SPC for Excel
SPC for Excel, a simple but powerful package, to handle all your SPC and statistical analysis needs. SPC for Excel software allows you to identify problem areas, gain insight into your data, spot trends and solve problems. All this in Excel. From the novice to the black belt, SPC for Excel will facilitate your process improvement efforts – in any industry – profit or non-profit.
Get all the techniques you need for your charting and analysis – including Pareto diagrams, Histogram, Control Charts, Gage R&R, Process Capability, Distribution Fitting, Data Transformation, Regression, DOE, Hypothesis Testing, and more! One time payment – yours forever. Two downloads per user and free Technical support. Try out our Demo – see how easy it is!
Process Capability analysis - to meet customer needs
Control charts and histograms - to manage processes
Gage R&R Studies – To validate your measurement system
Problem Solving Tools (Pareto and histogram, scatter, etc.) - to help your group solve problems
Advanced Data Analysis Tools (DOE and ANOVA, distribution fittings, regression, hypotheses testing and more) are available to meet your advanced requirements.
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Minitab Statistical Software
Our namesake product, Minitab Statistical Software, leads the way in data analysis with the power to visualize, analyze and harness your data to gain insights and solve your toughest challenges. Access trusted, proven and modern analytics combined with dynamic visualizations to empower you and your decisions.
The latest version of Minitab Statistical Software includes access to Minitab on the cloud so you can analyze from anywhere, and Graph Builder, our new interactive tool to instantly create multiple graph options at once. Minitab offers modules for Predictive Analytics and Healthcare to boost your analytics even further.
Available in 8 languages: English, Chinese, French, German, Japanese, Korean, Spanish, and Portuguese.
For 50 years, Minitab has helped thousands of companies and institutions spot trends, solve problems, and discover valuable insights in their data through our comprehensive, best-in-class suite of data analysis and process improvement tools.
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DC-E DigitalClone for Engineering
DigitalClone®, for Engineering is the only software that integrates multiple scales of analysis into a single package. It is the world's best gearbox reliability prediction tool. DC-E, in addition to the modeling and analysis capabilities at the level of the gearbox and the gear/bearing, is the only software that models fatigue life using detailed, physics-based models (US Patent 10474772B2).
DC-E allows the construction of a digital twin of a gearbox. This includes all stages of the asset's lifecycle, from design and manufacturing optimization to supplier selection to failure root cause analysis to condition based maintenance and prognostics. This computational environment reduces the time and cost of bringing new designs to market and maintaining them over time.
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ndCurveMaster
ndCurveMaster, a specialized curve fitting software, is designed to fit curves with multiple variables. It automatically applies nonlinear equations to your datasets. These can be observed or measured values. The software supports curve and surfaces fitting in 2D 3D 4D 5D ..., dimensions. ndCurveMaster is able to handle any data, no matter how complex or how many variables there are.
ndCurveMaster, for example, can efficiently derive the optimal equations for a dataset that has six inputs (x1-x6) and a corresponding output Y. For example: Y = a0 - a1 - exp(x1)0.5 + a2 ln(x2)8... + a6 x65.2 to accurately match measured value.
ndCurveMaster uses machine learning numerical methods to automatically fit the most suitable nonlinear regression function to your dataset, and discover the relationships between inputs and outputs. This tool supports various curve fitting methods, including linear, polynomial, and nonlinear methods. It also utilizes essential validation and goodness-of-fit tests to ensure accuracy. Additionally, ndCurveMaster provides advanced assessments, such as detecting overfitting and multicollinearity, using tools like the Variance Inflation Factor (VIF) and the Pearson correlation matrix.
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