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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:
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Abandonment
of viable properties,
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Exploitation
of unprofitable properties,
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Mismanagement
of viable properties, and
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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:
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How
is the constituent of interest distributed in the material
to be sampled?
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Conduct
Heterogeneity Tests to quantify the sampling characteristics
of the constituent of interest.
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Optimize
sampling protocols and the way they are implemented, according
to the results from the Heterogeneity Test.
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Implement
protocols using valid sampling equipment: 75% of the sampling
equipment available on the market will never do the job.
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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.
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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!
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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.
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You
will become familiar with necessary tests to be performed at mines
and plants to optimize all your sampling protocols.
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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.
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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.
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Variography
is the key to identify the various sources of variability affecting
routine chronological data. You will discover the power of Chronostatistics.
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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.
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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.
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The
Relative Difference Plots can show, in an unambiguous way, the presence
of conditional biases from sampling and from laboratories.
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You
will finally realize the weakness of today's standards on sampling:
They are obsolete and not in line with the Sampling Theory.
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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:
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Exploration
and ore grade control geologists
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President,
Vice Presidents, and operations managers
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Geostatisticians
and laboratory supervisors
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Miners,
metallurgists and chemists
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Quality
Assurance and Quality Control managers
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Environmental
engineers and pollution control specialists
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Concerned
investors and company shareholders
COURSE
CONTENT
Introduction
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Fundamental
statistical concepts used in sampling theory and sampling practices
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Nine kinds
of sampling errors: You must address them one at a time, otherwise
sampling is almost always invalid.
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Heterogeneity
of major constituents and trace constituents
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Examples
of common financial losses due to poor sampling practices
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Definition
of Data Quality Objectives
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Presentation
of a new quality strategy based on Data Quality Objectives
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Synergy
between Data Quality Objectives and sampling protocols
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Definition
of basic terms and symbols
Sampling
Theory and Practice
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Errors
generated by sample weights
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Optimization
of sampling protocols
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Description
of Heterogeneity Tests, for a normal case, and for a difficult
case
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Errors
generated by segregation
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Practical
implementation of sampling protocols
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Exploration
of the in situ Nugget Effect
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Selection
of realistic, economical cutoff grades
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Detailed
review of existing sampling systems:
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During
exploration (Diamond core, RC, …)
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At
mines (blastholes, …)
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At
plants (cross stream systems, in-stream probes, augers, …)
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At
laboratories (splitters, crushers, pulverizers, shovels, spoons,
spatulas, …)
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For
sampling commodities at shipping facilities
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For
sampling the environment
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Monitoring
precision and accuracy at the laboratory
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Monitoring
precision and accuracy of sampling and subsampling protocols
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Quantifying
the awesome cost of sampling precision
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Suggestions
for better sampling standards
Reconciliation
problems between the geological model, the mine, and the plant
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The myth
of reconciliation
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Identification
of major sources of reconciliation problems
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Capitalize
on existing data: A gold mine of opportunities
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Understand
the different kinds of heterogeneity and the variability they generate
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Become
more proactive through effective statistical thinking
Management
must set priorities
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Find causes
of problems and structural properties you must live with
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Invest
in minimizing causes of problems
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Find effects
of problems and circumstantial properties you cannot control
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Save money
by spending much less on effects of problems
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Managing
visible cost:
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Discovering
invisible cost:
Introduction
to Chronostatistics
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Critical
review of sampling modes: random systematic, stratified random,
and random
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Introduction
to variography
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Advanced
variography
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Introduction
to variographic statistical process control
The
Moving Average, a pragmatic, simple but delicate tool
The
Relative Difference Plot: The best tool for QC monitoring
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. |
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FEES
AND REGISTRATION
The registration
fee is $1,600 US. (10% discount for Colorado School of Mines
students.) The fee includes coffee breaks and course notes.
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 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
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FURTHER
INFORMATION
For further technical
information concerning the program, contact Mr. Francis Pitard at
(303) 451-7893, or e-mail at fpsc@aol.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.
The course will be
held on the campus of the Colorado School of Mines in Golden, Colorado
between 8 a.m. and 5 p.m. on the specified days.
Registrants are
responsible for making their own lodging and travel arrangements.
For travel information, click here
- for accommodations, click here.
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