STATISTICA Enterprise in the Mining Industry

•Executive Summary
•Leveraging STATISTICA Advanced Data Analysis and Data Mining Technology for Advanced Process Monitoring
•Some Technical and Application Details
•Typical Use Cases
•Multivariate Process Monitoring
•Predictive Data Mining and Process Optimization
•Application/Deployment of Data Mining Solutions
and Brief Demonstration
1.With commodity prices skyrocketing, precious metal mining companies are financially very successful
2.The process of converting ore (e.g., 1 metric ton) into precious metal (e.g., 6 grams of rare/precious minerals or metal) is a very complex process
3.Standard control charting methods is only a small part of the specific analyses and charts that go into successful monitoring of the entire process
4.When yield deteriorates (less precious metal is extracted from the ore), then the cost is enormous
5.There are usually only very few resources (Process Control Engineers) who have the skills necessary to effectively trouble-shoot faulty processes
6.By creating a system for advanced multivariate process monitoring fewer engineers can monitor more processes more effectively
Types of Analyses
•Commonality Analysis: Find common patterns of parameters that are associated with important process outcomes (e.g., find common combination of parameter settings that minimize emissions)
•Multivariate Process Monitoring: Use a data mining model to build multivariate process monitoring applications, to simultaneously track and monitor hundreds or thousands of parameters; detect process shifts and drifts early
•Predictive Data Mining and Process Optimization: Build predictive models of important process outcomes
Key Steps
•First understand domain and processes as best as you can
•Next understand the data, what is and is not “actionable”
•Identify key performance indicators (KPI’s), and identify the important predictors of KPI’s through root-cause analysis
•Track those predictors using multivariate control charting methods

•Main value proposition is: StatSoft has unique expertise, capabilities, and know-how for creating advanced process monitoring solutions for industries where there are no standard solutions, workflows, etc., and where simple univariate analyses will not solve problems

 

Summary:
STATISTICA Focus on: Refining of Precious Metals

1.StatSoft’s implementation experts are able to design and created an efficient dedicated data warehouse, with automated roll-ups and alignment of data from different sources (e.g., Assay, Milling, etc.).
2.Using STATISTICA algorithms for automated root cause analysis, StatSoft’s applied statisticians and consultants can identify effective analytic work flows that will locate problems in a fraction of the time, as compared to traditional trouble-shooting techniques.
3.The enterprise-wide deployment of automated customized analyses, summary reports (on process KPI’s), and effective ad-hoc analytic tools allows process control engineers to monitor more processes (sites) more effectively, and to address problems before they affect the bottom line.

STATISTICA Focus on: Refining of Precious Metals

•Fast root cause analysis
•Biplots, bag plots, for root cause analysis
•Soft-sensing (model-based SPC)

Applying advanced predictive analytics and data mining methods to multivariate process monitoring.

 

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About statsoftsa

StatSoft, Inc. was founded in 1984 and is now one of the largest global providers of analytic software worldwide. StatSoft is also the largest manufacturer of enterprise-wide quality control and improvement software systems in the world, and the only company capable of supporting its QC products worldwide, with wholly owned subsidiaries in all major markets (StatSoft has 23 full-service offices, on all continents), and its software is available in more than 10 languages.

Posted on November 27, 2012, in Uncategorized. Bookmark the permalink. Leave a comment.

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