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Office of Special Programs and Continuing Education
 
Sampling Theory, Sampling Practices
and Their Economic Impact
 
November 1-4, 2010

 

COURSE OBJECTIVES

Poor sampling, compounded by poor laboratory subsampling, leads to questionable geostatistics, and generates severe conciliation problems between the geological model, the mine, and the plant estimates. These problems also affect the price of commodities and the validity of environmental assessments. The result is a huge money loss for the company involved, evolving later in likely litigation. It is of key importance for geologists, miners, metallurgists, chemists, and environmental specialists to extract maximum information from the available data, as large investments and crucial decisions depend on it. False evaluations lead to devastating scenarios such as:

          • Abandonment of viable properties,
          • Exploitation of unprofitable properties,
          • Mismanagement of viable properties, and
          • Incompetence in fraud detection.

It is critically important to quantify the heterogeneity of important constituents in any new property. Failure to do appropriate testing leads to invalid sampling and subsampling protocols, excess drilling, and a biased database that would later lead to false geostatistics. The following sequence is part of inescapable practice:

          • How is the constituent of interest distributed in the material to be sampled?
          • Conduct Heterogeneity Tests to quantify the sampling characteristics of the constituent of interest.
          • Optimize sampling protocols and the way they are implemented, according to the results from the Heterogeneity Test.
          • Implement protocols using valid sampling equipment: 75% of the sampling equipment available on the market will never do the job.
          • Implement a comprehensive, systematic quality control program to monitor sampling precision and accuracy.

The staggering cost of data irrelevant variability is not easy to detect, quantify, or correct. A strategy for effective management of variability will enable managers to identify and minimize annoying conciliation problems between theoretical models and reality: Your decisions are only as good as your samples!

The course offers simple ways to quantify money losses for a given sampling precision, and it provides a good strategy to prevent catastrophic sampling inaccuracy for which there is no statistical cure. Unless sampling precision and accuracy are clearly connected to economic issues, it is unlikely that any manager would understand the reason for improving sampling protocols and the way they are implemented. At the end of the course, the attendee will be better equipped to present the economic advantages of good sampling to company executives. Therefore, the course is pre-requisite for bank investment: Bankers must listen, and trust the Sampling Theory.

WHAT YOU WILL LEARN

  • You will become familiar with the nine different kinds of sampling errors, how they take place, and how to minimize them; most people can list only two!
  • You will become familiar with sampling correctness, so you can eliminate or reject sampling systems offered to you that will never perform a satisfactory job.
  • You will become familiar with necessary tests to be performed at mines and plants to optimize all your sampling protocols.
  • You will be in a position to select appropriate Data Quality Objectives for operating parameters, which are worth continuous monitoring, to minimize your operating cost.
  • You will better appreciate the value of existing chronological data that allow you to better control any process. This data has great value for management, who should use them to identify structural problems leading to unnecessary financial losses.
  • Variography is the key to identify the various sources of variability affecting routine chronological data. You will discover the power of Chronostatistics.
  • Using existing data, variability from sampling and measurement must be clearly separated from process trends and process cycles. Unless this is well done, continuous process improvement will remain elusive.
  • The careful use of the Moving Average and especially its auxiliary functions can greatly help you to minimize the effect of poor sampling and measurement precision.
  • The Relative Difference Plots can show, in an unambiguous way, the presence of conditional biases from sampling and from laboratories.
  • You will finally realize the weakness of today's standards on sampling: They are obsolete and not in line with the Sampling Theory.
  • You will be updated on the new developments in the world of sampling that were exposed during the first World Conference on Sampling and Blending held in Demark in 2003, and the second WCSB held in Australia in 2005.

WHO SHOULD ATTEND

This course is designed for individuals responsible for optimizing the performance of mines, metallurgical plants, chemical plants, and environmental assessments. The course also applies to many other areas where someone must collect samples to make important decisions. The course is highly recommended for managers to optimize their operations. You should attend this course if you are:

          • Exploration and ore grade control geologists
          • President, Vice Presidents, and operations managers
          • Geostatisticians and laboratory supervisors
          • Miners, metallurgists and chemists
          • Quality Assurance and Quality Control managers
          • Environmental engineers and pollution control specialists
          • Concerned investors and company shareholders

COURSE CONTENT

Introduction

  • Fundamental statistical concepts used in sampling theory and sampling practices
  • Nine kinds of sampling errors: You must address them one at a time, otherwise sampling is almost always invalid.
  • Heterogeneity of major constituents and trace constituents
  • Examples of common financial losses due to poor sampling practices
  • Definition of Data Quality Objectives
  • Presentation of a new quality strategy based on Data Quality Objectives
  • Synergy between Data Quality Objectives and sampling protocols
  • Definition of basic terms and symbols

