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rita_gahatyari007
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six sigma - November 26th, 2006

What is Six Sigma ?
TOOLS OF SIX SIGMA
SIX SIGMA INFRASTRUCTURE
MUMBAIíS AMAZING DABBAWALLAS!!!!
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Re: six sigma - November 26th, 2006

thnx for d project......but pls post it in ryt section..............
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Re: six sigma - November 26th, 2006

rita u hav done a good project.....adn thnkx for sharin it wit us.....but u hav uplaoded it in wrong section..............do take care it nxt times...........upload pojects in projects section.........

thnkx anyways n........becareful while postin nxt time.........


whisky, beer and cigarettes are the man's worst enemies.....arent they...????
but, the man who runs away fron his enemies is a coward.....


so face ur enemies and finish thm off....
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Re: six sigma - November 26th, 2006

hey nice 1 ,i even went for the seminar this yr where the dabbawalla s were invited for a speech
ooo they r really amazing !!!
this was a nice way to appreciate them.
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Re: six sigma - November 30th, 2006

wow nice clips can u sent some more clips related to INternational maarketing Concept
its a bit urgent
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Re: six sigma - December 4th, 2006

can u post on mumbai Dhabawalla and six sigma? thnks for sharing it
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gooood.......thanks...great project.......
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The Six Sigma Revolution
By Thomas Pyzdek


Why Six Sigma?
For Motorola, the originator of Six Sigma, the answer to the question "Why Six Sigma?" was simple: survival. Motorola came to Six Sigma because it was being consistently beaten in the competitive marketplace by foreign firms that were able to produce higher quality products at a lower cost. When a Japanese firm took over a Motorola factory that manufactured Quasar television sets in the United States in the 1970s, they promptly set about making drastic changes in the way the factory operated. Under Japanese management, the factory was soon producing TV sets with 1/20th the number of defects they had produced under Motorola management. They did this using the same workforce, technology, and designs, making it clear that the problem was Motorola's management. Eventually, even Motorola's own executives had to admit "our quality stinks,"[i]

Finally, in the mid 1980s, Motorola decided to take quality seriously. Motorola's CEO at the time, Bob Galvin, started the company on the quality path known as Six Sigma and became a business icon largely as a result of what he accomplished in quality at Motorola. Today, Motorola is known worldwide as a quality leader and a profit leader. After Motorola won the Malcolm Baldrige National Quality Award in 1988 the secret of their success became public knowledge and the Six Sigma revolution was on. Today it's hotter than ever.

It would be a mistake to think that Six Sigma is about quality in the traditional sense. Quality, defined traditionally as conformance to internal requirements, has little to do with Six Sigma. Six Sigma is about helping the organization make more money. To link this objective of Six Sigma with quality requires a new definition of quality. For Six Sigma purposes I define quality as the value added by a productive endeavor. Quality comes in two flavors: potential quality and actual quality. Potential quality is the known maximum possible value added per unit of input. Actual quality is the current value added per unit of input. The difference between potential and actual quality is waste. Six Sigma focuses on improving quality (i.e., reduce waste) by helping organizations produce products and services better, faster and cheaper. In more traditional terms, Six Sigma focuses on defect prevention, cycle time reduction, and cost savings. Unlike mindless cost-cutting programs which reduce value and quality, Six Sigma identifies and eliminates costs which provide no value to customers, waste costs.

For non-Six Sigma companies, these costs are often extremely high. Companies operating at three or four sigma typically spend between 25 and 40 percent of their revenues fixing problems. This is known as the cost of quality, or more accurately the cost of poor quality. Companies operating at Six Sigma typically spend less than 5 percent of their revenues fixing problems . The dollar cost of this gap can be huge. General Electric estimates that the gap between three or four sigma and Six Sigma was costing them between $8 billion and $12 billion per year.

What is Six Sigma?
Six Sigma is a rigorous, focused and highly effective implementation of proven quality principles and techniques. Incorporating elements from the work of many quality pioneers, Six Sigma aims for virtually error free business performance. Sigma, s, is a letter in the Greek alphabet used by statisticians to measure the variability in any process. A company's performance is measured by the sigma level of their business processes. Traditionally companies accepted three or four sigma performance levels as the norm, despite the fact that these processes created between 6,200 and 67,000 problems per million opportunities! The Six Sigma standard of 3.4 problems per million opportunities[1] is a response to the increasing expectations of customers and the increased complexity of modern products and processes.

