Transcript INTEGRATION OF “SIX SIGMA” INTO MULTIDISCIPLINARY ENGINEERING DESIGN PROJECTS Mahbub Uddin Department of Engineering Science Trinity University A.

INTEGRATION OF “SIX SIGMA” INTO
MULTIDISCIPLINARY ENGINEERING DESIGN
PROJECTS
Mahbub Uddin
Department of Engineering Science
Trinity University
A. Raj Chowdhury
School of Technology
Kent State University
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I.
Introduction
II. Six Sigma Tools and Methodology
III. Integration of Six Sigma into
Multidisciplinary Engineering Design Projects
IV. Conclusions
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What is Six Sigma?
•“Six Sigma” is a data-driven, fact based, decision making
management tool used to improve the profitability of a
business enterprise by reducing the waste and defects
while improving product, processes and services and
increasing the customer satisfaction.
•Six Sigma is widely used in industry to improve the
efficiency of product design and development,
manufacturing and marketing.
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Improving Productivity …..
“6-Sigma”
Who is using Six-Sigma ?
Over
200
Companies
are using
Six-Sigma
today.
Few
examples
are:
ABB
Burlington
Hitachi Lincoln PerkinElmer
Allied
Cannon
Honda
Signal
Citigroup
Hughes IBM
Alcoa
Conseco
Jaguar
Maytag Raytheon
Kodak
NCR
Johnson Control
Amazon Dow-Chemical
Electric Poloroid
Lockheed Martin
Bendix
American Express Lear
Sony
Merrill Lynch
Ford
Honeywell
NCR
American Standard
Nokia
Motorola
Siemens T.I
Bank of America
SUN-Micro
Boeing
General Electric
Six-Sigma methods have applied to a variety of industries, such as:
Manufacturing, Service, Government, Legal, Financial
Software, Healthcare and Education
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History of “Six-Sigma”
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Six-Sigma was developed in the 1980’s by Motorola to address the
problem of how to be competitive with the Japanese companies.
Motorola engineers devised a method to track quality and compare
performance with customer requirements. An ambitious target of near
perfect quality (Six-Sigma) was the goal. Motorola’s goal required ten
(10) times improvement in five (5) years.
Motorola’s ambitious goal paid off…Two (2) years after launching SixSigma the company was awarded the “Malcolm Baldridge National Quality
Award”.
Over the next ten (10) years Motorola achieved the following:
* Cumulative savings attributed to six-sigma efforts were $14
billion.
* Five(5)-fold growth rate in sales with profits up to 20% per year.
* Stock prices gains compounded to an annual rate of 21.3%
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Six-Sigma-An Overview
The Greek letter  commonly represents standard deviation. The
phrase six sigma, on the other hand, denotes a specific
performance level—namely, 3.45 defects per million opportunities.
Six Sigma concepts are inspired by three fundamental ideas:
1. Cause and Effect Relationship.
2. A large variety of continuous physical observations follow the
normal probability distribution.
3. Common-cause variability is inherent in all systems. Additional
variability occurs due to assignable causes that must be identified
and eliminated.
•The basis of six sigma can be illustrated with the standard normal
distribution. The standard normal variable z is related to the normal
random variable x by the relationship:
  - 
•The standard normal distribution has the probability density
function:
z 
1
2
e - 1 z2
2
-
< 
•The standard normal distribution has zero and a unit variance.
•The normalization allows performance comparison of a wide variety
of processes and operations with widely varying units and
dimensions. The above equation leads to the familiar bell-shaped
curve.
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Improving Productivity …..
~ Why?? … Is it Worth Pursuing???
Sigma
Level
“DPMO”
1
691,000
2
309,000
3
67,000
4
6,200
5
230
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3.4
Cost of defects
as a percent(%)
of sales
•
•
31%
> 40%
•
•
69%
20- 40%
•
•
93.3%
15- 30%
•
•
99.4%
10- 20%
Quality
Level
99.98%
5- 10%
99.997%
0- 5%
Different Sigma Levels, Defects per Million
Opportunities, Quality Level and
Cost of defects/failures
Improve Quality
Improve Reliability
Reduce Cost
Reduce errors
Reduce waste
Improves Process
Improves Design
Improves Customer
Satisfaction
• Effective
Management
• Promotes Excellence
-
Creativity
Collaboration
Communication
Dedication
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Six-Sigma Tools
•Process Maps
•Cause and Effect Diagrams (Fishbone Diagram)
•Quality Function Deployment (QFD)
•Failure Modes and Effects Analysis (FMEA)
•Statistical Process Control (SPC)
•Analysis of Variance (ANOVA)
•Design of Experiments (DOE)
•Process Capability Analysis (PCA)
•Measurement Systems Analysis
•Multi-Variant Studies
•Control Plans
•Pugh Matrix (Criteria Matrix), etc.
