Six Sigma Quality Engineering
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Transcript of Six Sigma Quality Engineering
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CSUNEngineeringManagement
Six Sigma Quality
Engineering
Week 4Measure Phase
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Chapter 5 Outline
Process Map/Spaghetti Diagram Cause & Effect Fishbone Diagram Cause & Effect Matrix Reproducibility & Repeatability (Gage R&R) Capability Analysis
Components of Variation Studies FMEA
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Process Map/Spaghetti Diagram
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What is a Process Map?
A process map is a graphical representation of the flow of aprocess
A detailed process map includes information that can be usedto improve the process, such as:
Process Times
Quality
Costs
Inputs
Outputs
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Types of Process Map
Basic process map Detailed process map
Work-flow (spaghetti diagrams)
Top-down flowchart
Deployment flowchart Opportunity flowchart
Current State / Future state maps
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Uses of a Process Map
Identify areas for focus of improvement efforts Identify and eliminate non-value added steps
Combine operations
Assist root cause analysis
Baseline for failure mode and effect analysis (FMEA) Identify potential controllable parameters for designed
experiments
Determine needed data collection points
Eliminate unnecessary data collection steps
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Detailed Process Map Example
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TUNN
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(Y's)Coating- Thickn
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COAFITTI(x's)C Speed of c
C TemperatuC Make up ofS CleanlinesN GeometryS Pendant stS Amount peS Weight of p(Heat remoS Time fromN Humidity
(x's)
C Speed ofS TemperaN GeometrN HumidityS Air veloci(x's)S QualityC TempeS LevelS LevelN GeomeN OperatS QualityN SpecifiS Rate oS FluidityN Power
(x's)
S WatN WatC SpeN Mas(Rate
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NS
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Process Maps
Should include Major activities and tasks
Sub-processes
Process boundaries
Inputs
Outputs
Documents reality, not how you think the process is supposedto be completed
Should identify opportunities for improvement
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Steps for Process Mapping
Scope the process Identify the start and end points of the process of interest
Document the top level process steps
Create a flow chart
Identify the inputs and outputs
What are the results of doing each process step? (Ys)
What impacts the quality of each Y? (xs)
Characterise the inputs
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Characterising Inputs
Inputs can be classified as one of three types Controllable (C)
Things you can adjust or control during the process
Speeds, feeds, temperatures, pressures.
Standard Operating Procedures (S)
Things you always do (in procedures or common sense things)
Cleaning, safety.
Noise (N)
Things you cannot control or don not want to control(too expensive or difficult)
Ambient temperature, humidity, operator...
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Example
Machining a shafton a lathe
Inputs (xs)Rotation speedTraverse speedTool typeTool sharpnessShaft materialShaft lengthMaterial removal per cut
Part cleanlinessCoolant flowOperatorMaterial variationAmbient temperatureCoolant age
Outputs (Ys)DiameterTaperSurface finish
CCCCCCC
SCNNNS
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BEFORE40 NVA STEPS
NOTE: FROM THE CUSTOMERS
VIEWPOINT ALL OF ORDER ENTRY
IS NON-VALUE ADDED
Order Entry Process MapAs-Is
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AFTER11 NVA STEPS
REMEMBER: FROM THE CUSTOMERS VIEWPOINT
ALL OF ORDER ENTRY IS NON-VALUE ADDED
We eliminated the steps thatwere NVA and
UNNECESSARY (WASTE)BEFORE
40 NVA STEPS
Order Entry Process MapNew
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Work-flow or Spaghetti Diagram
A work flow diagram is a picture of the movements of people,materials, documents, or information in a process.
Start by tracing these movements onto a floor plan or map ofthe work space.
The purpose of the work-flow diagram is to illustrate theinefficiency in a clear picture.
How can you make the map look simpler? What lines canyou eliminate?
