PSL - Process Optimization Using Six Sigma Techniques

Your Gateway to Business Excellence
Define Measure Analyze Improve Control
Process Optimization Using
Six Sigma Techniques

What is DMAIC ?
Define
Measure
Analyze
Improve
Control
“Many Potential Projects”
“Many Potential” Root Causes”
“Where are we now?”
“How do we sustain
the gains”
Single Project Selected
Project Baseline Measured
Root Causes Identified
And Verified
“What is the solution?”
Improvements Tested
and Measured
Self-Sustaining
Institutionalized
Process
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DMAIC - Define
Project Charter: Scope, Goals, Metrics
Quality Time Cost Growth
VALUE STREAM MAP/
PROCESS MAP
Voice of the
Business
(VOB)
Areas of Focus
Voice of the
Customer
(VOC)
S I P O C
Define The problem, measures and
process associated with the problem ,
quantify benefits and identify project
team.
• Define Customers and Requirements
(CTQs , VOC , VOB and Focus Area)
• Develop Problem Charter
(Scope/Goals and Key Metrics)
• Identify team members
• Develop Process Map

• Process Map provides graphical representation of process flow.
• Provides visualization of the process and helps identify opportunities for improvement.
• Helps to identify the boundary of the process (start and end of the process).
SIPOC Chart
Inputs:
Process
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Outputs: Customers:
Suppliers:
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Project Charter
• THE key document defining the objectives,
scope and financial impact of a Six Sigma
project.
• Elements in a Project Charter :
 Problem Statement
 Business Case
 Scope
 Critical to Quality / Voice of the Customer
 Goals
 Team Members
 Project Plan/Time line

Write a project charter for the
selected improvement project.
Group Activity - Homework

What Is a Measure?
• A quantified evaluation of characteristics.
• Examples include:
– Length of time (speed, age)
– Size (length, height, weight)
– Dollars (costs, sales revenue, profits)
– Counts of characteristics or “attributes” (types of
customer, property size, gender)
– Counts of defects (number of errors, late
checkouts, complaints)

Collecting Data :
Data Collection Forms
• Check sheets are used to collect data
• Enhance ease of data collection
- Faster capture
- Consistent data from different people
- Quicker to compile data
• Need to be designed for each job
Week of: 6/26 Collected by: Kevin Regan
TV Smk Det Thrmstat RemCon Shower Window
30-Jun 8:00a EJS X X 10 min
28-Jun 8:15a MWT X 1 hr
27-Jun 7:00p MWT X 15 min
26-Jun 6:30p KLC X 2 hrs
28-Jun 5:45p PP X 30 min
30-Jun 6:00a KR X 40 min
1-Jul 8:15p DRT X 4 hrs Replaced part
1-Jul 8:20p ECS X 2 hrs Not in stock
28-Jun 9:35a MWT X 1 hr
29-Jun 9:40a KLC X 30 min
29-Jun 5:15p EJS X 45 min
29-Jun 5:20p KR X 15 min
Repair
Time
Notes
Repair Complaint
Call DateCall Time Initials

Histograms
• A histogram is used to display the
distribution of a process data set.
How to construct a Histogram:
1) Segment the range of the data into equal
sized bins.
2) Vertical axis of the histogram labeled
frequency and horizontal axis of the
histogram labeled with the range of your
response.
3) Determine the number of data points that
reside within each bin.
Histogram
Frequency
103
102
101
100
99
98
40
30
20
10
0
Histogramof Histogram
Histogram
Frequency
103
102
101
100
99
98
40
30
20
10
0
Histogramof Histogram

1) Finalize your data collection plan
2) Create your check sheet (if relevant)
3) Collect the data
4) Choose the relevant data displaying tool
for your collected data

Lets review your homework

• The normal distribution is the most recognized distribution in statistics.
• Many sources of data tend to follow the Normal Distribution or bell shaped curve.
• 99.73% of the area of the normal distribution is contained between -3 sigma and +3
sigma from the mean.
The Normal Distribution

 1


ƒ(x)

 2


 1


 2


 3
 
 3

68.26%
99.73%
95.46%

Observation
Individual
Value
28
25
22
19
16
13
10
7
4
1
60
50
40
30
20
10
0
_
X=29.06
UCL=55.24
LCL=2.87
1
Control Chart of Recycle
Elements of Control Charts
Process Center
(usually the Mean)
Special Cause
Variation Detected
Control Limits

Types of Variation
• Special Cause Variation
- It is non random and changes over time.
- It is usually caused by an force acting upon the
process from the outside.
• Common Cause Variation
- It is an inherent part of the process itself and
can only be changed by changing the process
itself.

Common Cause Variation
• Some examples of common cause variation are:
– Machinery
Vibration of machines
Temperature fluctuations
Variability in material hardness
Web tension
Viscosity change
– Office
Experience of individual workers
Workers out sick
Internet server response time

Process Capability
• Most measures have some target value and
acceptable limits.
• The extent to which the “expected” values fall
within these limits determines how capable
the process is of meeting its requirements.

Calculate the process capability for
the metrics of your project.

