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&rZ&_r_\\Ar^#b%!!0!+r&A&n&n& &Z&qAhJw</rAAAK!K!n&n&8r^^n&n&r^Six Sigma Best Practices:
A Guide to Business Process Excellence for Diverse industries
Dhirendra Kumar, Ph.D.
Adjunct Professor of Industrial Engineering
University of New Haven
West Haven, Connecticut
2006
Note: Reproduction of the web site material is permitted providing no changes are made to the content and the author is recognized.
Chapter WS1 Six Sigma Overview
A seamless integration of statistical methodologies of Six Sigma process for business needs is presented in the book. This process will help the businesses to execute their strategic plans and track both short- and long-term strategic progress within various areas of their businesses.
The overview of this process as well as what Six Sigma trained resource should know is presented under the following topics:
WS1.1 Six Sigma Process Overview DMAIC
WS1.2 What the Six Sigma Trained Should Know?
WS1.1 Six Sigma Process Overview DMAIC
A high level overview of Six Sigmas DMAIC process is presented in Figure WS1.1. The presented overview includes
All the phases of the DMAIC process
Key activities in each phase of the process
Key decisions of Six Sigma process
Commonly utilized tools in each phase of the DMAIC process.
SHAPE \* MERGEFORMAT
WS1.2 What the Six Sigma Trained Should Know?
There are several levels of Six Sigma training programs available Yellow Belt, Green Belt, and Black Belt. Yellow Belt training is an introductory training for 1-2 days. If the Yellow Belt trained participants refer their handout material that would be a good source for them. For Green Belt trained participants, iSixSigma.com is developing a list known as GreenBelt101. This would be a good starting place. Their goal is to have 101 points about which Green Belt trained person should be able to do/know.
For Black Belt trained participants, a detailed list has been developed and presented on this web site. The developed list is divided into the following phases of Six Sigmas DMAIC process:
General and Define
Measure
Analyze
Improve
Control.
General and Define: A Six Sigma Black Belt trained should be able to
Orient him/her primarily quantitatively.
Use process/product data and develop generalized project goals.
Develop the business case to accomplish the identified goals.
Develop detailed project plans for achieving the defined goals.
Develop a program measurement system to achieve the goals to satisfy the customer needs.
Understand and be able to communicate the concept and rationale of continuous improvement, even after accomplishing the project goals.
Quantify the project benefits.
Communicate the roles of various business associates in the business changes and Six Sigma program, for example, executive sponsorship, steering committee, champion, change agent, expert, team leader, facilitator, team member.
Understand and analyze the money value with time.
Analyze Six Sigma projects benefits in terms of present value and future value.
Calculate the break-even point of the project.
Develop the discounted cash flow analysis (DCF), internal rate of return (IRR), and compare with other projects IRR.
Identify the cost of poor quality and be able to correctly categorize into the identified areas.
Identify project activities with durations and precedence relationship; develop the project schedule; activities earliest start, earliest finish, latest start, latest finish, the activities slack time and the projects critical path.
Calculate the cost of catching up activities if the project is delayed to meet the projects finish date.
Calculate the cost of accelerating the project to complete before the defined finish time.
Explain the concept of benchmarking and its limitations.
Evaluate the probability of the project success, if the organizational structure is available and the participants (sponsors, process owners, and team members) philosophy about Six Sigma is also known.
Understand the behavior psychology of the project participants.
Develop the project proposal for management approval.
Develop and maintain the Project Charter.
Identify customer needs.
Convert customer needs into Critical to quality characteristics (CTQs).
Develop the process maps based on the narrative information for the as-is process and should-be process.
Measure: A Six Sigma Black Belt trained should be able to
Calculate defects per million opportunities (DPMO), error per million opportunities (EPMO), and parts per million (PPM); and relate to sigma metrics.
Communicate the various types of measure (effectiveness, efficiency, qualitative, and quantitative) in process analysis.
