Engineering & Mining Journal

JAN 2019

Engineering and Mining Journal - Whether the market is copper, gold, nickel, iron ore, lead/zinc, PGM, diamonds or other commodities, E&MJ takes the lead in projecting trends, following development and reporting on the most efficient operating pr

Issue link: https://emj.epubxp.com/i/1070726

Contents of this Issue

Navigation

Page 28 of 59

PLANT ENGINEERING JANUARY 2019 • E&MJ 27 www.e-mj.com Emerging Technologies New technologies could boost the pro- ductivity of Newmont's comminution cir- cuits even further and Giblett points to a number of emerging technologies that look promising. "These include ore sorting and pre- concentration technologies to reduce the amount of material that goes through fine crushing and grinding. We need to develop desktop characterization pro- cedures that define ore amenability to these processes early in the project life, without the need to collect and process large ore samples at pilot scale. Once we can do that we might expect to see a larger shift in how the industry oper- ates," he said. "Separating at coarser crush or grind sizes, and with improved liberation, will be a key to the future success of low- grade, high-tonnage operations. Reduc- ing our energy footprint is high on the agenda at Newmont." Sandy Worden is the Events and Commu- nication Coordinator for the Coalition for Energy Efficient Comminution (CEEC). Alison Keogh is the CEO for CEEC. www.ceecthefuture.org Fluor Uses Watson for Predictive Analytics on Megaprojects Last year, Fluor Corp. and IBM began using artificial intelligence (AI)-based systems to predict, monitor and measure the status of engineering, procurement, fabrication and construction (EPC) megaprojects from inception to completion. Fluor's extensive engineering, fabrication, construction and deep supply chain expertise, coupled with AI and analytic technologies from IBM's Watson, forms the foundation for big data analytics and diagnostic systems that help predict critical project outcomes and provide early insights into the health of projects. Large capital projects, especially in mining and metals mar- kets, are incredibly complex with enormous amounts of data, people and moving parts that are constantly changing and need to be understood to keep a project on schedule and budget. To gain insights from project data in nearly real-time and to under- stand the implications of changing factors, Fluor is introducing the EPC Project Health Diagnostics (EPHD) and the Market Dy- namics/Spend Analytics (MD/SA) systems. Developed with IBM Research and IBM Services, working collaboratively with Fluor, these innovative tools help to identify dependencies and provide actionable insights by fusing thousands of data points across the entire life cycle of capital projects. Fluor selected IBM to assist in the development of these ad- vanced systems as part of its global data-centric transformation strategy. These engineers can now leverage a wealth of experi- ence from across its entire historical data store and global work- force to quickly understand markets and monitor project factors impacting cost and schedule to drive improved certainty and cost efficiency across the entire project scope. "Harnessing the power of data to make meaningful insights will alter how megaprojects around the world are designed, built and maintained," said Arvind Krishna, senior vice president and director of IBM Research. "Together with IBM, Fluor is embrac- ing artificial intelligence as an engine for transformation in da- ta-driven industries that are ripe for innovation including energy and chemicals, and mining and metals construction projects." "The ability to rapidly analyze and comprehend big data that drives decisions at any point throughout the engineering, pro- curement, fabrication and construction of today's megaprojects is an imperative for the success of our company and the pro- tection of our clients' capital investments," said Ray Barnard, Fluor's senior executive vice president of Systems and Supply Chain. "And to be the best at predictive analytics and project execution in our industry, we teamed with IBM to create EPHD and MD/SA, an ad- vanced and effective set of diagnostic tools and capabilities that rapidly predict best-in-class pricing globally, project sta- tus and outcomes, and improves the qual- ity of services and decision-making as we serve our clients around the globe." The EPHD and MD/SA systems are de- signed to transform complex data into actionable business insights using do- main-driven semantic models to guide artificial intelligence-based predictive and diagnostics modeling. A unique feature of the systems is the blending of data with domain expertise to learn models that are operationally insightful. An advanced cognitive user interface provides seamless access to the data, reports and results of the analysis, using EPC domain-sensitive natural lan- guage conversational interface. The underlying domain under- standing is used to guide project diagnostics and provide natural language summaries based on the reports, with data visualization techniques to ease its quick consumption and understanding. These tools assess the status of a project by: • Predicting issues such as rising costs or schedule delays based on historical trends and patterns. • Gaining earlier insights from many sets of complex factors across project execution. • Identifying the root causes of issues and the potential impacts of changes as input to the decision-making process including estimate analysis, forecast evaluation, project risk assessment and critical path analysis. "Besides the work Fluor was already doing on predictive maintenance and construction sequencing, five years ago we began investing in predictive analytics and artificial intelligence capabilities to further evaluate performance and determine criti- cal project outcomes as a part of our data-centric journey," said Leslie Lindgren, Fluor's vice president of Information Manage- ment. "We will be using these innovations on select large and megaprojects to quickly discover trends, patterns and meaning in our structured and unstructured data that deliver competitive advantage through the digital transformation of data into critical information with significant benefits to our clients, other stake- holders and our company." As Fluor continues on its global data-centric transformation journey, the company plans to further develop and expand EPHD and MD/SA using analytics and artificial intelligence capabilities from IBM Watson and integrate them into Fluor's processes.

Articles in this issue

Links on this page

Archives of this issue

view archives of Engineering & Mining Journal - JAN 2019