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56 Frame (Small Motor) Assy & Fabrication -Before
BEFORE KAIZEN:Area: 4640 sq ftOperator Travel: 3696 ftProduct Travel: 1115 ft x
xx x
x xx
xx
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Cause & Effect
Fishbone Diagram
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Cause & Effect Fishbone Diagram
Objectives
To understand the benefits of Cause & Effect Analysis
To understand how to construct a C & E Diagram
Analysis
A method a work group can use to identify the possible causes of aproblem
A tool to identify the factors that contribute to a quality characteristic
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Uses of C & E Fishbone Diagram
Visual means for tracing a problem to its causes Identifies all the possible causes of a problem and how
they relate before deciding which ones to investigate
C & E analysis is used as a starting point for investigatinga problem
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Fishbone Diagram
Effect
The problem or quality characteristic
The effect is the outcome of the factors that affect it
Effect
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Fishbone Diagram
Causes All the factors that could affect the problem or the quality
characteristic
Five Major Categories
Materials
Methods
People
Machines
Environment
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Effect
PeopleMethodsMaterial
Machine Environment
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Cause & Effect
matrix
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The Eight Steps in Cause and EffectAnalysis
Define the Effect Identify the Major Categories
Generate Ideas
Evaluate Ideas Vote for the Most Likely Causes
Rank the Causes
Verify the Results Recommend Solutions
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Rating of
Importance to
Customer
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Total
Process Step Process Input
1 0
2 0
3 0
4 0
5 0
6 0
7 08 0
9 0
10 0
11 0
12 0
13 0
14 0
15 0
16 0
17 0
18 0
19 0
20 0
0
Total 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Lower Spec
TargetUpper Spec
1
2
3
4
5&
6
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Reproducibility & Repeatability
(Gage R&R)
Data is only as good as the system that measures it. If you
cant measure it, you cant manage it.
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I often say that when you measure what you are speakingabout and express it in numbers, you know something about it.
LORD KELVIN, 1891
He clearly stressed that little progress is possible in any field ofinvestigation without the ability to measure. The progress of
measurement is, in fact, the progress of science.
The Science of Measurement
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Objectives
Measurement Systems Analysis Key Terminology
Variable Gauge R&R
A tool for estimating measurement system error
How to conduct a gauge R&R
Minitab Output
Gauge R & R Study Exercise
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Definitions
Variable Data Continuous measurements such as length, voltage, viscosity
Repeatability
Variation in measurements obtained with one gage when usedseveral times by one appraiser.
Reproducibility
Variation in the average of the measurements made by differentappraisers using the same measurement system.
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What is GR&R?
Measurement Systems Analysis
GRRRRRRR!!!
2T =
2p +
2m
2T = Total Variance
2p = Process Variance
2m= Measurement Variance
How good is ourmeasurement system?
G R&R All C t l f th
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Gauge R&R Allows Control of theMeasurement System
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Variable Gauge R&R - Whats Involved?
1 Gauge
3 Appraisers
10 Parts
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How to set up a Variable GRR Study
Preparation & Planning 1 Gauge
3 Operators (Appraisers)
10 Parts
3 Trials Randomize the readings
Code the parts (blind study) if possible
3 Ops x 10 parts x 3 trails = 90 Data Points
4 Ops x 10 parts x 3 trails = 120 Data Points
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Minitab Gage R&R Graphical Output
The number of distinct categories of
parts that the process is currently able
to distinguish (Must distinguish at
least 5 types of parts)
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Acceptability Criteria
R&R Indices
10% Acceptable Measurement System 10% - 30% May be acceptable based upon application,
cost of measurement device, cost of repair,etc.
30% Not acceptable. Measurement systemneeds improvement.
Number of Distinct Categories Index
1 Unacceptable. One part cannot be
distinguished form another. 2 -4 Generally unacceptable
5 Recommended
Module0025
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Minitab Gage R&R Graphical Output
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Minitab Gage R&R Graphical Output
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Minitab Gage R&R Graphical Output
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Minitab Gage R&R Statistical Output
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Capability Analysis
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Process Capability Study
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Cpk & Cp
Cpk incorporates information about both the process spread and the process mean, so
it is a measure of how the process is actually performing.Cp relates how the process is performing to how it should be performing. Cp does
not consider the location of the process mean, so it tells you what capability your
process could achieve if centered.
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Process Capability Study
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Non-normal distributions
Use Capability Analysis (Nonnormal) to assess the capability of an in-control
process when the data are from the nonnormal distribution. A capable process is ableto produce products or services that meet specifications.
The process must be in control and follows a nonnormal distribution before you
assess capability. If the process is not in control, then the capability estimates will be
incorrect.
Nonnormal capability analysis consists of a capability histogram and a table of
process capability statistics
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Questions? Comments?