Stamp forming of lightweight fibre-metal laminate systems. A key criteria in the development of new vehicles is weight reduction. The aim of this project is to investigate the formability of fibre metal laminates (FMLs) for automotive applications. These hybrid material systems have significant advantages in terms of strength, weight, noise and impact reduction over metals. The major research issue addressed here is how can such materials be formed for volume production.
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE0775499
Funder
Australian Research Council
Funding Amount
$130,000.00
Summary
High Performance Optical Profilometer for mapping micro/meso/macroscopic topography. Developing advanced, high performance new materials requires an understanding of surfaces and interfaces. Making a small area, low yield material or device is a regular occurrence within the Australian research community. The ability to create reproducible, high yield materials requires greater understanding of the stresses, uniformities and deformations in a material over large areas. The proposed instrument ....High Performance Optical Profilometer for mapping micro/meso/macroscopic topography. Developing advanced, high performance new materials requires an understanding of surfaces and interfaces. Making a small area, low yield material or device is a regular occurrence within the Australian research community. The ability to create reproducible, high yield materials requires greater understanding of the stresses, uniformities and deformations in a material over large areas. The proposed instrument can measure topography over many centimeters-squared with sub-micron spatial resolution, currently beyond the capabilities of researchers in Australia. By providing a quantitative method to measure surface textures, the instrument will also support Australian industries looking for improved process control.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE0347079
Funder
Australian Research Council
Funding Amount
$160,000.00
Summary
Surface and strain measurement facilities for the investigation of intelligent CAD approaches. The basis of machine learning approaches is the ability to learn or train a system from data gathered through experiments or experience. A major short coming in the development and application of such methods is the lack of good quantitative data. Here we propose the acquisition of dimensional and strain measurement facilities that will allow the investigation of such methods in the context of manufact ....Surface and strain measurement facilities for the investigation of intelligent CAD approaches. The basis of machine learning approaches is the ability to learn or train a system from data gathered through experiments or experience. A major short coming in the development and application of such methods is the lack of good quantitative data. Here we propose the acquisition of dimensional and strain measurement facilities that will allow the investigation of such methods in the context of manufacturing - in particular sheet metal components for the automotive industry. The facilities will enable a database of dimensional and strain information to be established in support of related manufacturing R&D projects.Read moreRead less
Design surface feature recognition for near net shaped manufactured components. The aim of this project is to investigate methods and techniques that, given an ab initio design requirement, allow databases of knowledge from previous designs to be intelligently searched for similar patterns, both geometric and physical state, that will assess the likelihood of a successful design and suggest potential alternatives based on previous experience
The plan is to approach the research problem from a m ....Design surface feature recognition for near net shaped manufactured components. The aim of this project is to investigate methods and techniques that, given an ab initio design requirement, allow databases of knowledge from previous designs to be intelligently searched for similar patterns, both geometric and physical state, that will assess the likelihood of a successful design and suggest potential alternatives based on previous experience
The plan is to approach the research problem from a machine learning/pattern recognition point of view. By mapping the characterized properties into a search space of reduced dimensionality in which feature patterns have been pre-classified through supervised training, it should be possible to identify similar features.
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Dimensional Control of Stamped Components for Optimized Assembly Operations. Dimensional control is one of the most important challenges in automotive body assembly. The aim of this project is to develop a method of characterizing dimensional variation in a stamped sheet formed parts such that the effect of this variation on assemblies can be analysed. This will lead to an approach to flexible fixturing to minimizing assembly dimensional variation and improve dimensional quality.