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Design for Six Sigma Methodology
The tools of Six Sigma are most often applied through various
performance improvement methodologies such as:
•DMAIC: Design, Measure, Analyze, Improve & Control
•DMADC: Define, Measure, Analyze, Design & Verify
•DMEDI: Define, Measure, Explore, Design & Implement
Usually, DMAIC is used for improvement of product, process and
services, while DMADV and DMEDI are used for design and
development of new product, process and services.
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
projects
Define
What is the business case for the project?
Identify the customer?
Current state map
Future state map
What is the scope of this project?
Deliverables
Due Date
Control
During the project how will I control risk, quality, cost,
schedule, scope, and changes to the plan?
What types of progress reports should I create?
How will I assure that the business goals of the
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were accomplished?
How will I keep the gains made?
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Improve
What is the work breakdown structure?
What specific activities are necessary to meet the
project’s goals?
How will I re-integrate the various sub projects?


do?




this
Measure
What are the key metrics for this business process?
Are metrics valid and reliable?
Do we have adequate data on this process?
How will I measure progress?
How will I measure project success?
Analyze
Current state analysis
Is the current state as good as the process can
Who will help make the changes?
Resource requirements
What could cause this change effort to fail?
What major obstacles do I face in completing
project?
Flow Chart of Application of DMAIC Methodology
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Define
What is being designed?
Why is it being designed?
Uses of QFD or the Analytic Hierarchical Process, to assure that
the goals are consistent with customer demands and enterprise
strategy
Verify
Verify the design’s effectiveness in the real world
Measure
Determine critical to stakeholder metrics
Translate customer requirements into project goals
Design
Design the new product, service or process
Use predictive models, so,I;atopm, prototypes, pilot
runs, etc. to validate the design concept’s effectiveness
in meeting goals
Analyze
Analyze the options available for meeting the goals
Determine the performance of similar best – in – class
designs
Flow Chart of Application of DMADV Methodology
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Implementation of Six Sigma
Design Methodology
The Implementation of DMADV methodology will be illustrated
through a multidisciplinary engineering design project: Design, built
and test the performance of a Shell and Tube Heat Exchanger. Shell
and Tube Heat Exchangers are widely used in process industry. The
design of a Shell and Tube Heat Exchanger requires the knowledge
of thermodynamics, fluid mechanics, heat transfer, process control
and instrumentations.
The schematic of a shell-and-tube heat exchanger.
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10 6 
8
 11,111
30  24
Application of a Shell and Tube Heat Exchanger
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Implementation of Six Sigma
Design Methodology
The DFSS (Design for Six Sigma) methodology is based on
four fundamental design objectives:
1. Design should incorporate a balanced prospective of customer
needs, current technology, efficient manufacturability,
sustainability and commercialization.
2. Design should full-fill the product functional requirement
without failure under normal conditions.
3. Design should be optimized based on the effect of
uncertainties on its performance.
4. The performance level (Six Sigma or otherwise) of the
designed product should be verifiable against all product
requirements.
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Step 1: Define
• Define the goal of the design activity: Design, build, test and
improve the performance of a shell and tube heat exchanger.
• Define the customer need: The customer wants to reduce the
uncertainties in the operation and performance of the heat
exchanger.
• The cost of the heat exchanger should be reduced by 20% of the
current market price. (This can be accomplished by efficiently
estimating and optimizing the safety factor of the heat exchanger
area).
• Make sure that design goals are consistent with customer needs.
• Establish a benchmark for a shell and tube heat exchanger.
• The following Six Sigma tools should be used in this step to assist
the project management: QFD (Quality Function Deployment),
SIPOC (Suppliers Input Process Outputs and Customers) and
Process map.
