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High risk and high reward outlines are built-in to the metals and mining industry. Projects are typically on a multi-billion-dollar scale, with staged layers of complexity that everyone brings their own challenges. How can executives and decision-makers during this field effectively manage the threats of failure and set-backs and make truly informed decisions? Often, decisions are made supported subjective experience and expert opinions. While these elements have value, taken alone they're insufficient for handling the challenges of recent mining: delays, budget overruns, and questions of safety. Quantitative, systematic approaches to decision-making and risk management are necessary. Here are just a couple of recommendations on how such strategies are often wont to improve the management of mining and metals projects.

Take New Projects on a Test Run with Simulation Models

Pilot projects in any industry are pricy, but metal refineries affect particularly high costs. Take the instance of Met-Mex Peñoles—the world’s largest refiner of silver, and Mexico’s largest refiner of gold. Met-Mex wanted to avoid high pilot program costs and high numbers of the trial. Naturally, any pilot program testing innovations involving silver or gold are costly, as any value that's lost or ruined within the process carries a high price with it. Thus, they developed a quantitative method for process optimization that might hamper on the necessity for multiple trials runs on the metals themselves.

To do this, Met-Mex uses a Six Sigma Design of Experiments model in Microsoft Excel that comes with a Monte Carlo duplicate to make simulated trial runs of the newest manufacturing processes. This enables engineers to simulate changes in process design and answer difficult questions without actually running expensive trials of the method. The corporate utilizes actual data from past pilot projects as inputs to the recent mathematical model, alongside precise specifications and tolerances of its manufacturing devices, assorted physical operations, random processing errors, and price analyses. Precise pieces of knowledge help create a more accurate distribution of outcomes.

Pinpoint the foremost Pernicious Risks with Sensitivity Analysis

In these simulated test runs, Met-Mex Peñoles also wanted how to spot which of the various differing types of variables had the best influence on the result of the simulated test run.

Thus, they turned to a computational technique referred to as “What- If” sensitivity analysis to pinpoint which variables have the foremost impact.

“Whether in greater savings, improved pilot projects, or the security of employees, employing mathematically sound tools to any facet of the business in question can help metal and mining firms succeed”

Using software that involuntarily shows this data in tornado graphs, Met-Mex decision-makers were ready to easily review the most important risk factors and make decisions around mitigation plans during a truly informed way.

Quantify Project Ability with Monte Carlo-based Real Options Survey

Among the foremost important decisions mining companies make is which new projects to take a position in. There are always multiple choices for where to open new mines, and corporations must compare and evaluate different potential projects within the face of highly uncertain information. a nasty decision could waste billions.

One effective method for evaluating investment options during a portfolio may be a real options analysis. The method assigns a worth to varied investment options while considering risk. Unfortunately, many frameworks believe highly technical mathematical and economic analyses of investment options and portfolio construction, limiting the technique’s potential.

But it doesn’t need to be that way. Simplified real options frameworks carried the Datar-Mathews Method, expanded by the Boeing Corporation, are employed by organizations like mining giant Anglo American. These analyses incorporate external uncertainty as a source of project probability and endogenous unreliability as a source of project risk. Monte Carlo simulation is additionally wont to quantify the uncertainty inherent in each project and supply probabilistic ranges of possible values for his or her outcomes. Using these techniques, mining companies can recover insights into their capital portfolios than standard discounted income methods can provide.

Use Decision Trees for Complex Engineering Problems

Sadly, the metals and mining industry deals with serious safety risks. Mining is taken into account one among the world’s most dangerous occupations, with accidents often leading to loss of life. Thus, analyzing, evaluating, and mitigating safety risk is paramount for decision-makers during this field.

One of the foremost notorious mining accidents occurred on August 5, 2010, within the San José mine in northern Chile. The mine collapsed, trapping 33 miners 700 meters below the bottom. The Chilean government reached bent dozens of experts to assist affects the crisis, including the engineering consultancy Metaproject.

Manuel Viera, the CEO and managing partner of Metaproject, used a model-based approach to work out the simplest thanks to rescuing the miners that might subject them to the smallest amount risk. Viera used a choice support tool referred to as a choice tree to map the varied rescue alternatives, both from a technical and economic perspective. Metaproject also factored the key risks into their calculations, like the danger of landslides, failure of drilling machines, and therefore the physical and psychological state of the miners thanks to prolonged stays below ground.

Using the choice tree approach, Metaproject developed a matrix of statistical results for every rescue option, making it possible to work out, for instance, that for a few of the drilling options it had been feasible to maneuver the miners in two stages, except for others, it had been not, thanks to logistical problems.

Thanks in large part to the present thorough and significant approach, Metaproject was ready to recommend the simplest method of saving the 33 miners, and therefore the operation was administered successfully.

The mining and metals industry stands to realize an excellent deal from quantitative risk management. Whether in greater savings, improved pilot projects, or the security of employees, employing mathematically sound tools to any facet of the business in question can help metal and mining firms succeed.