If you're looking for new techniques, don't bother. Six Sigma's magic isn't in statistical or high-tech razzle-dazzle. Six Sigma relies on tried and true methods that have been around for decades. In fact, Six Sigma discards a great deal of the complexity that characterized Total Quality Management (TQM). By one expert's count, there were over 400 TQM tools and techniques. Six Sigma takes a handful of proven methods and trains a small cadre of in-house technical leaders, known as Six Sigma Black Belts, to a high level of proficiency in the application of these techniques. To be sure, some of the methods used by Black Belts use are highly advanced; including the use of up-to-date computer technology. But the tools are applied within a simple performance improvement model known as DMAIC, or Define-Measure-Analyze-Improve-Control[2]. DMAIC can be described as follows:

D
Define the goals of the improvement activity. At the top level the goals will be the strategic objectives of the organization, such as a higher ROI or market share. At the operations level, a goal might be to increase the throughput of a production department. At the project level goals might be to reduce the defect level and increase throughput. Apply data mining methods to identify potential improvement opportunities.

M
Measure the existing system. Establish valid and reliable metrics to help monitor progress towards the goal(s) defined at the previous step. Begin by determining the current baseline. Use exploratory and descriptive data analysis to help you understand the data.

A
Analyze the system to identify ways to eliminate the gap between the current performance of the system or process and the desired goal. Apply statistical tools to guide the analysis.

I
Improve the system. Be creative in finding new ways to do things better, cheaper, or faster. Use project management and other planning and management tools to implement the new approach. Use statistical methods to validate the improvement.

C
Control the new system. Institutionalize the improved system by modifying compensation and incentive systems, policies, procedures, MRP, budgets, operating instructions and other management systems. You may wish to utilize systems such as ISO 9000 to assure that documentation is correct.



Infrastructure
A very powerful feature of Six Sigma is the creation of an infrastructure to assure that performance improvement activities have the necessary resources. In this author's opinion, failure to provide this infrastructure is the #1 reason why 80% of all TQM implementations failed in the past. Six Sigma makes improvement and change the full-time job of a small but critical percentage of the organization's personnel. These full time change agents are the catalyst that institutionalizes change.

Leadership
Six Sigma involves changing major business value streams that cut across organizational barriers. It is the means by which the organization's strategic goals are to be achieved. This effort cannot be lead by anyone other than the CEO, who is responsible for the performance of the organization as a whole. Six Sigma must be implemented from the top-down.

Champions and Sponsors
Six Sigma champions are high-level individuals who understand Six Sigma and are committed to its success. In larger organizations Six Sigma will be lead by a full time, high level champion, such as an Executive Vice-President. In all organizations, champions also include informal leaders who use Six Sigma in their day-to-day work and communicate the Six Sigma message at every opportunity. Sponsors are owners of processes and systems who help initiate and coordinate Six Sigma improvement activities in their areas of responsibilities.

Master Black Belt
This is the highest level of technical and organizational proficiency. Master Black Belts provide technical leadership of the Six Sigma program. Thus, they must know everything the Black Belts know, as well as understand the mathematical theory on which the statistical methods are based. Master Black Belts must be able to assist Black Belts in applying the methods correctly in unusual situations. Whenever possible, statistical training should be conducted only by Master Black Belts. Otherwise the familiar "propagation of error" phenomenon will occur, i.e., Black Belts pass on errors to green belts, who pass on greater errors to team members. If it becomes necessary for Black Belts and Green Belts to provide training, they should do only so under the guidance of Master Black Belts. For example, Black Belts may be asked to provide assistance to the Master during class discussions and exercises. Because of the nature of the Master's duties, communications and teaching skills are as important as technical competence.

Black Belt
Candidates for Black Belt status are technically oriented individuals held in high regard by their peers. They should be actively involved in the process of organizational change and development. Candidates may come from a wide range of disciplines and need not be formally trained statisticians or engineers. However, because they are expected to master a wide variety of technical tools in a relatively short period of time, Black Belt candidates will probably possess a background in college-level mathematics, the basic tool of quantitative analysis. Coursework in statistical methods should be considered a strong plus or even a prerequisite. As part of their training, Black Belts receive 160 hours of classroom instruction, plus one-on-one project coaching from Master Black Belts or consultants.

