This is an introduction course for six sigma.

The Lean Six Sigma Approach

Program Goals

• Techniques and tools for process improvement
• Goal is to improve quality by removing causes and minimizing variability
• Each project follows a defined sequence of steps and has KPIs

Tools

There are a lot of tools available to support each step of Lean Six Sigma process.

1. Define
• Process Mapping
• QFD(Quality Function Deployment)
• Kano Model
• Matrix Diagram
• Benchmarking
• Quality Costs
2. Measure
• Process Mapping
• Pareto Diagrams
• Sampling Methods
• Distribution
• Capacity of the process
3. Analyze
• FEMA
• Multi Vari Cards
• Correlation
• Simple and Multiple Linear Regression
• Proof of Hypothesis
4. Improve
• Experiment Analysis
• 2K Factorial Design
• Factorial Fractional Design
• Mix Design
• Surface Response Methodology
5. Control
• Control Plan
• Control Cards
• Poka Yoke
• Continuous Improvement(Kaizen)
• 5S

Step One: Define

There are 3 main activities in the define step.

1. Selection
2. Customer Focus
3. Process Mapping

Selection

• Determine the business need
• Develop a preliminary definition of the project
• Scope the project
• Determine what we will provide to the customer
• Establish roles

Customer Focus

• Who are our customers?
• What do we provide for them?
• What does "Critical to Quality" mean to our customers?
• What are the internal process we follow to provide products or services CTQs for our customers?
• How are our internal processes related to the CTQs?

Examples of Critical to Quality(CTQs)

Requisiton and delivery times
Invoice delivery and number of errors
Repair times
Correct instructions for use
Problem solving support
Politeness and courtesy
Preferential treatment

Process Mapping

"Value Stream Map" may be created to extend the usefulness of the process flow maps by adding more information such as: material flow, information flow, operational parameters, proces times, waiting times, etc.

Measure

Measurement Systems

• The effectiveness of any Six Sigma project relies in the use of $\underline{measurement}$.
• The foundation of the Six Sigma methodology is making decisions using data
• Decisions made using this data make the process reliable
• Decisions made using no reliable data equal decisions made not using any data at all

That is the reason why it is vital to have a good measurement system

Data Classifications

ATTRIBUTE DATA- Result from pass/non pass measure instruments
VARIABLE DATA - Result from the real measure of characteristics such as a credit application

Variance in Measurement System

The variance observed in any group of data is the sum of the real variation of the parts plus the variation of the measurement system.

Measurement Value = Real Value + Error in the Measurement

What to Expect from Data

• Accuracy
• Stability
• Repeatability
• Reproducibility

Measure: Key Concepts

• You must always verify your measurement system
• The samples must contain parts that cover the full range of the potential measurements
• The resolution of the machine must be under 10% of the potential range of measurement
• Evaluate the R&R of measurement as a % of the study of variation when the measuremetn is used for process decision-making
• Use tolerance % when the measuring is used to accept and reject parts

Analyze

FEMA

Failure Mode and Effect Analysis

It is a methodology used by a systematically directed team that identifies the potential failure modes in a manufacturing/assembly system
It identifies critical or significant characteristics of the disign or process that require special controls to prevent or detect the failure modes
It is a tool intended for problem prevention

Types of FEMA

• Product FEMA
• Process FEMA
• Application FEMA
• Service FEMA

Priority Risk Number(PRN)

• Severity (of Effect)
• Ocurrence (of Cause)
• Detection (capacity of the current controls)

Improve

Experiment Design

1. Define the Problem
• Clearly state the problem that has to be solved
2. Determine the Objective
• Identify the characteristics of response
• Determine the measuring method
3. Brainstorm
• Group control factors and noise factors
• Determine noise levels and values
4. Design the Experiment
5. Carry out the Experiment and Collect Data
6. Analyze the Data Using
• Regular analysis
• ANOVA(Analysis of Variance)
• Response graph
7. Interpret the Results

Control

• Develop of the control plan
• Implementation of a monitoring system
• Change revision and evaluation
• Changes in the process documentation
• Statistical Control of the Process
• Quality Plan

Control Plans

• List the outputs measurements
• List the key inputs from your data analysis

Control activities and process improvement must be made simultaneously to support continuous improve

Quality Plan

• The quality paln is a document of the Organization
• The control plan is part of the quality plan
• The quality plan is formed by the quality manual and the procedures of each area
• At the same time, the procedures and control plans generate other documents like the quality records
• The quality plan may be based on the IS, the TS or any other system
• The quality system is the responsiblity of every member of the organization

What is not measured is not improved

Improvement Process

• Need Analysis
• Function Analysis
• Formal Risk Evaluation (FMEA)
• Suppliers Evaluation
• Contigency Plan
• Auto Quality
• Process Tests
• Product and process Evaluation

QC Table of the Process

• Quality(Q): Imbalances, % of defects, capability of the process
• Costs(C): Material and personal costs, expenses
• Amount and Date(D): Utilization rate, deadlines, delays and compliance rate
• Productivity(P): Amount produced per time unit, number of times a worker operates each unit
• Safety(S): Number of accidents, level of accidents
• Morale(M): Absenteeism rate, number of improvement suggestions

In God we trust, all others must bring data

The Seven Basic Tools

1. Cause and Effect Diagrams
2. Flowcharts
3. Pareto Charts
4. Line Graphics
5. Histograms
6. Scatter Diagrams
7. Control Charts

The End

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