Sampling Theory and Practice

  • Errors generated by sample weights
    • Optimization of sampling protocols
    • Description of Heterogeneity Tests, for a normal case, and for a difficult case
  • Errors generated by segregation
  • Practical implementation of sampling protocols
    • Complete review of sources of sampling biases
  • Exploration of the in situ Nugget Effect
  • Selection of realistic, economical cutoff grades
  • Detailed review of existing sampling systems:
    • During exploration (Diamond core, RC, …)
    • At mines (blastholes, …)
    • At plants (cross stream systems, in-stream probes, augers, …)
    • At laboratories (splitters, crushers, pulverizers, shovels, spoons, spatulas, …)
    • For sampling commodities at shipping facilities
    • For sampling the environment
  • Monitoring precision and accuracy at the laboratory
  • Monitoring precision and accuracy of sampling and subsampling protocols
  • Quantifying the awesome cost of sampling precision
  • Suggestions for better sampling standards

Reconciliation problems between the geological model, the mine, and the plant

  • The myth of reconciliation
  • Identification of major sources of reconciliation problems
  • Capitalize on existing data: A gold mine of opportunities
  • Understand the different kinds of heterogeneity and the variability they generate
  • Become more proactive through effective statistical thinking

Management must set priorities

  • Find causes of problems and structural properties you must live with
  • Invest in minimizing causes of problems
  • Find effects of problems and circumstantial properties you cannot control
  • Save money by spending much less on effects of problems
  • Managing visible cost:
    • Historical priority placed on visible cost
    • The accountant's point of view
  • Discovering invisible cost:
    • The staggering cost of constituents grade variability
    • Reconciling statistical and accounting points of view

Introduction to Chronostatistics

  • Critical review of sampling modes: random systematic, stratified random, and random
  • Introduction to variography
  • Advanced variography
  • Introduction to variographic statistical process control

The Moving Average, a pragmatic, simple but delicate tool

  • How much averaging is appropriate
  • The random noise
  • The corrected data

The Relative Difference Plot: The best tool for QC monitoring

  • Detection of a conditional bias as a function of time
  • Detection of a conditional bias as a function of increasing constituent content

An improvement strategy for effective sampling


INSTRUCTOR

Mr. Francis F. Pitard has been a consulting expert in Sampling, Statistical Process Control, and Total Quality Management for twenty-one years. He is President of Francis Pitard Sampling Consultants, and Technical Director of Mineral Stats Inc. in Broomfield, Colorado. He provides consulting services in many countries. Mr. Pitard has six years of experience with the French Atomic Energy Commission and fifteen years with Amax Extractive R&D. He taught Sampling Theory, SPC, and TQM for the Continuing Education Offices of the Colorado School of Mines, for the Australian Mineral Foundation, and for the Mining Department of the University de Chile. He has degrees in chemistry from the Gay-Lussac Institute in Paris and from the Academy of Paris. His clients include at least 150 companies around the world.

 

 

FEES AND REGISTRATION

The registration fee is $1,750 US. (10% discount for Colorado School of Mines students.) The fee includes coffee breaks and course notes. Attendees who enroll prior to October 1 will receive a free copy of Mr. Pitard's CRC Press textbook: Pierre Gy's Sampling Theory and Sampling Practice. The sponsor reserves the right to cancel the course and return registration fees if enrollment is insufficient. Cancellations will be charged a $150 service fee if made more than 10 working days prior to the start of the course; otherwise a $300 penalty will be applied. Substitutions may be made at any time without penalty. No refunds will be made to registrants who fail to substitute or cancel prior to the start of the course. CSM will award 2.6 Continuing Education Units (CEUs) for participation in the course. Registrants are responsible for making their own lodging and travel arrangements. A list of suggested accommodations will be sent to registrants upon receipt of enrollment application.

Register

LOCATION

This course will be held on the campus of the Colorado School of Mines in Golden, Colorado between 8:00 am and 5:00 pm on the specified days.

FURTHER INFORMATION

For further technical information concerning the program, contact Mr. Francis Pitard at (303) 451-7893, or e-mail at fpsc@aol.com. Website is located at: www.fpscsampling.com.

For registration information, contact the Office of Special Programs and Continuing Education (SPACE), Colorado School of Mines, at (303) 273-3321; fax (303) 273-3314, e-mail space@mines.edu.

Registrants are responsible for making their own lodging and travel arrangements. For travel information, click here - for accommodations, click here.


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