Edge computing is helping Newcrest Mining improve throughput and reduce downtime in Australia's largest underground block cave mine, the Cadia Valley gold mine in New South Wales. Newcrest Mining won the best Primary Industry Project in our 2019 IoT Awards for the project, which uses machine learning to optimise the level of crushed ore in bins, preventing downtime. Now Microsoft and its partner Insight Enterprises have released details about the solution and its benefits. The solution is improving productivity, reducing downtime and increasing throughput, Newcrest Mining CIO Gavin Wood stated in a press release. And the company has seen a return on investment within three months of starting to use the solution.
Opportunities for digital technologies implementation, including implementation of artificial intelligence, are being implemented in the mining sector. Technologies help to save money and to solve problems that humans can't solve. McKinseyestimates that by 2035, the use of data analysis and digital technologies will help coal, iron ore, and copper producers save between $290 billion and $390 billion annually. Digital technologies and artificial intelligence enable companies to extract minerals in hard-to-reach places and under extreme weather conditions. This article first appeared in Mining Review Africa Issue 10, 2019 Read the full digimag here or subscribe to receive a print copy here This means that in an environment when mineral resources are becoming increasingly scarce, it is possible to develop deposits that used to be inaccessible, to do it without endangering lives of employees and to minimize human errors that often lead to costly mistakes.
Here is an unavoidable truth. Resource extraction is hard physical work. And perhaps this is the very reason modern investors have wandered away from mining--whether or not it's to their benefit. New AI methods may change that. Just like society, many investors today are overlooking the connection between the products we use and the source of the materials to make them.
Newcrest Mining has deployed Microsoft cloud, AI and IoT technologies at Australia's largest underground, block cave mine to monitor and manage crushed ore bin levels. The soft sensor delivered a return in investment within the first three months of operation. The technology, developed by Newcrest in association with Microsoft and its partner Insight Enterprises, has been rolled out at Newcrest's Cadia Valley gold mine in NSW. The challenge facing Newcrest at Cadia was managing the levels in the underground crushed ore bins. If the bins overfill, they have to be manually emptied introducing lengthy and expensive production delays.
The field of process mining started in the late 1990s when Wil van der Aalst, who is now a professor leading the Process and Data Science group at RWTH Aachen University, began looking for ways to combine process science and data science. Much of this early work was theoretical, but the field has started accelerating over the last couple of year with advancements in data gathering and analytics technologies. "The adoption of process mining has accelerated over the last couple of years," van der Aalst said in an interview. There are now over 30 vendors of commercial process mining tools, including leaders like Celonis, Disco, UiPath (ProcessGold), myInvenio, Minit, Mehrwerk, Lana Labs, StereoLOGIC and Everflow. This has made it easier for large organizations, like Siemens and BMW, to apply process mining at scale with thousands of process mining users.
Mercury Systems, Inc. today unveiled the EnterpriseSeries RES AI rugged rackmount server line, bringing High Performance Computing (HPC) capabilities to aerospace, defense and other mission-critical applications at the edge. "The proliferation of sensors, ever-growing data loads and the evolution of complex deep learning neural networks continues to increase computational demands, driving the need for supercomputing infrastructure closer to the edge," said Scott Orton, Vice President and General Manager of Mercury's Trusted Mission Solutions group. "Through close collaboration with technology leaders such as NVIDIA and Intel, we've developed reliable parallel computing systems that accelerate demanding artificial intelligence (AI), signal intelligence (SIGINT), and sensor fusion applications where it's needed the most." Why it Matters: Evolving compute-intensive AI, virtualization, big data analytics, SIGINT, autonomous vehicle, Electronic Warfare (EW) and sensor fusion applications require data center supercomputing capabilities closer to the source of data origin. Delivering HPC capabilities to the edge presents challenges as every application has its own security, performance, footprint, budget and reliability requirements.
What's your plan for steel?" is a question Bill Gates always uses whenever someone pitches him an idea of how to stop global warming . Agriculture and the industry are responsible for almost half of the gas emissions worldwide and the steel industry is a major contributor. We encounter steel everywhere in life. I guess most of you are reading this article sitting on a steel chair – and for a good reason. The adaptability and durability of steel are unique and it is used to construct cars, buildings, gas pipelines, electrical transmission towers, and tools that we use on a daily basis.
Editor's Note: Get caught up in minutes with our speedy summary of today's must-read news stories and expert opinions that moved the precious metals and financial markets. The Australian government is setting up two mining research centres in partnership with universities and commercial supporters, according to an announcement made on Tuesday. The centers will be based in Sydney and Adelaide. The Australian government said research activity at the University of Sydney "...will focus on data analytics related to the long-term impact of resource use on Australia's economy, society and environment. It will help develop the necessary data science skills for Australia's resource industries to make the best possible evidence-based decisions when using our natural resources."
A lot of nat gas analysts would at times reference EIA's Nuclear Capacity Outage (NCO henceforth), yet I haven't seen anyone do a detailed explanation of how they apply it toward an objective bias in implied Nat Gas demand, i.e. Fair Value bias going forward expected by traders paying attention to NCO. So I got curious, and first look at NG prices vs. YOY change in NCOs: So it looks like there is likely somewhat of a rough relationship, that some traders are paying attention to it. Then the next step would be an attempt toward precision via Time Series Analysis. So, what I'd do here is a 2 Step Machine Learning process of 1) Forecast expected NCO for the rest of 2019, then apply that to estimate Natural Gas futures fair value bias going forward.
We're about to enter the "exascale era" of computing, which could have widespread positive impacts for governments, businesses and society at large. The U.S. Department of Energy recently announced contracts for supercomputers that will each provide more than an exaflop of performance. That means they can perform 1 quintillion mathematical calculations (called floating-point operations, or flops) every second. The work done on these systems will impact all our lives. And the technologies developed for them will enhance computing systems at all scales, transforming the future of the enterprise.