Cause and Effect Diagram
(Fishbone or Ishikawa)
• What
– Relationship between an effect
(problem) and its potential
causes. Categorizes causes.
– It uses verbal inputs in a team
environment.
Problem or
Condition
The Y
The X’s
(Causes)
l
Categories
Material Measurement Environment
People Machine Method
The
Problem
Problem or
Condition
The Y
The X’s
(Causes)
l
Categories
Material Measurement Environment
People Machine Method
The
Problem

Group Activity
Create a cause and effect diagram for the factors that
affect the throwing distance of the catapult. Why
couldn’t you hit the 2 meters target accurately ?
Ex :
Pull back distance
Rubber elasticity
Measurement error
Time allocated = 15 minutes

Session Format
• Introduction to Improve
• Exercise : Catapult
• Improve phase
• Improvement Action Plan
• Introduction to Control
• Process Control Plan
• Group activities
• Homework
• Project Closeout Checkpoints
• Project guidelines

Exercise : The X Pult
Mission objective
To consistently hit the enemies at 2 meters accurately.
Exercise
1) Based on your root cause analysis , brainstorm and
come out with an improvement plan for your catapult .
2) Test it out and collect the data for 100 measurements.
3) Generate a revised X bar R bar with new control limits.
4) Calculate the new process capability index.
Time allocated = 1 hour

Action Responsible Due % Complete
Action Plan Template

Control
Implement controls to “sustain the gains”.
– Define and Validate Monitoring and Control
System
– Develop Standards and Procedures
– Implement Statistical Process Control
– Determine Process Capability
– Verify Benefits, Cost Savings/Avoidance, Profit
Growth
DMAIC - Control

Process Control Plan

Timeline for Project Commissioning, Project
Closeout Meetings and Validate Gate Review

Project Guidelines (Cont)
Use the required competencies below as a
checklist for your Process Optimization project.
To successfully complete this unit of
competency, you should ensure that you
document as many activities as possible using
the templates provided.
Your coach will guide you through the process.

Tools and Templates
1. SIPOC Map
2. Project Charter
3. X bar R chart (Excel file)
4. Process capability (Excel file)
5. Data collection plan
6. Cause and effect diagram
7. 5 Why analysis
8. Improvement action plan
9. Process control plan

Assessment Time
• Please hand copies of your completed
project forms and presentations to your
coach for assessing.
• If you need assistance, please ask

Appendix :Control Chart Selection Tree
TYPE OF DATA
Poisson Distribution
Count or Classification
(Attribute Data)
Count
Defects or
Nonconformance
Fixed
Opportunity
C Chart
Variable
Opportunity
U Chart
Classification
Defectives or
Nonconforming Units
Fixed
Opportunity
NP Chart
Variable
Opportunity
P Chart
Subgroup
Size of 1
I-MR
Subgroup
Size < 8-10
Xbar & R
Subgroup
Size > 8-10
Xbar & S
Measurement
(Variable Data)
Binomial Distribution Normal Distribution/Central Limit Theorem

Appendix : Process in Control ?
A. One or more points falls outside of the (UCL) or (LCL).
B. Two out of three successive points fall in the area that is beyond two standard deviations.
C. Four out of five successive points fall in the area that is beyond one standard deviation.
D. A run of six or more points that are all either successively higher or successively lower.
E. If eight or more points fall on either side of the mean.
F. 15 points in a row fall within the area on either side of the mean.

Appendix :
Sigma Quality Level Conversion Table
Yield DPMO Sigma
6.6% 934,000 0
8.0% 920,000 0.1
10.0% 900,000 0.2
12.0% 880,000 0.3
14.0% 860,000 0.4
16.0% 840,000 0.5
19.0% 810,000 0.6
22.0% 780,000 0.7
25.0% 750,000 0.8
28.0% 720,000 0.9
31.0% 690,000 1
35.0% 650,000 1.1
39.0% 610,000 1.2
43.0% 570,000 1.3
46.0% 540,000 1.4
50.0% 500,000 1.5
54.0% 460,000 1.6
58.0% 420,000 1.7
61.8% 382,000 1.8
65.6% 344,000 1.9
Yield DPMO Sigma Yield DPMO Sigma
69.2% 308,000 2
72.6% 274,000 2.1
75.8% 242,000 2.2
78.8% 212,000 2.3
81.6% 184,000 2.4
84.2% 158,000 2.5
86.5% 135,000 2.6
88.5% 115,000 2.7
90.3% 96,800 2.8
91.9% 80,800 2.9
93.3% 66,800 3
94.5% 54,800 3.1
95.5% 44,600 3.2
96.4% 35,900 3.3
97.1% 28,700 3.4
97.7% 22,700 3.5
98.2% 17,800 3.6
98.6% 13,900 3.7
98.9% 10,700 3.8
99.2% 8,190 3.9
Yield DPMO Sigma Yield DPMO Sigma
99.4% 6,210 4
99.5% 4,660 4.1
99.7% 3,460 4.2
99.75% 2,550 4.3
99.81% 1,860 4.4
99.87% 1,350 4.5
99.90% 960 4.6
99.93% 680 4.7
99.95% 480 4.8
99.97% 330 4.9
99.977% 230 5
99.985% 150 5.1
99.990% 100 5.2
99.993% 70 5.3
99.996% 40 5.4
99.997% 30 5.5
99.9980% 20 5.6
99.9990% 10 5.7
99.9992% 8 5.8
99.9995% 5 5.9
99.99966% 3.4 6
Yield DPMO Sigma

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