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Decision Making 

Authors: Jack Caldwell


This review describes the use of formal decision making methods and software in comparing alternatives, evaluating risk, and making decisions in a mining context. The review lists software and consultants that may be employed to assist in the many phases of decision making, from brainstorming, alternatives listing, criteria setting and definition, alternatives comparison, risk evaluation, ranking, and rationalization for mining-related projects ranging from site selection, facility design, through to mine close plans and long-term surveillance and maintenance.


In this review we look at some of the methods and software readily available for use in making decisions in complex situations involving multiple criteria and trade offs.


The mine geologist, whether in exploration or on an established mine is part scientist, part practitioner, and part genius. How do you find that hidden ore body or track an elusive vein of gold that denies logic? Einstein said that genius is ninety-nine percent sweat and one percent inspiration. My old professor said that judgment is doing all the dreary calculations and then deciding on the basis of gut-feel and a bottle of brandy.

The sweat and calculation for the geologist is gathering data, collating information, walking the field, knowing the science, and looking at the stars. The inspiration and judgment, the decision, come in that blink of realization when the truth dawns.


Fault Tree Analysis Example Lightening hit the pump station. A pipe in the water treatment plant independently sprung a leak. Water potentially affected by perchlorate entered the domestic water supply. It was late Friday and nobody could communicate with anybody else. By Thursday the next week, at a client's behest, the following books were on my desk and we were compiling fault trees to evaluate system performance and decide what to fix:

  • McDermott, R.E., Mikulak, R.J., and Beauregard, M.R. "The Basic of FMEA" Productivity, Inc. Tel: 800-394-6868.
  • Stamatis, D.H. "Failure Mode and Effect Analysis: FMEA from Theory to Execution" ASQ Quality Press, Milwaukee, Wisconsin. www.asq.org
  • U.S. Nuclear Regulatory Commission "Fault Tree Handbook" NUREG-0492 NTIS Springfield, VA 22161.

I had never before compiled a fault tree, but after a visit to the plant where the pipe broke, and long discussions with the operators, I was able (with a very intelligent colleague) to formulate detailed fault trees that are now the basis of an extensive system overhaul.

The cynic's view of fault trees is that they are just another way of graphing the obvious. This may be true on superficial observation, but in my most limited experience, I was delighted by the results that accrued from the simple application of the rules and protocols. It is like dancing: the simplest steps soon take on a life of their own and a new vision of reality beckons.


ReliaSoft has a huge selection of software available for those faced with making a decision, evaluating equipment reliability, building fault trees, and visualizing stochastic events.

Isograph claims to be the world leader in developing and supplying integrated Reliability Engineering Software. Their products include software for fault tree analysis, event tree analysis, risk evaluation, reliability analysis life cycle costing and so on down the list to project management.

An interesting site I found where the consultants state they provide fault tree analysis services to the mining industry across Africa is Democritus whose services to mining include Root Cause Analysis, Event Tree Analysis, Fault Tree Analysis, and one I had not previously heard of Structured What If Technique (SWIFT).

Other sites where you can get the software and the means to draw fault trees or undertake any one of the many evaluations leading to a sound decision include:


These three publication set out a whole new and exciting way of making decisions:

If you want the philosophy, read Dennett; if you want the economic application, read Beinhocker; if you want to analyze your problems and make decisions, get the Palisade products.

Here is an overview of some of their tools and codes:

@RISK enables you to develop a model by defining your problem in an Excel worksheet, identifying uncertainty by specifying variables and their possible values along with probability distributions, analyzing the model via simulations to determine the range and probabilities of possible outcomes, and finally making a decision based on the model results and your own preferences.

PrecisionTree enables you to compile and analyze problems using influence diagrams and decision trees-you can apply probability distributions to any uncertain values in the decision tree, let Monte Carlo run, and get the range of possible results-hence you can make your decisions.

RISKOptimizer uses genetic algorithm-based optimization and Monte Carlo simulation to find optimal solutions to problems that are "unresolvable" by standard linear and non-linear optimizers. This is the tool if you seek to use the insights of Darwin to simulate your real-world problems and hence make decisions.