Successful candidates will be comfortable with computers. At a minimum, they should understand one or more operating systems, spreadsheets, database managers, presentation programs, and word processors. As part of their training they will be required to become proficient in the use of one or more advanced statistical analysis software packages. Six Sigma Black Belts work to extract actionable knowledge from an organization's information warehouse. To assure access to the needed information, Six Sigma activities should be closely integrated with the information systems (IS) of the organization. Obviously, the skills and training of Six Sigma Black Belts must be enabled by an investment in software and hardware. It makes no sense to hamstring these experts by saving a few dollars on computers or software.

Green Belt
Green Belts are Six Sigma project leaders capable of forming and facilitating Six Sigma teams and managing Six Sigma projects from concept to completion. Green Belt training consists of five days of classroom training and is conducted in conjunction with Six Sigma projects. Training covers project management, quality management tools, quality control tools, problem solving, and descriptive data analysis. Six Sigma champions should attend Green Belt training. Usually, Six Sigma Black Belts help Green Belts define their projects prior to the training, attend training with their Green Belts, and assist them with their projects after the training.

Staffing Levels and Expected Returns
As stated earlier in this article, the number of full time personnel devoted to Six Sigma is not large. Mature Six Sigma programs, such as those of Motorola, General Electric, Johnson & Johnson, AlliedSignal, and others average about one-percent of their workforce as Black Belts. There is usually about one Master Black Belts for every ten Black Belts, or about 1 Master Black Belt per 1,000 employees. A Black Belt will typically complete 5 to 7 projects per year. Project teams are lead by Green Belts, who, unlike Black Belts and Master Black Belts, are not employed full time in the Six Sigma program. Black Belts are highly prized employees and are often recruited for key management positions elsewhere in the company. After Six Sigma has been in place for three or more years, the number of former Black Belts tends to be about the same as the number of active Black Belts.

Estimated savings per project varies from organization to organization. Reported results average about US$150,000 to US$243,000. Note that these are not the huge mega-projects pursued by Re-engineering. Still, by completing 5 to 7 projects per year per Black Belt the company will add in excess of US$1 million per year per Black Belt to its bottom line. For a company with 1,000 employees the numbers would look something like this:

Master Black Belts: 1
Black Belts: 10
Projects: = 50 to 70 (5 to 7 per Black Belt)
Estimated saving: US$10 million (US$10,000 per employee)
Do the math for your organization and see what Six Sigma could do for you. Because Six Sigma savings impact only non-value added costs, they flow directly to your company's bottom line.

Implementation of Six Sigma
After over two decades of experience with quality improvement, there is now a solid body of scientific research regarding the experience of thousands of companies implementing major programs such as Six Sigma. Researchers have found that successful deployment of Six Sigma involves focusing on a small number of high-leverage items. The steps required to successfully implement Six Sigma are well-documented.

1.Successful performance improvement must begin with senior leadership.
Start by providing senior leadership with training in the principles and tools they need to prepare their organization for success. Using their newly acquired knowledge, senior leaders direct the development of a management infrastructure to support Six Sigma. Simultaneously, steps are taken to "soft-wire" the organization and to cultivate an environment for innovation and creativity. This involves reducing levels of organizational hierarchy, removing procedural barriers to experimentation and change, and a variety of other changes designed to make it easier to try new things without fear of reprisal.

2.Systems are developed for establishing close communication with customers, employees, and suppliers. This includes developing rigorous methods of obtaining and evaluating customer, employee and supplier input. Base line studies are conducted to determine the starting point and to identify cultural, policy, and procedural obstacles to success.

3.Training needs are rigorously assessed. Remedial basic skills education Is provided to assure that adequate levels of literacy and numeracy are possessed by all employees. Top-to-bottom training is conducted in systems improvement tools, techniques, and philosophies.

4.A framework for continuous process improvement is developed, along with a system of indicators for monitoring progress and success. Six Sigma metrics focus on the organization's strategic goals, drivers, and key business processes.

5.Business processes to be improved are chosen by management, and by people with intimate process knowledge at all levels of the organization. Six Sigma projects are conducted to improve business performance linked to measurable financial results. This requires knowledge of the organization's constraints.