Approximate the relative cost of unacceptable quality with various sigma levels, for example, 2.5 sigma business quality means 30% cost of unacceptable quality.
Quantitatively analyze the survey information received from customers and employees.
Develop the survey format for data collection.
Identify and develop the measurement scales, for example, nominal, ordinal, interval, etc.
Develop a data collection system, which ensures the concept of repeatability, reproducibility, accuracy, and stability.
Select the appropriate measurement system depending on the process activities.
Compute sigma value from the known process activities sequence data versus unknown process activities sequence data.
Utilize some basic data presentation techniques to present the historical and/or collected data, for example, histogram, pie chart, and bar graph.
Calculate some basic statistics from the data, for example, mean, median, mode, and standard deviation.
Construct a Pareto Diagram of the problem (issue) frequencies from a given list of problems (issues).
Validate the concept of central tendency based on a given set of raw data.
Compute statistical measures for dispersion and shape on a given set of raw data.
Identify the 25th and 75th percentile, the median, the lowest and the highest values in a given box plot.
Understand and apply wherever appropriate the concept of factorials, permutations and combinations, and commonly used probability distributions.
Compute expected values for the deterministic and probabilistic random variables.
Compute univariate statistics for samples.
Compute confidence intervals for various statistics
Read and interpret the values from a cumulative frequency table, histogram, and chart.
Perform a Process Capability Analysis, which includes computing and interpreting process capability indices, control limit calculations, estimating the percentage failure, etc.
Explain the assumptions that underlie the use of process capability indices.
Interpret and perform an FMEA/FMECA study.
Interpret and perform a modified FMEA study.
Develop the Event Tree Analysis.
Develop a Fault Tree Analysis.
Explain the relationship between business metrics (Net Profit, Return on Assets, and Cash Flow) and operational metrics (Throughput, Operating Expense, and Inventory).
Design the data (information) collection process.
Analyze: A Six Sigma Black Belt trained should be able to
Design the data analyzing system, once the data type is known.
Determine whether there is any statistically significant difference between two or more survey data.
Perform statistical trend analysis on cost of poor quality, if some historical/collected data are available.
Identify the statistical distribution(s) for the cost of poor quality if enough historical/collected data are available.
Develop an issues matrix and able to perform Chi-square analysis if the issues are listed by functional department.
Determine the linear or non-linear relationship if a table of X and Y data pairs is available.
Determine when to apply parametric statistical methods and when to apply non-parametric statistical methods.
Determine when to apply analytic statistical methods, and when not to apply.
Show the basic understanding of probability concepts, for example, the probability of dependent and independent events, mutually exclusive events, and simultaneously occurring events.
Have an understanding with the commonly used probability distributions, including: normal, hyper-geometric, binomial, exponential, Poisson, Chi-square, students t and F.
Correctly identify and utilize the probability distribution to conduct the analysis based on the historical/collected data.
Select and properly utilize the correct tool from the various available techniques to analyze the data, when the given data are assumed known or estimated from a sample.
Stratify the data as necessary before any detailed statistical analysis.
Understand and apply the assumptions of ANOVA, and be able to transform the data as necessary.
Identify which issue among the list of possible issues will most likely explain a non-random pattern in the regression residuals.
Perform a Chi-square test to determine if the samples are significantly different when two or more sets of responses to categorical items are collected. For example, customer survey responses for the auto garage service as poor, fair, good, and excellent.
Recognize/identify the need for any transformation of dependable variable and should be able to apply the correct transformation.
Determine if the stationary point is a minimum, maximum, or saddle point for a given/collected data.
Utilize a quadratic functional relationship to calculate the cost of a given process.
Conduct simple and multiple linear and quadratic regressions.
Identify patterns in residuals from an incorrect regression model and utilize the corrective action plan.
Explain the difference between regression and correlation analysis.
Perform goodness-of-fit tests to assess the possibility that sample data come from a population of a specified type of probability distribution.