Let us turn then to what I have not done, namely use evolutionary theory in decision making. By way of background, here is how Palisade summarizes the relevant theory - see pp. 153-154 of the RISK Optimizer Users Guide, which comes with the DecisionTools Suite Industrial Edition.(I prefer the description by Dawkins in "The Selfish Gene"; a more recent description is to be found in "Breaking the Spell", once again by Dennett):

1. "Evolution takes place at the level of the chromosome. The organism doesn't evolve, but only serves as the vessel in which the genes are carried and passed along. It is the chromosomes which are dynamically changing with each rearrangement of genes.

2. Nature tends to make more copies of chromosomes [than can survive] which produce a more "fit" organism. If an organism survives long enough, and is healthy, its genes are more likely to be passed along to a new generation of organism through reproduction. This principle is often referred to as "survival of the fittest". Remember that "fittest" is a relative term; and organism only needs to be fit in comparison to others in the current population to be "successful".

3. Diversity must be maintained in the population. Seemingly random mutations occur frequently in nature that ensure variation in the organism. These genetic mutations often result in a useful, or even vital feature for a species' survival. With a wider spectrum of possible combinations, a population is less susceptible to a common weakness that could destroy them all (virus, etc.) or other problems associated with inbreeding."

Palisade tells us "the popularity of genetic algorithm is now growing exponentially … The International Conference of Genetic Algorithms is already focusing on practical applications, a sign of maturity that eludes other 'artificial intelligence' technologies."

Least I leave you with the idea that this is a biological issue only, here are some situationsoptimized using RISKOptimizer:

1. A senior executive wants to find the most effective way to distribute funds among the various departments of the company to maximize profit.

2. ZooCo is thinking of marketing a new drug used to make hippos healthier; they need to select the capacity level for a new plant that maximizes profits.

3. A university must assign 25 different classes to 6 pre-defined time blocks. Since the schedule must be developed prior to student registration, the actual number of students per class is uncertain.

4. It is June 8, 2000. GlassCo needs to purchase 500,000 gallons of heating oil on November 8, 2000. The current spot price of oil is 42 cents per gallon. GlassCo is hedging the price risk inherent in future oil purchase by buying oil futures that expire on December 8, 2000. How many futures should they buy?

5. A broker has a list of 80 securities of different types that will be worth a different and uncertain amount of money in the future. The broker wants to group these securities into five packages (portfolios) that will be as close to each other in total value as possible one year form now.

6. A salesman is required to visit every city in the assigned territory once. What is the route with the shortest travel time possible that visits every city?

7. And finally one that has aggravated each and every one of us: what is the optimal number of reservations to accept in excess of the number of available seats-the classic overbooking problem.

For the mining engineer, these are the classic problems you may solve with Palisade's suite of codes: Will minerals be found? If a deposit is found, will it be economical, or a bonanza? Will the costs of developing the deposit be as forecast? Will some political event like an embargo, tax reform, or new environmental regulations drastically alter the economic viability of the project? If you do solve any of these problems using these codes, let both Palisade and me know and we will pass along the success story.

Maybe I am lucky: I have no acknowledged problem of sufficient complexity to warrant use of RISKOptimizer. In the meantime I can only revel in the beauty of the theory, the code, and the potential. But before you take off, here are some problems culled from Wikipedia that may affect the answer:

1. In complex problems, genetic algorithms (GAs) may converge towards local optima rather than the global optimum. The likelihood of this occurring depends on the shape of the fitness landscape. The Palisade technical folk note that they have always found that GAs do better than traditional linear solvers at finding global solutions rather than local optima.

2. Operating on dynamic data sets is difficult, as genomes begin to converge early on towards solutions which may no longer be valid for later data. Recent research has also shown the benefits of using biological exaptation (or preadaptation) to solve this problem.

3. GAs cannot effectively solve problems in which the only fitness measure is right/wrong, as there is no way to converge on the solution. (No hill to climb). In these cases, a random search may find a solution as quickly as a GA.

4. Selection is clearly an important genetic operator, but opinion is divided over the importance of crossover versus mutation. Some argue that crossover is the most important, while mutation is only necessary to ensure that potential solutions are not lost. Others argue that crossover in a largely uniform population only serves to propagate innovations originally found by mutation, and in a non-uniform population crossover is nearly always equivalent to a very large mutation (which is likely to be catastrophic).

