Casual academic and a PhD student from the Faculty of Engineering and IT working in the areas of Advanced Manufacturing, Additive Manufacturing (3D Printing), Industry 4.0 and Internet of Things (IoT).
Working on a project to apply Advanced Manufacturing to advance the Australian mining industry. Received a scholarship funded by The Commonwealth of Australia’s Department of Industry, Innovation and Science (Innovative Manufacturing CRC Ltd) and Downer, via its subsidiary Mineral Technologies to conduct research in the project “Revolutionising Mineral Separation using Additive Manufacturing”.
- IMCRC: https://www.imcrc.org/2018/06/01/mineral_technologies/
- Engineers Australia: https://portal.engineersaustralia.org.au/news/milestone-mining-manufacture-3d-printing
International and local conferences:
- IEEE International Conference on Cybernetics and Intelligent Systems and the International Conference on Robotics, Automation and Mechatronics (CIS-RAM) (2019, Thailand)
- National Manufacturing Week/IMCRC Conference (2019, Australia): Presented talk regarding the project “Revolutionising Mineral Separation using Additive Manufacturing”. https://www.imcrc.org/conference-highlights/
- International Symposium on Automation and Robotics in Construction (ISARC)(2019, Canada): Session chair of the session: Data Sensing, Computing, and Visualisation.
- International Conference on Computer and Information Science (ICIS)(2018, Singapore)
- International Conference for Convergence in Technology (I2CT)(2018, India)
- Annual Sessions of the Institute of Engineers Sri Lanka (2017, Sri Lanka)
- Runners-up winner in IEEE NSW poster competition for the poster “Advanced Manufacturing of Spirals for Mineral Separation with Integrated Smart Sensing”
- First Place Winners of Sysco Labs Hall of Fame (2017)
- Second Runners up Sysco’s Hack Day (2016)
- ACES Coders v5.0 - 1st Place Winners
Advanced Manufacturing, Additive Manufacturing, Industry 4.0 and Internet of Things (IoT)
Flow rate measurement in pipes is essential for many applications. Thus, there have been a variety of flow meters developed that incorporate different technologies. However, a typical limitation in flow meters is that the pipe must be full in order to get an accurate flow reading. In many cases, this is not possible for practical reasons. When the pipe is full, ultrasonic flow meters can calculate the flow rate using known properties of the pipe and fluid, namely the cross-section, propagation path and fluid sound velocity. However, when the pipe is only partially filled, the propagation path is unknown which leads to an inability to calculate the correct flow rate. This paper presents a cost-effective sensor fusion approach to extend the capabilities of transit time ultrasonic flow meters to handle such scenarios. The approach determines the propagation path using capacitance-based level sensing, combined with fluid velocities ascertained via an ultrasonic sensor, leading to a significantly more accurate estimation of flow rates. Experiments in low flow rate situations validated the efficacy of the proposed model, with a 92% reduction of mean error in the lowest water height when compared to a conventional ultrasonic flow meter.
Munasinghe, N, Woods, M, Miles, L & Paul, G 2019, '3-D Printed Strain Sensor for Structural Health Monitoring', IEEE International Conference on Cybernetics and Intelligent Systems (CIS) and the IEEE International Conference on Robotics, Automation and Mechatronics (RAM), IEEE International Conference on Cybernetics and Intelligent Systems (CIS) and the IEEE International Conference on Robotics, Automation and Mechatronics (RAM), IEEE, Bangkok.
Additive manufacturing, or 3D printing, is evolving from a technology that can only aid rapid prototyping, to one that can be used to directly manufacture large-scale, real-world equipment. Gravity Separation Spirals (GSS) are vital to the mining industry for separating mineral-rich slurry into its different density components. In order to overcome inherent drawbacks of the traditional mould base manufacturing methods, including significant tooling costs, limited customisation and worker exposure to hazardous materials, a 3D printer is under development to directly print spirals. By embedding small Internet of Things (IoT) sensors inside the GSS, it is possible to remotely determine the operation conditions, predict faults, and use collected data to optimise production output. This work presents a 3D printed strain sensor, which can be directly printed into the GSS. This approach uses a carbon-based conductive filament to print a strain gauge on top of a Polylactic Acid (PLA) base material. Printed sensors have been tested using an Instron E10000 testing machine with an optical extensometer to improve accuracy. Testing was conducted by both loading and unloading conditions to understand the effect of hysteresis. Test results show a near-linear relationship between strain and measured resistance, and show a 6.05% increase in resistance after the test, which indicates minor hysteresis. Moreover, the impact of viscoelastic behaviour is identified, where the resistance response lags the strain. Results from both conductive and non-conductive material show the impact of the conductive carbon upon the tensile strength, which will help to inform future decisions about sensor placement.
Munasinghe, MINP, Miles, L & Paul, G 2019, 'Direct-Write Fabrication of Wear Profiling IoT Sensor for 3D Printed Industrial Equipment', Proceedings of the 36th International Symposium on Automation and Robotics in Construction (ISARC 2019), International Symposium on Automation and Robotics in Construction, IAARC, Banff, Canada, pp. 862-869.View/Download from: Publisher's site
Additive Manufacturing (AM), also known as 3D printing, is an emerging technology, not only as a prototyping technology, but also to manufacture complete products. Gravity Separation Spirals (GSS) are used in the mining industry to separate slurry into different density components. Currently, spirals are manufactured using moulded polyurethane on fibreglass substructure, or injection moulding. These methods incur significant tooling cost and lead times making them difficult to customise, and they are labour-intensive and can expose workers to hazardous materials. Thus, a 3D printer is under development that can print spirals directly, enabling mass customisation. Furthermore, sensors can be embedded into spirals to measure the operational conditions for predictive maintenance, and to collect data that can improve future manufacturing processes. The localisation of abrasive wear in the GSS is an essential factor in optimising parameters such as suitable material, print thickness, and infill density and thus extend the lifetime and performance of future manufactured spirals. This paper presents the details of a wear sensor, which can be 3D printed directly into the spiral using conductive material. Experimental results show that the sensor can both measure the amount of wear and identify the location of the wear in both the horizontal and vertical axes. Additionally, it is shown that the accuracy can be adjusted according to the requirements by changing the number and spacing of wear lines.
Munasinghe, MINP 2018, 'Dynamic Hand Gesture Recognition Using Computer Vision and Neural Networks', 2018 3rd International Conference for Convergence in Technology (I2CT), IEEE, pp. 1-5.
Gravity Separation Spirals (GSS) are vital to the mining industry for separating mineral-rich slurry into its different density components. The slurry is pumped to the top and, then the spiral slope naturally helps separate the slurry due to the different particle density. Spiral profile can be slightly varied for every customer, depending on the mineral they separate. The research project is focused on developing a 3D printer to print GSS, which can avoid the drawbacks inherent to the traditional GSS manufacturing process. Another objective of this project is to embed sensors into the 3D-printed GSS for remotely monitor the operational conditions, fault diagnosis, and predictive maintenance. 3D printed sensors are being developed instead of embedding conventional sensors where possible since they are low-cost and can be integrated into the large build volume of the structural material without compromising the mechanical integrity of the object.