6.Six Sigma projects are conducted by individual employees and teams lead by Green Belts and assisted by Black Belts.
Although the approach is simple, it is by no means easy. But the results justify the effort expended. Research has shown that firms that successfully implement Six Sigma perform better in virtually every business category, including return on sales, return on investment, employment growth, and share price increase. When will you be ready to join the Six Sigma revolution?

About the Author
Thomas Pyzdek is a consultant in Six Sigma. Pyzdek writes the monthly column Six Sigma Nuts & Bolts for Quality Digest magazine. He has authored over 50 copyrighted works, including The Six Sigma Handbook.

source: http://www.pyzdek.com/six-sigma-revolution.htm



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101 Things A Six Sigma Black Belt Should Know
By Thomas Pyzdek


1.In general, a Six Sigma Black Belt should be quantitatively oriented.

2.With minimal guidance, the Six Sigma Black Belt should be able to use data to convert broad generalizations into actionable goals.

3.The Six Sigma Black Belt should be able to make the business case for attempting to accomplish these goals.

4.The Six Sigma Black Belt should be able to develop detailed plans for achieving these goals

5.The Six Sigma Black Belt should be able to measure progress towards the goals in terms meaningful to customers and leaders.

6.The Six Sigma Black Belt should know how to establish control systems for maintaining the gains achieved through Six Sigma.

7.The Six Sigma Black Belt should understand and be able to communicate the rationale for continuous improvement, even after initial goals have been accomplished.

8.The Six Sigma Black Belt should be familiar with research that quantifies the benefits firms have obtained from Six Sigma.

9.The Six Sigma Black Belt should know or be able to find the PPM rates associated with different sigma levels (e.g., Six Sigma = 3.4 PPM)

10.The Six Sigma Black Belt should know the approximate relative cost of poor quality associated with various sigma levels (e.g., three sigma firms report 25% COPQ).

11.The Six Sigma Black Belt should understand the roles of the various people involved in change (senior leader, champion, mentor, change agent, technical leader, team leader, facilitator).

12.The Six Sigma Black Belt should be able to design, test, and analyze customer surveys.

13.The Six Sigma Black Belt should know how to quantitatively analyze data from employee and customer surveys. This includes evaluating survey reliability and validity as well as the differences between surveys.

14.Given two or more sets of survey data, the Six Sigma Black Belt should be able to determine if there are statistically significant differences between them.

15.The Six Sigma Black Belt should be able to quantify the value of customer retention.

16.Given a partly completed QFD matrix, the Six Sigma Black Belt should be able to complete it.

17.The Six Sigma Black Belt should be able to compute the value of money held or invested over time, including present value and future value of a fixed sum.

18.The Six Sigma Black Belt should be able to compute present value and future value for various compounding periods.

19.The Six Sigma Black Belt should be able to compute the break even point for a project.

20.The Six Sigma Black Belt should be able to compute the net present value of cash flow streams, and to use the results to choose among competing projects.

21.The Six Sigma Black Belt should be able to compute the internal rate of return for cash flow streams and to use the results to choose among competing projects.

22.The Six Sigma Black Belt should know the COPQ rationale for Six Sigma, i.e., he should be able to explain what to do if COPQ analysis indicates that the optimum for a given process is less than Six Sigma.

23.The Six Sigma Black Belt should know the basic COPQ categories and be able to allocate a list of costs to the correct category.

24.Given a table of COPQ data over time, the Six Sigma Black Belt should be able to perform a statistical analysis of the trend.

25.Given a table of COPQ data over time, the Six Sigma Black Belt should be able to perform a statistical analysis of the distribution of costs among the various categories.

26.Given a list of tasks for a project, their times to complete, and their precedence relationships, the Six Sigma Black Belt should be able to compute the time to completion for the project, the earliest completion times, the latest completion times and the slack times. He should also be able to identify which tasks are on the critical path.

27.Give cost and time data for project tasks, the Six Sigma Black Belt should be able to compute the cost of normal and crash schedules and the minimum total cost schedule.

28.The Six Sigma Black Belt should be familiar with the basic principles of benchmarking.

29.The Six Sigma Black Belt should be familiar with the limitations of benchmarking.

30.Given an organization chart and a listing of team members, process owners, and sponsors, the Six Sigma Black Belt should be able to identify projects with a low probability of success.

31.The Six Sigma Black Belt should be able to identify measurement scales of various metrics (nominal, ordinal, etc).