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Step 2: Measure
Measure the CTQ (Critical to Quality) variables and check their
compliance with the Upper and Lower Control Limits (UCLs and
LCLs).
For Heat Exchanger design project measure the following variables:
Heat Transfer Area
Shell-side heat transfer coefficient
Tube inside heat transfer coefficient
Shell-side fouling resistance
Tube inside fouling resistance
Tube wall thermal conductivity
Effective tube inside area
Effective tube outside area
Tube inside diameter
Tube outside diameter
Number of tube passes
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Number of shell passes
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Step 2: Measure (con’t)
For Heat Exchanger design project measure the following variables
(con’t):
• Translate customer requirement into project goals: Heat exchanger
outlet temperatures should not vary more than +5°C. Performance
analysis indicates that by reducing the variation of heat exchanger
outlet temperatures to +5°C will improve the heat exchanger
operation from Three Sigma to Five Sigma.
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Step 3: Analyze
• Analyze innovative concepts for design to satisfy customer need.
• Analyze the variability in CTQs.
• Analyze the effect of variability of input parameters to outputs.
For Heat Exchanger design example:
• Perform a stochastic (probabilistic) simulation for heat exchanger
design.
• Analyze the variation of CTQs: 1) variation of shell-side heat
transfer coefficient, 2) variation of tube in-side heat transfer
coefficient, 3) variation of shell-side fouling resistance, 4) variation
of tube inside fouling resistance, 5) variation of flow rates of input
streams and 6) variation of temperatures of input streams.
• Perform a sensitivity analysis of heat exchanger output
temperatures as a function of variability in CTQs. Take measures to
reduce the variance in the CTQ variables. The following Six Sigma
tools should be used in this step to analyze and reduce the
variance in CTQs: ANOVA, DOE, SPC, and PCA.
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Step 4: Design
• Design new equipment, process, product or services to satisfy
customer needs. The objective is to develop a detail design, predict
CTQs and revise design until CTQ predictions meet requirements.
Also, develop a simulation model and management plan for
construction/manufacturing and quality control. Develop a
prototype model to validate design effectiveness.
For Heat Exchanger design example:
• Complete the construction of a prototype shell and tube heat
exchanger based on design calculation, analysis and simulation.
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Step 5: Verify
• Verify whether the design satisfies the specifications, CTQ’s and
customer needs under real world application. Develop a control
plan to implement FEMA and SPC. Develop plans to assure
continued performance at a desired sigma level.
For Heat Exchanger design example:
• Verify whether the expected performance of the heat exchanger is
achieved under real world application. Continue to increase the
sigma level by identifying and eliminating the most significant
causes of the variability in heat exchanger design, manufacturing
and operation processes.
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10 6 
8
 11,111
30  24
Calculation of Sigma Level
On average, the outlet temperatures of the heat exchanger fails to
meet its specification 8 hours per month on service. After design
improvement using the DMADV methodology, the outlet temperature
of the heat exchanger fails to meet its specification 1 hour per month
on service. Calculate the Sigma level of the performance of the heat
exchanger before and after the design improvement.
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 1 1 ,1 1 1
DPMO before design improvement = 1 06 
3 0 2 4
Using Figure 3, the signal level = 3.7.
1
DPMO after design improvement = 1 06  3 0  2 4  1 ,3 8 8
Using Figure 3, the signal level = 4.5.
DMADV methodology Steps 1 – 5 are repeated to continuously
improve the performance of the heat exchanger till it achieves the
desired sigma level.
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23
10 6 
8
 11,111
30  24
Calculation of Sigma Level
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Senior
Design
Courses
ImpleApplication
mentation
of
Of Six
DMAIC
Sigma
DMADV,
Projects
DMEDII
Sophomores and Junior Design Courses
Six Sigma
Tools
Quality Control &
Reliability Analysis
Project
Management
Freshman Design Courses
Introduction to Six Sigma
Concepts
Background
Overview
Integration of Six Sigma into Engineering Design Courses.
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Conclusions:
Integrating Six Sigma concepts into multi-disciplinary design
projects would provide students a better understanding on how to
incorporate realistic design constraints, reduce variability and
continuously improve product and process design.
Integration of Six Sigma into multi-disciplinary design projects
would significantly enhance students learning experience in project
management and prepare them to provide leadership in
implementing Six Sigma in Industry.
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