Improve: A Six Sigma Black Belt trained should be able to
Utilize the concept of process reengineering to eliminate waste activities, minimize non-value added activities, and re-process the value-added activities.
Understand and develop the improvement strategies for factors and alternatives.
Complete statistical analysis with analysis of variance table for a 22 full-factorial experiment.
Plan a statistically designed experiment utilizing the basic principles of the Design of Experiments (DOE).
Demonstrate the understanding of the DOE through critiquing various experimental plans with or without shortcomings.
Differentiate the various types of experimental design models, for example, fixed-effects, random-effects, and mixed.
Understand the concept of randomization and blocking in designing an experiment.
Perform one-factor and two or more factors analysis and interpret the results.
Determine the correct experimental layout for a given set of variables each at two levels. The data analysis of such an experiment can identify which main effects are significant and can also state the effect of these factors.
Understand which two factors interactions are confounding along with the significant effects of the main factors.
Evaluate the requirements for the type of design of experiment.
Compute basic reliability statistics, for example, MTBF, and mission time reliability.
Utilize the failure rate data to improve the MTBF.
Compute and improve the system reliability through designing the system configuration in some combination of series, parallel, and series-parallel.
Recognize when the process is approaching Six Sigma.
Control: A Six Sigma Black Belt trained should be able to
Establish control system(s) to retain the gains achieved through Six Sigma project.
Understand the concept and procedures of the available pre-control methods.
Understand the impact of constraints, and should also be able to select the most appropriate constraint to optimize the implemented improvement.
Develop and interpret a run chart for a given set of data in time-ordered sequence.
Perform run length calculations, number of runs, and quantitative trend evaluation.
Develop preferably the run chart over the standard X control chart if the data are from an exponential distribution.
Select and perform the control charts and to analyze the developed charts for a given process whether the process is in a state of statistical control or not.
Demonstrate the above concept for both the discrete and continuous data.
Analyze the control chart and should also be able to match it with the correct situation, for example, sudden change in pattern versus a gradual trend toward upper/lower specification limit.
Correctly apply some available control charts for continuous data, for example, EWMA, Moving Average, and CUSUM.
Recognize the value of project documentation; and guide the team to complete the documentation.
Develop the future projects list.
PAGE
PAGE 1
DhirendraKumar ( 2006 -
Figure WS1.1: Six Sigma Process Overview - DMAIC
Self control, Dominant
variable, Feed back loop,
Controllable errors, SPC,
Project benefits
Control
Application of
Statistics in process
Improvement DOE,
Alternate solutions,
Risk analysis
Improve
Analyze
Define
and
Measure
Projected Benefits
No
Yes
Program Control and Analysis of
Actual Project Benefits
Proposed solution
and implementation
DOE to establish
better dependency
Test
Alternatives
Identify
Factors
Need to
define (study)
more about
dependency
Defined
enough
dependency
Alternatives
Improvement
goals met
?
Determine
(classify)
nature
of Xs
Process Reengineering
Eliminate obvious sources of variation
Analyze the relationship between Xs and Y, and Utilize Process Reengineering
Tools: Stratification, Hypothesis Testing, 2 Goodness of Fit Test, ANOVA, and
Regression and Correlation
EMBED Equation.3
Tools: Flow Charting, Business Metrics, and
Cause-and-Effect Diagram
Data Collection and Presentation: Tables
Graphs, and Charts
Basic Statistics: Mean, Median, Mode, Range,
Variance, and Standard Deviation
Quality Metrics: Sigma Metrics, DPMO, EPMO
Process Capability and Performance Indices
Expected
Benefits
Historical Data Analysis
Data Collection and Modification
CTQs
Only High Level Issues
S-I-P-O-C
Included: Specific, Measurable,
Observable, and Manageable
Excluded: Blame, Cause, and Remedy
Problem Statement
Mission Statement
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Steve Buda.
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