32.Given a metric on a particular scale, the Six Sigma Black Belt should be able to determine if a particular statistical method should be used for analysis.

33.Given a properly collected set of data, the Six Sigma Black Belt should be able to perform a complete measurement system analysis, including the calculation of bias, repeatability, reproducibility, stability, discrimination (resolution) and linearity.

34.Given the measurement system metrics, the Six Sigma Black Belt should know whether or not a given measurement system should be used on a given part or process.

35.The Six Sigma Black Belt should know the difference between computing sigma from a data set whose production sequence is known and from a data set whose production sequence is not known.

36.Given the results of an AIAG Gage R&R study, the Six Sigma Black Belt should be able to answer a variety of questions about the measurement system.

37.Given a narrative description of "as-is" and "should-be" processes, the Six Sigma Black Belt should be able to prepare process maps.

38.Given a table of raw data, the Six Sigma Black Belt should be able to prepare a frequency tally sheet of the data, and to use the tally sheet data to construct a histogram.

39.The Six Sigma Black Belt should be able to compute the mean and standard deviation from a grouped frequency distribution.

40.Given a list of problems, the Six Sigma Black Belt should be able to construct a Pareto Diagram of the problem frequencies.

41.Given a list which describes problems by department, the Six Sigma Black Belt should be able to construct a Crosstabulation and use the information to perform a Chi-square analysis.

42.Given a table of x and y data pairs, the Six Sigma Black Belt should be able to determine if the relationship is linear or non-linear.

43.The Six Sigma Black Belt should know how to use non-linearity's to make products or processes more robust.

44.The Six Sigma Black Belt should be able to construct and interpret a run chart when given a table of data in time-ordered sequence. This includes calculating run length, number of runs and quantitative trend evaluation.

45.When told the data are from an exponential or Erlang distribution the Six Sigma Black Belt should know that the run chart is preferred over the standard X control chart.

46.Given a set of raw data the Six Sigma Black Belt should be able to identify and compute two statistical measures each for central tendency, dispersion, and shape.

47.Given a set of raw data, the Six Sigma Black Belt should be able to construct a histogram.

48.Given a stem & leaf plot, the Six Sigma Black Belt should be able to reproduce a sample of numbers to the accuracy allowed by the plot.

49.Given a box plot with numbers on the key box points, the Six Sigma Black Belt should be able to identify the 25th and 75th percentile and the median.

50.The Six Sigma Black Belt should know when to apply enumerative statistical methods, and when not to.

51.The Six Sigma Black Belt should know when to apply analytic statistical methods, and when not to.

52..The Six Sigma Black Belt should demonstrate a grasp of basic probability concepts, such as the probability of mutually exclusive events, of dependent and independent events, of events that can occur simultaneously, etc.

53.The Six Sigma Black Belt should know factorials, permutations and combinations, and how to use these in commonly used probability distributions.

54.The Six Sigma Black Belt should be able to compute expected values for continuous and discrete random variables.

55.The Six Sigma Black Belt should be able to compute univariate statistics for samples.

56.The Six Sigma Black Belt should be able to compute confidence intervals for various statistics.

57.The Six Sigma Black Belt should be able to read values from a cumulative frequency ogive.

58.The Six Sigma Black Belt should be familiar with the commonly used probability distributions, including: hypergeometric, binomial, Poisson, normal, exponential, chi-square, Student's t, and F.

59.Given a set of data the Six Sigma Black Belt should be able to correctly identify which distribution should be used to perform a given analysis, and to use the distribution to perform the analysis.

60.The Six Sigma Black Belt should know that different techniques are required for analysis depending on whether a given measure (e.g., the mean) is assumed known or estimated from a sample. The Six Sigma Black Belt should choose and properly use the correct technique when provided with data and sufficient information about the data.

61.Given a set of subgrouped data, the Six Sigma Black Belt should be able to select and prepare the correct control charts and to determine if a given process is in a state of statistical control.

62.The above should be demonstrated for data representing all of the most common control charts.

63.The Six Sigma Black Belt should understand the assumptions that underlie ANOVA, and be able to select and apply a transformation to the data.

64.The Six Sigma Black Belt should be able to identify which cause on a list of possible causes will most likely explain a non-random pattern in the regression residuals.

