A key application of @RISK is Six Sigma and quality analysis. Industries ranging from engine manufacturing to precious metals to airlines and consumer goods are using @RISK every day to improve their processes, enhance the quality of their products and services, and save money.

Whether it’s in DMAIC, Design for Six Sigma (DFSS), Lean projects, Design of Experiments (DOE), or other areas, uncertainty and variability lie at the core of any Six Sigma analysis. @RISK uses Monte Carlo simulation to identify, measure, and root out the causes of variability in your production and service processes and designs.

@RISK analyzes thousands of different possible outcomes, showing you the likelihood of each occurring. Uncertain factors are defined using over 35 probability distribution functions, which accurate describe the possible range of values your inputs could take. @RISK allows you to define Upper and Lower Specification Limits and Target values for each output, and comes complete with a wide range of Six Sigma statistics and capability metrics on those outputs, like Cpk, Cp, Cpm, and much more. These metrics can be placed directly in your spreadsheet model, or appear in the @RISK Results Summary window. Output graphs show markers for LSL, USL, and Target values. The Industrial edition of @RISK adds RISKOptimizer to your Six Sigma analyses for optimization of project selection, resource allocation, and more.

Six Sigma Quick Start
in @RISK
To do a quick Six Sigma analysis in @RISK:

1. Add your output cell, and click the properties button in the @RISK Add Output dialog box. Choose the Six Sigma tab, and enter LSL, USL, and Target values (or plug in cell references).

2. Enter in your spreadsheet where you'd like to see Six Sigma metrics. For instance, =RiskCpkUpper(A10) will return the upper limit of Cpk for the output in cell A10.

3. Simulate. Then see Six Sigma metrics directly in your spreadsheet, in the @RISK Results summary window, and on graph markers.

The figure below illustrates how @RISK helps to identify, quantify, and hone in on variation in your processes.

See @RISK Six Sigma results graph
See @RISK Six Sigma Results Summary window
See @RISK Six Sigma results in spreadsheet

Add RISKOptimizer
@RISK Industrial edition also includes RISKOptimizer, which combine the power of Monte Carlo simulation with genetic algorithm-based optimization. This gives you the ability to tackle optimization problems like that have inherent uncertainty, such as:

• resource allocation to minimize cost
• project selection to maximize profit
• optimize process settings to maximize yield or minimize cost
• optimize tolerance allocation to maximize quality
• optimize staffing schedules to maximize service
  

Learn More

» @RISK and RISKOptimizer Six Sigma Example Models
» @RISK and DMAIC
» @RISK and DFSS
» @RISK and Lean Six Sigma
» Download @RISK Six Sigma User’s Guide (PDF)