#18 'six sigma', presented by samik sengupta (ppt)

Six Sigma

EEL6887: Software Engineering

Shamik SenguptaSchool of EECS

University of Central Florida

March 8, 2006

3/8/06 Shamik Sengupta 2

Reference Sources

• The Inventors of Six Sigma, “http://www.motorola.com/motorolauniversity”

• GE, “http://www.ge.com/en/company/companyinfo/quality/whatis.htm”

• Wikipedia, “http://en.wikipedia.org/wiki/Six_Sigma”

• Six Sigma Overview, “http://www.induction.to/six-sigma/”

• “http://www.isixsigma.com/sixsigma/six_sigma.asp”

• “http://www.itil-itsm-world.com/sigma.htm”


Overview

• What is Six Sigma?– Definition– Why it is known as Six Sigma?– History of six sigma

• Six Sigma methodologies– Process model – Six Sigma project process tool

• Roles Required for Implementation

• Criticism of Six Sigma

• Six Sigma and CMMI

• Conclusion


What is Six Sigma?

• Six Sigma is a highly disciplined approach that helps enterprises focus on developing and delivering near-perfect products and services with 99.99966% accuracy.

• Originally, it was defined as a metric for measuring defects and improving quality; and a methodology to reduce defect levels below 3.4 Defects Per (one) Million Opportunities (DPMO) .

• 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.

• A statistical methodology to manage process variations that cause defects, defined as unacceptable deviation from the mean or target; and to systematically work towards managing variation to eliminate those defects.


Why is it known as Six Sigma?

Six Sigma focuses first on reducing variation, and then on improving process capability.


History of six sigma

• Six Sigma was pioneered by Bill Smith at Motorola in 1986.

• GE became one of the early adopters of Six Sigma and reported benefits of over US$300 million during its first year of application.

• Six Sigma is a registered service mark and trademark of Motorola.

• Motorola has reported over US$17 billion savings from Six Sigma to date.

• Starting with manufacturing, today Six Sigma is being widely used across a wide range of industries like banking, business process outsourcing (BPO), telecommunications, insurance, construction, healthcare, and software.


Six Sigma Methodologies

• Six Sigma has two key methodologies– DMAIC

– DMADV

• DMAIC is used to improve an existing business process.

• DMADV is used to create new product designs or process designs in such a way that it results in a more predictable, mature and defect free performance.


DMAIC

Define• Why must this project be done now?• Who is the customer?• What is the current state?• What are the tangible deliverables?• What is the due date?• ....

Analyze• Current state analysis• Who will make the changes?• What are the resources?• Failure probability• Major obstacles• ….

Improve• Work Breakdown Structure• Activities needed to meet goals• Reintegrate the various sub-projects• ….

Measure• What are the key metrics of this project?• Are metrics valid and reliable?• How will the metrics be measured?• How will the progress be measured?• ….

Control• Risk, quality, cost, schedule• Project reports• Business goals• Gains• ….


DMADV

Define• Why must this project be done now?• Who is the customer?• What is the initial state?• What are the tangible deliverables?• What is the due date?• ....

Analyze• Initial state analysis• Who will develop the project?• What are the resources?• Failure probability• Major obstacles• ….

Design• Plan• Detailed design • Work Breakdown Structure• Documentations• ….

Measure• What are the key metrics of this project?• Are metrics valid and reliable?• How will the metrics be measured?• How will the progress be measured?• ….

Verification• Plan• Design• Setup pilot runs• Documentations• ….


Six Sigma Metrics

• Baseline data from processes

• Defect rate (parts per million or ppm)

• Sigma level

• Process capability indices

• Defects per unit


Key Tools for Analysis

• Failure Modes Effects Analysis

• Cost Benefit Analysis

• Chi-Square Test of Independence and Fits

• Correlation

• Taguchi

• Pareto analysis and Control Charts


Failure Modes Effects Analysis

• Failure mode and effects analysis (FMEA) is a fault tree method (first developed for systems engineering) that examines potential failures in products or processes.

• It may be used to evaluate risk management priorities for mitigating known threat-vulnerabilities.

• The basic process is to take a description of the parts of a system, and list the consequences if each part fails. In most formal systems, the consequences are then evaluated by three criteria and associated risk indices:

– severity (S),

– likelihood of occurrence (O),

– inability of controls to detect it (D)

– Each index ranges from 1 (lowest risk) to 10 (highest risk).

• The overall risk of each failure is called Risk Priority Number (RPN)– RPN = S × O × D


Cost Benefit Analysis

• Cost-benefits analysis is the process of weighing the total expected costs vs. the total expected benefits of one or more actions in order to choose the best or most profitable option.

• Cost-benefit calculations typically involve using time value of money formula.

• This is usually done by converting the future expected streams of costs and benefits to a present value amount.


Chi-Square Test of Independence and Fits

• The chi-square test determines the probability of obtaining the observed results by chance, under a specific hypothesis.

• It tests independence as well as goodness of fit for a set of data retrieved from sub-projects.

• Pearson's chi-square test is the original and most widely used chi-squared test used in Six Sigma models.


Correlation

• Correlation, statistically known as correlation coefficient, indicates the strength and direction of a relationship between modules.

• “Zero” correlation coefficient between modules indicates that the modules do not have any correlation and are independent from each other.