65.If shown control chart patterns, the Six Sigma Black Belt should be able to match the control chart with the correct situation (e.g., an outlier pattern vs. a gradual trend matched to a tool breaking vs. a machine gradually warming up).

66.The Six Sigma Black Belt should understand the mechanics of PRE-Control.

67.The Six Sigma Black Belt should be able to correctly apply EWMA charts to a process with serial correlation in the data.

68.Given a stable set of subgrouped data, the Six Sigma Black Belt should be able to perform a complete Process Capability Analysis. This includes computing and interpreting capability indices, estimating the % failures, control limit calculations, etc.

69.The Six Sigma Black Belt should demonstrate an awareness of the assumptions that underlie the use of capability indices.

70.Given the results of a replicated 22 full-factorial experiment, the Six Sigma Black Belt should be able to complete the entire ANOVA table.

71.The Six Sigma Black Belt should understand the basic principles of planning a statistically designed experiment. This can be demonstrated by critiquing various experimental plans with or without shortcomings.

72.Given a "clean" experimental plan, the Six Sigma Black Belt should be able to find the correct number of replicates to obtain a desired power.

73.The Six Sigma Black Belt should know the difference between the various types of experimental models (fixed-effects, random-effects, mixed).

74.The Six Sigma Black Belt should understand the concepts of randomization and blocking.

75.Given a set of data, the Six Sigma Black Belt should be able to perform a Latin Square analysis and interpret the results.

76.Ditto for one way ANOVA, two way ANOVA (with and without replicates), full and fractional factorials, and response surface designs.

77.Given an appropriate experimental result, the Six Sigma Black Belt should be able to compute the direction of steepest ascent.

78.Given a set of variables each at two levels, the Six Sigma Black Belt can determine the correct experimental layout for a screening experiment using a saturated design.

79.Given data for such an experiment, the Six Sigma Black Belt can identify which main effects are significant and state the effect of these factors.

80.Given two or more sets of responses to categorical items (e.g., customer survey responses categorized as poor, fair, good, excellent), the Six Sigma Black Belt will be able to perform a Chi-Square test to determine if the samples are significantly different.

81.The Six Sigma Black Belt will understand the idea of confounding and be able to identify which two factor interactions are confounded with the significant main effects.

82.The Six Sigma Black Belt will be able to state the direction of steepest ascent from experimental data.

83.The Six Sigma Black Belt will understand fold over designs and be able to identify the fold over design that will clear a given alias.

84.The Six Sigma Black Belt will know how to augment a factorial design to create a composite or central composite design.

85.The Six Sigma Black Belt will be able to evaluate the diagnostics for an experiment.

86.The Six Sigma Black Belt will be able to identify the need for a transformation in y and to apply the correct transformation.

87.Given a response surface equation in quadratic form, the Six Sigma Black Belt will be able to compute the stationary point.

88.Given data (not graphics), the Six Sigma Black Belt will be able to determine if the stationary point is a maximum, minimum or saddle point.

89.The Six Sigma Black Belt will be able to use a quadratic loss function to compute the cost of a given process.

90.The Six Sigma Black Belt will be able to conduct simple and multiple linear regression.

91.The Six Sigma Black Belt will be able to identify patterns in residuals from an improper regression model and to apply the correct remedy.

92.The Six Sigma Black Belt will understand the difference between regression and correlation studies.

93.The Six Sigma Black Belt will be able to perform chi-square analysis of contingency tables.

94.The Six Sigma Black Belt will be able to compute basic reliability statistics (mtbf, availability, etc.).

95.Given the failure rates for given subsystems, the Six Sigma Black Belt will be able to use reliability apportionment to set mtbf goals.

96.The Six Sigma Black Belt will be able to compute the reliability of series, parallel, and series-parallel system configurations.

97.The Six Sigma Black Belt will demonstrate the ability to create and read an FMEA analysis.

98.The Six Sigma Black Belt will demonstrate the ability to create and read a fault tree.

99.Given distributions of strength and stress, the Six Sigma Black Belt will be able to compute the probability of failure.

100.The Six Sigma Black Belt will be able to apply statistical tolerancing to set tolerances for simple assemblies. He will know how to compare statistical tolerances to so-called "worst case" tolerancing.

101.The Six Sigma Black Belt will be aware of the limits of the Six Sigma approach.

source: http://www.pyzdek.com/101.htm



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