Agenda

TIME	AGENDA
09:00	Welcome Speech & Opening Remarks by Forum Producer
09:10	Case Study – Applying Deep Learning & Immersive Reality In Pipeline/Site Inspection & Maintenance In Sydney Water
	Use of VR & AI to provide immersive site experience Sydney Using Gamification to explore hazards Complete site induction onsite/offsite Digitization of site induction recording Increasing inspection time efficiency
	Dammika Asset Infrastructure Research Lead, Corporate Strategy Sydney Water
09:40	Case Study – AI And Drones, Automating Building Inspections

10:10	*Morning Refreshments & Networking Session*
Leveraging The Power Of AI And Big Data Analytics To Predict Equipment Failure
10:30	How Digital Maintenance Helped BHP To Standardize Tasks And Reduced The Average Truck Downtime For A Regular Service From Two Hours To Just 40 Minutes
	Ali Izadi Maintenance Superintendent A&I BHP
Understanding The Costs And ROI Of Predictive Maintenance Programs
11:15	Predictive Maintenance: Data-Driven Techniques To Improve Prediction Of Pipe Failures For Water Utilities
	Professor Chen will talk about how to create the most accurate prediction method in the world for urban water infrastructure pipe failure prediction. The method has been validated worldwide through datasets coming from more than 30 utilities, including many key utilities in Australia, and others in UK, Netherlands and Hong Kong. Based on new algorithms Prof Chen and the team created, the analysis on more than 10 million assets and more than 1 million failure records cross the global utilities proved more than double of discovery rate on failures than industry standard methods. She will also talk about other data driven predictions in water sector.
	Dr. Fang Chen Executive Director Data Science University of Technology Sydney (UTS)
12:00	*Networking Luncheon*
13:15	Robots For Maintenance: The Use Of Intelligent Robots For Civil Infrastructure Maintenance, Inspection And Painting
	Infrastructure in transport (e.g. bridges and tunnels), energy (e.g. transmission towers, offshore structures) and water (e.g. pipelines and dams) is important to economy and community in every country, but it is progressively deteriorating due to ageing, environmental changes and loading. Lack of or inappropriate maintenance poses very serious risks. Infrastructure robotics research has made significant progress. A number of autonomous and intelligent robots have been developed and deployed for maintaining infrastructures such as the Sydney Harbour Bridge. Examples of such robots include autonomous grit-blasting robot for steel bridge maintenance, bio-inspired climbing robot for confined space inspection and autonomous underwater robot for underwater structure cleaning and condition assessment. This robotic technology can significantly reduce the risks involved in as bridge inspections and improve the overall health and safety of workers.
	Dr Andrew To Research and Development Engineer, Centre for Autonomous Systems (CAS) University of Technology Sydney
13:50	Downer Turns Predictive Maintenance Into A Reality
	The programs predicts the need for maintenance before a failure manifest as a problem that affects service.
	Saad Khan General Manager Capability & Asset Management Downer Defence Systems
14:20	Safer Rail Operations: Reactive To Proactive Maintenance Using State-Of-The-Art Automated In-Service Vehicle-Track Condition Monitoring
	Ravi Ravitharan Director, Institute of Railway Technology (IRT) Monash University
15:00	*Afternoon Refreshment & Networking*
Optimizing MRO With Machine Learning And AI
15:30	Digital Facility Management: Building Performance Optimization
	Dominik Holzer Associate Professor in Digital Architecture, Melbourne School of Design University of Melbourne
16:10	Early Fault Detection Prevents Powerline Faults And Fires
	Dr Alan Wong Founder and CEO IND Technology
17:00	Closing Remarks by Forum Chairperson
	Andrew Sarah Senior Project Manager, Nomad Digital Committee Member Melbourne Chapter, Asset Management Council
17:05	Champagne Networking Session
	After a long day of learning, benchmarking, and planning, unwind and mingle with your peers.

