Crystal Ball Downloadable Resources
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This paper discusses techniques for estimating treatment plant operating costs, including identification of high impact cost areas and expected key cost variations year by year.
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This paper describes some of the lessons learnt in building a portfolio model of petroleum assets. The example is based on the evaluation of an acquisition opportunity, a setting which imposed its own constraints on the methodology.
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The application and benefits of Monte Carlo simulation in optimising the growth portfolio of Kumba Resources, a diversified mining company based in South Africa.
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A mining corporation is evaluating a small underground gold mining project containing an estimated one million ounces of gold.
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When drilling wells in certain types of terrain, the performance of a drill bit erodes with time because of wear. The problem is to determine the optimum replacement policy; that is, the drilling cycle between replacements.
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Example of how Lockheed Martin uses Crystal Ball
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Crystal Ball can be utilised to evaluate process steps for their full range of variation and assess the impacts of binary events. Results from the
analysis provide better assessments cycle time variation than an average approach.
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Statistically designed experiments (DOEs) have become an essential tool in many fields of research because they can lead to rapid learning and optimisation in less time and with less cost.
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This edition focuses on the CB.GetForePercent Crystal Ball function. Instead of having to go to the Forecast Chart, you can now view the corresponding forecast value directly on the spreadsheet.
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The Freeze command lets you see the that effect certain cells have on the model while holding other assumptions to their spreadsheet values.
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This article addresses cases whereby users observe small variations in the output between simulation runs. The article provides an understanding of 'seed' values and how they can be used to ensure consistent outcomes.
