials. Using fabrication of microstructured polymer optical fibre as a key case study, a coupled finite volume methodology holds the key for the next generation of computational rheology simulators.
Economic Operability Assessment of Leaching Process at Kwinana Nickel Refinery. Process operability is concerned with systematic analysis and improvement of process performance in the face of variable operating conditions. This project will develop a rigorous methodology for analysis of process operability with respect to short-term and transient disturbances. The proposed technique will be applied to the Kwinana Nickel Refinery Leach section, in order to reduce the plant variability and increas ....Economic Operability Assessment of Leaching Process at Kwinana Nickel Refinery. Process operability is concerned with systematic analysis and improvement of process performance in the face of variable operating conditions. This project will develop a rigorous methodology for analysis of process operability with respect to short-term and transient disturbances. The proposed technique will be applied to the Kwinana Nickel Refinery Leach section, in order to reduce the plant variability and increase nickel throughput and plant availability. This can be considered as significant move by a process industry to embrace advanced theoretical developments and will act as a benchmark to promote future links between Australian industry and academia.Read moreRead less