sQcLLC provides both standard and custom training packages for statistical analysis and problem solving. Some examples of available modules are shown. Contact us to find out more!
These basic modules allow you to solve simple problems and to organize data for more complex analysis. Each module explains the concept, provides examples for the student to reference, and closes with "Hints, Tricks and Tips" for success. All modules are available on in a PDF format.
Organize the team's thoughts in to a coherent problem statement with initial improvement goals using the sQcLLC Roadmap. Focus on both short-term containment and long-term root cause analysis and problem resolution
Develop a process flow diagram of your manufacturing or service process
Use brainstorming techniques to generate ideas, then organize the ideas into categories to begin the DMAIC "Analyze" phase
Use the Toyota Production System method of analyzing a problem to determine why it occurred. Useful tool for procedural issues
Graphical techniques to determine which problems should be tackled first to provide the "biggest bang for your corrective action buck"
A visual technique to determine if problems follow a pattern or not
Data is examined for shifts, trends and cycles or a lack of time-based dependence
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Overview of the Define-Measure-Analyze-Improve-Control process
Determine if variable and attribute measurement systems are sufficient to solve a particular problem
Sample sizes to select for various types of problem solving efforts. Includes a discussion on the perils of using both too large and too small of a sample for a particular analysis
Discussion on the difference between parametric and non-parametric analysis techniques, including the pros and cons of using each type for a given set of data
Includes probability, hypothesis testing, and confidence intervals for one and two populations of data. Tests include z, Student t, Chi Square and F distributions
Alternative non-parametric tests for one or more populations. Tests include binomial sign, Wilcoxan Rank Sum, Tukey Duckworth, Wilcoxan Signed Rank, Kruskal-Wallis, and Brown and Forsythe
Parametric Analysis of Variance for Single Factor, Two Factor with and without Replication, and Full Factorial design and analysis
Explains the process to perform both simple and multiple linear regression
Explains how to incorporate and analyze categorical data using the Chi Square distribution
Provides an explanation and examples of the FMEA process, including suggestions for scaling factors and corrective actions
Methods to determine required tolerancing and control of the process using control plans and techniques
Custom modules can be created, too. Let us help you!
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