5. For specific optimization problems and problem instantiations, simpler optimization algorithms may find better solutions than genetic algorithms (given the same amount of computation time). Alternative and complementary algorithms include simulated annealing, hill climbing, and particle swarm optimization.


Once the draft of the feasibility study was ready, we proceeded to meet with the responsible parties to discuss comparison of alternatives and designate the preferred alternative. The first peer reviewer of the feasibility study said that I wrote too much in comparing the alternatives and that he had forgotten the beginning by the time he came to the end. Another approach to comparing alternatives was needed.

We settled on Decision Plus, one of the most fun-to-use software packages I have recently come across. Open the screen, type in your goal, in our case "Remediate the Site", then type in objectives or criteria (whatever you choose to call them), and then type in your Alternatives.

I did this alone, but the system is set up to be used in a brainstorming session, in a freewheeling group of individuals with bold and brash ideas. Next with the mouse you join the objectives to the goal, or join secondary objectives to primary objectives. Finally click a menu button, and there appears a fine hierarchy diagram linking goal, criteria, and alternatives.

To establish which is the best alternative, which is the worst, and which fall somewhere in the middle, you or your group of experts is required to assign weights to criteria and alternatives. This sounds hard but it is very easy in practice-that is if you can get everybody to agree (a task for a skilled facilitator).

Once the weighs are in the computer, again another click of the button and the rating scores appear in any one of a number of formats, including bar charts, pie charts, and sensitivity plots if you have included uncertainty in your ratings and rankings and weights.

DecisionPlus uses different methods to calculate scores, but ultimately they are all based on the concepts of multi-attribute utility analyses, which for those who do not care, boils down to adding the numbers you put in for each weight and normalizing by sums calculated by formulae that are well documented in the handbook.

And on that topic let me confess that I enjoyed reading the handbook almost as much as I enjoyed playing with the program. The handbook is well written, clear, and informative. The only problem I had with this software is that printing out the results was a disaster and finally I gave up and passed it on to the graphics department whose comments I suppress.


We collate almost everything Andy Robertson has written on mine closure in an InfoMine e-book. In particular we include chapters on the use of Failure Modes & Effect Analysis (FEM) and Multiple Accounts Analysis (MAA) in making a decision about how to close a mine. In essence the MAA approach is simply the reduction of decision trees to a static matrix listing criteria on the left-hand side and alternatives in the top row and putting weights and scores in the intersecting boxes. The MAA materials are useful in that they list criteria used in practice in comparing alternatives in real mining situations.


Gordon McPhail of Metago in Australia writes of the use of risk assessment strategies in making decision about how best to close mine waste disposal facilities in Australia.


The EPA and those complying with EPA regulations use these evaluation criteria to compare alternatives and come to a decision. This is usually done by way of a way of written narrative. There is no reason in principle why these may not be used as the primary criteria in a decision tree, hence numerical comparison of alternatives:

  1. Overall protection of human health and the environment. Addresses whether an option protects both human health and the environment. This standard can be met by reducing or removing pollution or by reducing exposure to it.
  2. Compliance with applicable or relevant and appropriate requirements. This standard, known as ARARs, ensures that options comply with federal, state and local laws.
  3. Long-term effectiveness and permanence. This evaluates how well an option will work over the long-term, including how safely remaining contamination can be managed.
  4. Reduction of toxicity, mobility or volume through treatment. Addresses how well the option reduces the toxicity, movement and amount of pollution.
  5. Short-term effectiveness. How quickly can an option help the situation and how much risk will there be while the option is under construction.
  6. Implementability. Evaluates how feasible the option and whether materials and services are available in the area.
  7. Cost. Includes not only buildings, equipment, materials and labor but also the cost of maintaining the option for the life of the cleanup.
  8. State acceptance. Does the Michigan Department of Environmental Quality accept the option. EPA evaluates this criteria after receiving public comments.
  9. Community acceptance. How well do nearby residents accept the option. EPA evaluates this standard after a public hearing and comment period.