• “One” correlation coefficient between modules indicates that the modules have strong correlation and are totally dependent on each other.

• The best known correlation coefficient determination method is the Pearson product-moment correlation coefficient


Taguchi

• Taguchi methods are statistical methods developed largely by Genichi Taguchi to improve the quality of manufactured goods.

• Taguchi's principle contributions to statistics are:– Taguchi loss-function– The philosophy of off-line quality control

• Taguchi loss-function– Taguchi adopted a squared-error loss function – It is the first symmetric term in the Taylor series expansion of any reasonable,

real-life loss function, and so is a "first-order" approximation– Total loss is measured by the variance– As variance is additive it is an attractive model of cost

• Off-line quality control – Taguchi realized that the best opportunity to eliminate variation is during

design of a product– The process has three stages:

• System design• Parameter design • Tolerance design


Pareto analysis and Control Chart

• A Pareto Chart is a special type of bar chart where the values being plotted are arranged in descending order.

• Typically the left axis is frequency, but can also be cost, or other unit of measure.

• The goal (and usage) of a Pareto Chart is to highlight the biggest factor for a set of factors.

• In a quality analysis this can be the largest defect, or can be used to represent the top half of problems.

• The control chart, also known as the 'Shewhart chart' or 'process-behavior chart' is a statistical tool intended to assess the nature of variation in a process and to facilitate forecasting and management.

• A control chart is a run chart of a sequence of quantitative data with three horizontal lines drawn on the chart:

– A central line, drawn at the process mean

– An upper control-limit

– A lower control-limit


Six Sigma Organizational Architecture

Champions

Process Owner (PO)

Green Belt (GB)

Quality Leader

(QL/QM)

Master Black Belt

(MBB)

Black Belt (BB)


Roles Required for Implementation

• Six Sigma identifies five key roles for its successful implementation.

• Executive Leadership includes CEO – Responsible for setting up a vision for Six Sigma implementation.

– Empower other role holders with the freedom and resources

• Champions are responsible for the Six Sigma implementation across the organization in an integrated manner.

• Master Black Belts, identified by champions, act as in-house expert

– They devote 100% of their time to Six Sigma.

– They assist champions and guide Black Belts and Green Belts.

– Apart from the usual rigor of statistics, their time is spent on ensuring integrated deployment of Six Sigma across various functions and departments.


Roles Required for Implementation (contd.)

• Black Belts operate under Master Black Belts – Apply Six Sigma methodology to specific projects.

– They devote 100% of their time to Six Sigma.

– They primarily focus on Six Sigma project execution,

– whereas Champions and Master Black Belts focus on identifying projects/functions for Six Sigma.

• Green Belts are the employees who take up Six Sigma implementation along with their other job responsibilities.

– They operate under the guidance of Black Belts and support them in achieving the overall results.

• Specific training programs are available to train people to take up these roles.


Training for Black Belts

Block 1• Strategy• People• Process or systems

Block 2• Customer Service

• Economics and Return• Measurement of Systems• Cycle Time Reduction

Block 3• Project Management• Control Charts

Block 4• Root Cause Investigation• Design of Experiments

Block 5• Procedures and Control Plan• Reliability Engineering• Presentation Skills• Theory of Inventive Problem Solving• Project Review

Black BeltCertification !!!


Training for Green Belts

Unit 1• Six Sigma introduction• Project guidelines• Defects handling• Behavior• Data Handling• Personal & team empowerment• Leadership and motivation

Unit 2• Customer Service• Finance control• Measurement of Systems• Cycle Time Reduction • Defining a project• Reading control charts

Unit 3• Project Management• Design of experiments• Root cause investigation• Failure modes effect analysis• Rigorous statistical methods• Audits• Presentations


Criticism of Six Sigma

• Complex methodology

• Rigorous statistical methods

• Rigorous training

• Controversy over the level of Six Sigma's effects, with some believing that its benefits have been vastly overstated

• Starts an unending cycle of improvement

• The sigma shift theory is often criticized by statisticians that the sample size is too small to make mathematically justified predictions.


Six Sigma and CMMI

• Six Sigma for Software is not a software development process definition

• Six Sigma is a data driven approach while CMMI is a process/document driven approach

• For an individual process:– CMMI identifies what activities are expected (industry best practices)

– Six Sigma identifies how activities can be improved (more efficient and more effective)

– Example: Project Planning

• The full potential of the data produced by following CMMI cannot be fully leveraged without applying the more comprehensive Six Sigma for Software toolkit.

• An additional distinction is that Six Sigma is typically applied to selected projects, while CMMI is intended for all projects.

• Six Sigma and CMMI compliment each other


Conclusion

• After being pioneered in 1986, Six Sigma is considered as one of the most comprehensive methodology to improve software systems.

• Application of proper Six Sigma methodology reduce defect levels below 3.4 Defects Per (one) Million Opportunities (DPMO).

• Companies that are already Six Sigma certified:– Dell, GE, HP, Intel, Motorola, Seagate, Xerox, and even the US Men's Olympic

Team

• Six Sigma is a data driven approach with complex statistical methodology

• Requires full time training and certification for personnel before being Six Sigma MBB / BB / GB

• It is still an open end problem

#18 'six sigma', presented by samik sengupta (ppt)

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