TIME	AGENDA
Using Autonomous Drones For Field Service Inspection & Maintenance
09:00	Welcome Speech & Opening Remarks by Forum Producer

09:15	Drone Data: 3D Reality Models For Virtual Site Visits And Optimising Field Service Inspections
	Andrew Chapman CTO and NSW Operations Manager Australian AUAV
How Predictive Maintenance Can Reduce Maintenance Costs And Increase Asset Lifespan
09:45	How Does Digitalisation Help Maintain Asset Value?
	Greg William Director Engineering & Asset Management Yarra Trams
10:15	*Morning Refreshments & Networking Session*
Root Cause Analysis Of Equipment Breakdowns With Analytics
10:30	Leveraging Big Data Analytics To Determine Root Cause Analysis Of Equipment Breakdowns
	Root cause analysis (RCA) is an essential step in the Predictive Maintenance journey. Thanks to significant advances in machine learning and Big Data analytics, root cause analysis can be performed using automated methods. These methods are unbiased and based purely upon historic and real-time data from the production floor.
	Manohar Esarapu Head of Data and Information City of Port Philip
From Predictive To Prescriptive Maintenance
11:10	Case Study: The Application Of AI In Condition Based Maintenance For Gas Metering And Thermal Application

11:40	Case Study – AI For Utilities Asset Inspection And Network Mapping

12:10	*Networking Luncheon*
Augmented And Virtual Reality For Field Safety Training In Dangerous Environments
13:15	Using AR/VR At Melbourne Water To Train Maintenance Engineers
	Melbourne Water uses VR and augmented-reality (AR) for training. The company sees the new technology as ideal supplements to existing training, particularly in applications where real-world resources either are difficult to access or not always required. Examples include refresher training and laying the foundation for new processes that can then be honed on actual engines. The VR interface gives maintenance engineers a real-world experience at a fraction of the cost.
	Gavin Kenny Manager SHEQ – Service Delivery Melbourne Water
Interactive Roundtable Discussion
13:50	Roundtable Discussions
	Table 1: Maturity assessment to improve the equipment reliability in mine sites
	Dr Ali Soofastaei AI Expert, Artificial Intelligence Center VALE
	Table 2: Designing AR And VR Experiences For Maintenance And Operations Training
	Ben Horan Director, CADET Virtual Reality Laboratory Deakin University
	Table 3: Use Of Drones For Asset Inspection
	James Rennie Co-Director & CEO AUAV
15:15	*Afternoon Refreshment & Networking Session*
15:30	Automation Roadmap Into The Future For Construction
	Nathan Kirchner Head of Robotics\| Ventrures Advisor – Engineering Excellence Group Laing O’Rourke
16:00	The Use Of AI To Reduce Maintenance Costs
	Predictive maintenance analytics using machine learning models can then identify the correlation between the amount of money spent on maintenance. This led to less downtime and millions of dollars saving from maintenance expenses as well as operational disruptions, as well as positive impact on environmental factors by reducing pollution and waste material generation.
	Dr Ali Soofastaei AI Expert, Artificial Intelligence Center VALE
16:30	Closing Remark by Forum Chairperson

TIME	AGENDA
09:00 – 12:00	Site Visit A
	Drones For Field Service Inspection. Assets and infrastructure in hard-to-reach locations, or over large areas, are costly, difficult and often dangerous to inspect regularly. In recent years, robotics have begun to offer a better way to conduct these inspections and ensure early detection of faults and damage that may cause service interruptions or risk. Unmanned aerial vehicles (UAVs) in particular have been demonstrated to halve inspection costs in some cases, while cutting weeks-long inspections to mere days – and even allowing some assets to avoid shutdowns and disruption while under inspection. Get an up-close look at how forward-looking companies maximize the potential of drones for maintenance inspections with 3D modelling for internal and external inspections.
13:00 – 16:00	Site Visit B
	Swinburne University of Technology – Factories of the Future Factory of the future is a new platform for businesses, on a digital transformation journey, to experience and road-test advanced manufacturing technologies and new business strategies in collaboration with Swinburne. It enables businesses to redefine value creation and capture through exploration, strategy and innovation underpinned by Industry 4.0 technologies. Join us on this exclusive site tour to experience first-hand how through a synergy of skills, projects co-created with industries, and empowerment of students and industry 4.0 demonstrators , we are enabling businesses to industry 4.0 technology demonstrators to de-risk innovation. The factory houses a series of co-located studios, each with a specific function: Advanced Inspection and Machining Studio: advanced machining capability combined with state-of-the-art inspection equipment for developing high quality components 3-D Visualisation and Design Studio: featuring advanced visualisation tools that allow for intuitive real-time interaction with realistic 3-D imagery Rapid Manufacturing Studio: equipped with advanced additive manufacturing tools that facilitate conversion from digital concepts to metal, plastic or ceramic prototypes
	Space In Each Site Visit Is Limited, Registrations Will Be Available On First Come, First Reserved Basis.