More specific to the mining industry is the acronym: EE/CA. It is short for Engineering Evaluation/Cost Analysis. It is the brainchild of the U.S. Environmental Protection Agency (EPA): another of those documents that records decision making, usually involving the cleanup of a site-a removal action is the term used.To give you a better feel for the scope of a typical EE/CA, here is the Table of Contents for your perusal.

  • Executive Summary
  • Site Characterization
  • Identification of Removal Action Objectives
  • Identification and Analysis of Removal Action Alternatives
  • Comparative Analysis of Removal Action Alternatives
  • Recommended Removal Action Alternative.

EE/CAs have been used at many a mine site and it is instructive to read the summaries of these that are readily available on the internet:

A complete copy of the EE/CA for the Riley Pass Uranium Mines, South Dakota is available from the link provided. Similarly for the Midnight Mine, Washington. See also the comprehensive report on the White King and Lucky Lass mines in Oregon. The longest complete EECA I found is that for the La Sal Creek Watershed Project, Utah where old uranium mines are to be remediated.

Consultants with experience in EE/CA preparation and review include American Geological Services. To be fair, most consultants have written an analogous document, maybe with a different name but similar format and intent. But be careful, an EE/CA is supposed to be shorter than the RI/FS (thankfully), and less detailed than a cumbersome document called the Remedial Alternatives Analysis Report that I have dealt with.


I cannot but resist bringing your attention to the site for Sharpe Decisions Inc.Sharpe Decisions Inc. On the topic of risk assessment this is what they say:

"Sharpe Decisions Executive Workshop voting software is used by Corporations, Management Consultants and Associations around the world for Risk Assessment and Control Self Assessment Workshops. Using Rating Scales, Risks are rated on Impact and Likelihood (Probability) based on the knowledge of the participants in the room. Voter X-Y plots can be called up to see the "gap" in the vote and to discuss any wide ranging opinions. Weighted Sums and Formulas can be entered to have any results calculated by Adding, Subtracting, Multiplying or Dividing any result against any other. A "risk map" can be generated at the touch of a button with Heat Map colours, text, cross-hairs and labels added as required. Instantly the group can see which Risks are the highest threats to the organization and Controls can be formulated. If the organization wants to repeat the workshop in a few months to see the progress of the Controls, the new data can be plotted on the third and fourth axes and through the use of "arrows" the path the Risk has taken can be shown."

The history of the firm: In 1996 Sharpe Decisions Inc., was formed to develop and provide computer software and professional facilitation services for Group Decision Support. Their flagship software Sharpe Decisions(TM) Executive Workshop has the features and functions necessary to use in any format where participants opinions or judgments are needed.

Underground Mining with Simul8

Can’t afford the latest CIM collection of technical papers? It’s now on sale for $150. Here is how I got the information from a paper, the title of which caught my eye. The title is “Using Simul8 to model underground hard rock mining operations.”

A quick Google search provided a brief overview where McIntosh writes:

“A typical example of a [Simul8] computer simulation in underground mining would be a scenario involving multiple Load Haul Dump (LHD) units transferring ore from a source location (stopes or draw raises) to one or more ore passes. An engineering evaluation would be completed to determine the optimum number and size of LHDs required to transfer a specified ore quantity over the course of a particular time period (shift, day, week, month).

With certain limitations, it is possible to solve this problem with a spreadsheet. Cycle times can be determined based on alternative speeds, loading times, and tramming distances. The spreadsheet solution does not allow one to easily determine (with high confidence) the impact of multiple LHDs operating simultaneously.

If one LHD can handle a given tonnage of ore in a single shift, can two LHDs transfer double the quantity? Can three LHDs transfer three times the quantity? Of course the answer is no, two or more LHDs working simultaneously will encounter interference delays resulting in reduced productivities. Performing the evaluation with a spreadsheet requires the engineer to estimate an “interference factor.” The more units of equipment operating, the greater the impact of the interference factor.

The engineer’s problem is that no one has an instinctive feel for an appropriate interference factor. While we may have a good feel for factors such as loading, dumping, and travel times (based on the actual mining conditions), we do not have an instinctive feel for interferences.

They describe three case histories of the application of Simul8 in underground mine operations. These case histories deal with: (1) Underground Storage Bins; (2) Underground Truck Haulage; and (3) Block Level Cave Draw and Haulage Optimization. Bravo the freedom of the internet!

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