SIX SIGMA

STATISTICAL ANALYSIS 

Participants will gain the knowledge of Six Sigma skills and tools to improve business processes. This course is designed to teach Six Sigma methods and applications. It is ideal for a participant who:

• Leads improvement projects and needs knowledge of six sigma statistical and analytical methods to pinpoint opportunities and make improvements.
• Is a previously-trained black belt who wants to refresh and energize implementation of six sigma approaches.

In this 7-day workshop, participants are trained and tested on their understanding and ability to apply the statistical tools and techniques of the Six Sigma methodology.

Start Date:  June 3, 2015, Continuing June 4, 16, 17, 18, July 1, 2

Time: 9:00 a.m. to 3:30 p.m. 

Location: 2200 W. Cypress Creek Road, Fort Lauderdale,  FL 33309

Tuition:  SFMA Member: $2800 Group Rate (4 or more): $2600

Non-Member: $3000   Group Rate: $2800

Prerequisite:  Ideally, participants should have a laptop computer for use in class; have a technical background with advanced mathematics skills; have competence in computer use of spreadsheets and data applications; be able to use charts and graphs.

Topics Covered

Topic: DMAIC (Define, Measure, Analyze, Improve, Control) Process Improvement.  In this overarching topic, the DMAIC structured problem solving methodology is described and used. The phases of DMAIC lead a team logically from defining the problem to implementing changes to assuring improvements stick. The tools applicable to the various phases of DMAIC will be demonstrated through exercises.

Topic: Statistical Process Control and Process Capability.  In this topic, the simple but powerful Statistical Process Control tool is demonstrated and exercised to study key business processes and product characteristics. In this way the participant will learn to identify and predict process performance patterns.

Topic: Statistics for Effective Process Improvements.  This topic introduces and teaches advanced statistical tools that help participants determine what process and product data should be collected, interpret the data, and make decisions that maximize the effectiveness of process improvement activities.

Topic: Introduction to Designed Experiments.  This topic provides participants with the tools necessary to identify those inputs critical to the target process, and then set optimum levels for these inputs by performing Full and Fractional Factorial Designed Experiments.

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