Advanced Predictive Analytics
Business Challenges n the current [mining] economic climate, minimizing costs is critical. Equipment reliability must be stepped up to increase production and reduce delays. Equipment reliability requires effective maintenance. Maintenance expenses in the mining industries are commonly between 30%-50%of mine site total operating costs. Suggested Solution The overall goal is the application of Advanced Analytics […]
Business Challenges Diesel fuel is a significant source of energy in surface mining operations. Haul trucks are the primary users of this energy resource. Based on the analysis of the data collected from mine sites, Gross Vehicle Weight (GVW), Truck Speed (S), and Total Resistance (TR) were identified to be the most influential parameters affecting […]
Business Challenges Data collected from payload management systems at some surface mining operations show significant variance. Heavily loaded trucks travel slower up ramps than lightly loaded trucks. Faster trucks are slowed by the presence of slower trucks, resulting in “Bunching” and production losses Suggested Solution This project has been completed to develop an algorithm and […]
Business Challenges Since the onset of the slump in commodity prices in mid-2012, the mining industry has sought to significantly enhance productivity and lower labor and cost inputs. Most companies have progressed through two to three waves of cost-cutting exercises, with the result that much of the low-hanging fruit has been plucked, and further cost […]
Business Challenges Mineral exploration activities require robust predictive models that accurately map the possibility that mineral deposits can be found at as pecific location. Suggested Solution Random forest (RF) is a powerful machine data-driven predictive technique unknown in potential mineral mapping. This project explores the performance of RF regression for the nickel deposits in the […]
Business Challenges Metal price predictions support evaluations of future profits from metal exploration and mining and inform purchasing, selling, and other day-to-day activities in the metals industry. Past research has shown that repeated behaviour is a dominant characteristic of metal prices. Wavelet analysis allows capturing this cyclicality by decomposing a time series into its frequency […]
Business Challenges Streaming Data Analysis (SDA) of Big Data Streams (BDS) for Condition Based Maintenance (CBM) in the context of Rail Transportation Systems(RTS) in the mining industry is a state-of-the-art field of research. SDA of BDS is the problem of analysing ,modelling, and extracting information from vast amounts of data that continuously come from several […]
Business Challenges The number of vessels to transfer mine materials is limited. There are few big competitors and predict of available vessels for chartering is important for big mining companies. Using machine learning is an innovative method to predict the vessel availabilities in different regions Suggested Solution Gathering data from different internal and external resources […]
Business Challenges The rate of mine material shipping (TC rate) is a dynamic parameter. This parameter plays a critical role to estimate the fin al material cost. There is an opportunity to build an integrated architecture and analytical platform that can provide business use rs with optimal decision capabilities based on a holistic overview of […]
Business Challenges The Vale marketing intelligence team provides insights on a wide range business area for important decision making. These insights rederived combining several individuals excel based models coming from different team members (each responsible for a particular sub-topic).As the complexity of analysis/ forecast is increasing, team is finding it difficult to maintain and consolidate […]