AI: Reshaping the Future of Resources
April 17th, 2019
Adelaide - Whyalla - Hobart - Launceston - Livestream
When harnessing any resource, improving efficiency and productivity is crucial to profitability. Even small improvements in speed and efficiency can make an extraordinary impact from yielding profits to environmental conservation and human safety.
AI is changing the resource landscape by recognising patterns and harnessing this predictive value to increase agility and responsiveness. This allows companies to be proactive rather than reactive. Additionally, the potential to minimise the human cost by decreasing the event of dust inhalation, noise related harms and chemical risks is an incredible use of technology.
As AI improves both performance and risk management in the resource sector we must question if models that don’t leverage AI will soon become a thing of the past.
Come along to hear how AI is already reshaping our resource sector and a glimpse into the future disruption of the industry.
Professor David Giles
Strand Leader and John Ralston Chair of Minerals and Resources Engineering, Future Industries Institute
David will be presenting on "Mining 4.0" and chairing the Panel Session at AI: Reshaping the Future of Resources on April 17th 2019.
About the Speaker
Prof David Giles is Strand Leader and John Ralston Chair of Minerals and Resources Engineering at the Future Industries Institute, University of South Australia. At the Future Industries Institute we partner with resource sector companies to deliver innovative solutions underpinning productivity and sustainability across the resources industry value chain.
Prof Giles has over 20 years’ experience in minerals exploration spanning the boundaries of industry and academia. Between 2010 and 2018 Prof Giles was Program 3 Leader in the Deep Exploration Technologies CRC and part of a multidisciplinary R&D team responsible for introducing Coiled Tubing drilling with attendant in-field sampling and sensing technology to the mineral exploration industry.
He is Chief Scientific Officer of MinEx CRC where he manages a portfolio of mineral exploration research projects in collaboration with resource companies, METS companies, government organisations and research providers.
Exploration of AI Possibilities
Consilium Technology is discovering opportunities for companies to benefit from AI, and developing AI Tools that improve decision-making. AI brings huge benefits in today’s data-driven world. It’s simply not possible for people to make fast and accurate predictions, or optimal decisions, from the influx of large, complex and multi-dimensional data. AI can provide more accurate predictions, which reduces uncertainty, allowing better decision-making. Rather than fear being replaced by robots (substitutive AI) in the workplace, there’s an opportunity to embrace a human-machine partnership (complementary AI). Some case studies of AI in mining will be discussed, including process optimisation, crew scheduling and predictive maintenance.
About the Speaker
Andrew Harris completed his Bachelor of Science with a first class Honours in Physics at Flinders University in 1995. He spent the first 22 years of his career at Scantech, a company which designs and manufactures high-tech conveyor-mounted elemental and moisture analysers for the global mining industry.
His experience includes data analytics, analyser calibration (predominantly linear regressions using large time-series data sets), on-site commissioning/servicing, product development, technical team management, R&D leadership, IP management, nurturing customers, as well as supporting sales through market strategy, customer meetings and maintaining marketing materials.
In his final role as Operations Manager, he continued to lead R&D, as well as oversee the Technical, Manufacturing, Contracts and Customer Service departments to ensure the company had the best product on the market with customer-focused service to match. He brings all of his experience in providing technical solutions to industry.
Dr Larissa Statsenko
PRIF Consortium and Mining Strategic Research Manager, Institute for Mineral and Energy Resources
Larissa will be presenting "Digital Solutions to Mining Challenges" at AI: Reshaping the Future of Resources on April 17th 2019.
Digital Solutions to Mining Challenges
The mining industry is moving towards the digital transformation. The key to interoperable, agile and efficient operations, is a fully integrated mining value chain that enables rapid and well informed decision making, based on near-real time data streamed from advanced sensors and automated equipment. The Research Consortium led by the University of Adelaide has been established to provide digital solutions for mining value chain integration. Mining Industry 4.0 CRC, another Australia wide collaborative initiative, has recently been established to facilitate digital transformation of the mining industry.
About the Speaker
Dr Larissa Statsenko has a mining engineering and computer science background and fourteen years of experience of applied research in industry and government sponsored projects in Australia and Kazakhstan, focused on mining value chain integration.
She has joined the Institute for Mineral and Energy Resources to manage a Research Consortium of technology providers and a multidisciplinary research team, established to solve mining operator challenges using advanced sensing, data analytics and machine learning.
Predictive Maintenance: Why and How
In today’s world, we have limited resources and the competition is serious. It is a real need for the industry to become smarter and use what already exists such as data, along with the engineering expertise in modelling the systems. What we do at Predict is to try to make the most of this data to perform Predictive Maintenance.
The solution developed includes health assessment, failures predictions, failures root causes diagnosis, throughput improvement and energy optimisation, therefore maximising systems performance, asset availability and reliability. By detecting and analysing subtle drifts from monitored signals, PREDICT solution can identify:
- What is going to break?
- When is it going to happen?
- How, where and why?
About the Speakers
Latha is a Data Scientist at PREDICT Australia where she develops analytic models to perform predictive maintenance for industrial equipment. She has around 6 years of industry experience and, previously worked for a data storage company, developing algorithms and protocols to build operating systems for storage infrastructure.
From 2018, she has been the Treasurer of the Computer Society chapter of IEEE South Australia section.
Amelie is a French Legal Counsel specialised in international and comparative law, who arrived in Adelaide in May 2016.
She joined PREDICT Australia in March 2018 to establish and develop the company in Adelaide, bring Predict's experience in translating the industrial needs into IT solutions and keep pushing the technology further in Adelaide.
She also represents PREDICT and more broadly the experience of French companies opening a subsidiary in South Australia to French & Australian governments, organisations and companies involved in Defence and in particular the FSM program. In this regard, Amelie is an active board member at the French-Australian Chamber of Commerce and Industry SA, an independent not-for-profit organisation governed by 19 Board of Directors and comprising more than 500 members whose main mission is to promote members and help French and Australian companies succeed through information, networking and business support services.
PREDICT Australia is a subsidiary of a large French company specialised in real-time monitoring and Predictive Maintenance since 1999, today working in many various sectors in Europe & Australia: Defence, Nuclear, Manufacturing, Oil&Gas, Energy...
The creation of PREDICT is the result of 3 years of research successfully undertaken by the founder and CEO Jean-Baptiste Leger, regarding remote monitoring of 3 hydroelectric power plants based in Norway, Spain and Portugal. Over time, Predict and its team extended their digital solutions to many other industrial sectors while continuously improving the technology.
Today, our goal at PREDICT is to bring our experience in translating the industrial needs into IT solutions and keep pushing our technologies further for the transition into industry 4.0.
Data Scientist - AICN Steering Committee
Ben Moretti has a background in data analysis, management and governance in the environmental and oil and gas sectors. He is currently working as a data scientist in the renewable energy industry. As a member of the AICN Steering Committee, Ben is building the community of practice for the use of AI and ML in industry in SA.
Ben will be on the Panel for AI: Reshaping the Future of Resources on April 17th 2019.