Six Sigma (What is it?) “Six sigma was simply a TQM process that uses process capabilities analysis as a way of measuring progress” --H.J. Harrington, “Six Sigma’s Long-Term Impact,” Quality Digest, June 2001 Six Sigma is a disciplined, data-driven approach and methodology for eliminating defects (driving towards six standard deviations between the mean and the nearest specification limit) in any process -- from manufacturing to transactional and from product to service.

Six Sigma (What can we expect?) To achieve Six Sigma, a process must not produce more than 3.4 defects per million opportunities.

Nonconforming Rate When Process is Centered Spec. Limit Conformance Non-Conform. Rate (ppm) Cp ±1 68.7% 317300 0.33 ±2 95.45% 48550 0.67 ±3 99.73% 2700 1.00 ±4 99.9937% 63 1.33 ±5 99.999943% 0.57 1.67 ±6 99.9999998% 0.002 2.00

Nonconforming Rate When Process is Off-Center ±1.5 Spec. Limit Conformance Non-Conform. Rate (ppm) Cpk ±1 30.23% 697700 -0.167 ±2 69.13% 308700 0.167 ±3 93.32% 66810 0.500 ±4 99.3790% 6210 0.834 ±5 99.97670% 2330 1.167 ±6 99.9996600% 3.4 1.500

Six Sigma (What do we need to do?) The fundamental of the Six Sigma methodology is the implementation of a measurement-based strategy that focuses on process improvement and variation reduction through the application of Six Sigma improvement projects. DMAIC process (define, measure, analyze, improve, control) for existing processes falling below specification and looking for incremental improvement. DMADV process (define, measure, analyze, design, verify) for developing new processes or products at Six Sigma quality levels.

Six Sigma (DMAIC) For existing process Define the project goals and customer (internal and external) deliverables Measure the process to determine current performance Analyze and determine the root cause(s) of the defects Improve the process by eliminating defects Control future process performance

Six Sigma (DMADV) For product/process development Define the project goals and customer (internal and external) deliverables Measure and determine customer needs and specifications Analyze the process options to meet the customer needs Design (detailed) the process to meet the customer needs Verify the design performance and ability to meet customer needs

Six Sigma (What do you need to know?) Define Project Definition / Management Developing a Business Case Chartering a Team Defining Roles and Responsibilities Gathering Voice of the Customer, Support for Project Translating Customer Needs into Specific Requirements SIPOC (Suppliers, Inputs, Process, Outputs, Customers) Diagram

Six Sigma (What do you need to know?) Measure (1) Process Mapping (As-Is Process) Data Attributes (Continuous Versus Discrete) Defining Metrics Measurement System Analysis Gage Repeatability and Reproducibility Data Collection Techniques Calculating Sample Size

Six Sigma (What do you need to know?) Measure (2) Data Collection Plan Understanding Variation Measuring Process Capability Calculating Process Sigma Level Rolled Throughput Yield Visually Displaying Baseline Performance

Six Sigma (What do you need to know?) Analyze (1) Visually Displaying Data (Histogram, Run Chart, Pareto Chart, Scatter Diagram) Detailed (Lower Level) Process Mapping of Critical Areas Value-Added Analysis Cause and Effect Analysis (a.k.a. Fishbone, Ishikawa) Affinity Diagram Data Segmentation and Stratification Correlation and Regression (Linear, Multiple)

Six Sigma (What do you need to know?) Analyze (2) Process Performance (Cp, CpK, Pp, PpK, CpM) Short Term Versus Long Term Capability Non-Normal Data Distribution Transformations Central Limit Theorem Goodness of Fit Testing Hypothesis Testing Analysis of Variance (ANOVA), Two Sample T-Tests, Chi Squared Test

Six Sigma (What do you need to know?) Analyze (3) Design of Experiments (DOE) - Full, Fractional Factorials Verification of Root Causes Determining Opportunity (Defects and Financial) for Improvement Statistical Software

Six Sigma (What do you need to know?) Improve Brainstorming Multi-Voting Process Simulation Quality Function Deployment Selecting a Solution Failure Modes and Effects Analysis (FMEA) Poka Yoke (Mistake Proofing New Process) Piloting Your Solution Implementation Planning Culture Modification Planning

Six Sigma (What do you need to know?) Control Assessing The Results of Process Improvement Statistical Process Control (SPC) Rational Sub-grouping Establishing Process Standards for Inputs, Process and Outputs Developing a Process Control Plan Documenting the Process Statistical Software

Six Sigma (What is the benefit$$?) According to the Six Sigma Academy, Black Belts save companies approximately $230,000 per project and can complete four to 6 projects per year. General Electric, one of the most successful companies implementing Six Sigma, has estimated benefits on the order of $10 billion during the first five years of implementation. (1995-2000)