Asset Intelligence: Maximising Operational Effectiveness for Digital Era . The primary aim of this project is to develop an innovative lifecycle semantic–based decision making approach through asset intelligence so as to maximize the operational effectiveness maintenance, repair and rehabilitation planning of infrastructure assets, such as concrete pavement. The research intends to address an important gap by providing logical formalisms and real-time capability to life-cycle asset information t ....Asset Intelligence: Maximising Operational Effectiveness for Digital Era . The primary aim of this project is to develop an innovative lifecycle semantic–based decision making approach through asset intelligence so as to maximize the operational effectiveness maintenance, repair and rehabilitation planning of infrastructure assets, such as concrete pavement. The research intends to address an important gap by providing logical formalisms and real-time capability to life-cycle asset information through computational intelligence. The expected outcome will be an intelligent asset management platform that provides structured and semantically enriched lifecycle asset information for optimised solutions to help reduce the cost, time and effort in asset information storage and retrieval, and decision-making. Read moreRead less
Artificial intelligent system for integrated wear debris analysis and vibration analysis in machine condition monitoring. Vibration and wear debris analyses are the two main condition monitoring techniques for machinery maintenance and fault diagnosis. However, they can diagnose less than 50% of faults. A series of experimental and theoretical studies on the correlation of the two techniques will be conducted. This project will integrate advanced technologies including 3D microscopy, neural netw ....Artificial intelligent system for integrated wear debris analysis and vibration analysis in machine condition monitoring. Vibration and wear debris analyses are the two main condition monitoring techniques for machinery maintenance and fault diagnosis. However, they can diagnose less than 50% of faults. A series of experimental and theoretical studies on the correlation of the two techniques will be conducted. This project will integrate advanced technologies including 3D microscopy, neural networks and expert systems to develop an artificial intelligent system based on the dependent and independent roles of the two condition monitoring techniques. Successful outcomes will result in an improved maintenance program and reduction in human involvement, and will provide significant economic benefit to engineering industries.Read moreRead less
A generic decision-making design environment to enable end users in rural industries to develop expert systems. Successful decision support systems developed by end-users has been limited: our proposed approach advances this capability. Using natural representations of industry knowledge, this project will specify a generic design environment in which industry end-users can develop relevant decision support systems. It extends expert systems technologies to overcome known limitations, increasin ....A generic decision-making design environment to enable end users in rural industries to develop expert systems. Successful decision support systems developed by end-users has been limited: our proposed approach advances this capability. Using natural representations of industry knowledge, this project will specify a generic design environment in which industry end-users can develop relevant decision support systems. It extends expert systems technologies to overcome known limitations, increasing context and relevance and encouraging user uptake. Key industry stakeholders will select relevant problems to identify decision categories, leading to specification of the generic design environment. This promises improved decision quality for dairy farmers in the recently deregulated dairy industry; the design environment will be transferable to other rural industries.Read moreRead less