LSS SIX SIGMA EXAM 1

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Average of the raw data

Recorded values reflecting length, volume, and time

Measureable, Continuous, Variable

Distributions bounded at the left by zero

Lognormal, Weibull, and Exponential Distributions

5M and E version of the cause and effect diagram

Machine, Material, Method, Manpower, Measurement, and Environment

4M Version of the Cause and Effect Diagram

Machine, Material, Method, and Manpower

Continuous Probability Distributions

Normal, Log-normal, Exponential, Extreme Value, F, Student t, Chi-square, and Weibull

Project Scope

The boundaries of the project

Unintended Needs

The customer uses the product in an unintended manner

QFD

The desires of the customer and how to make a produce or process meet them; a customer driven process which is implemented by the organization; includes customer competitive assessment and technical results

Process Capability Analysis

The determination that the process can meet the product specifications as intended; Recognizing the nature of process variability the process capability target is usually tighter than product specifications

Bimodal

The distribution has two modes (two peaks on the curve).

Exponential

The distribution used to describe the time between failures which occur independently and at a constant rate. The mean and standard deviation are equal.

Market Segmentation

Targeted subsets of the market

Traceability

The accuracy of a measuring instrument linked to the U.S. National Standards.

Confidence Interval

A 90% confidence interval means that given the sample data, there is a 90% chance that the true population mean is contained in the interval. As sample size increases the width of the interval decreases.

Defector

A customer that has been lost

Terrorist

A customer who has turned against you and will spread ill-will regarding your company and product

Confidence interval for population variance

A function of n-1 based on the chi-square distribution

Balanced Scorecard

A method or process for managers to focus on business performance metrics, strategy management, financial metrics, stakeholder interests

Statistic

A number derived from sample data that describes the data in some useful way; Sample Value

Variables

A quality which can assume several (more than two) values

Perceptual Map

A specialized matrix diagram that captures the perceptions of a customer; items of customer importance vs customer's corresponding satisfaction level

Flowcharting

A tool frequently used in the audit. Can reveal wasted manpower or resources, excess handling, or extra processing. Can find holes, gaps, or weak areas in the control system; There can be multiple paths through the flowchart, there can only be a single process flow start point, flow charts can have parallel processes, a flow chart can have multiple end points; Asking why we do it this way, asking what would make it perfect, analyzing each step in detail, a comparison with processes different than your own

Customer Life Cycle

Acquisition, Retention, Attrition, Defection, and Reaquisition

Conformance

An affirmative indication that a product or service has met the requirements.

Ratio

An extension of the interval level that includes an inherent zero starting point. Data is interval data with a natural zero point. For example, time is ratio since 0 time is meaningful. Degrees Kelvin has a 0 point (absolute 0) and the steps in both these scales have the same degree of magnitude.

Sample Data

Any sample size if randomly selected can be suitable for audit purposes, since we are not directly performing lot acceptance or rejection; Coding and rounding affect both the mean and standard deviation

Checklists and Flowcharts

Basic quality tools most applicable for a work team to use when there is a desire to follow procedures and work instructions more closely

Hierarchy of Customer Expectations

Basic, Expected, Desired, Unanticipated

Tools that display the same data reads on a continuous scale

Boxplots, histograms, and stem and leaf plots

Fishbone (AKA Cause and Effect Session, AKA Ishikawa Diagram) Parts

Brainstorming, Prioritizing, Action plan development; problem statement is at far right; it takes time to perform and prioritize and it does not develop an action plan; Separate a problem into smaller components, show how various causes interact, display many possible causes in a graphical manner

Organization Chart

Can show organizational deficiencies

Team Membership

Composition of the Improvement Team

Truncated

Cut off in some way and is not normal

Purpose of Milestones

Keeping the project on track

Interval

Data is like ordinal except we can say the intervals between each value are equally split. The most common example is temperature in degrees Fahrenheit. The difference between 29 and 30 degrees is the same magnitude as the difference between 78 and 79. With attitudinal scales and the Likert questions you usually see on a survey, these are rarely interval, although many points on the scale likely are of equal intervals.

Variable Data

Data that are measured with some sort of instrument, such as a micrometer, tape measure, or watch.

Attribute data

Data that can be counted

Nominal

Data that consists of names or categories only. Basically refers to categorically discrete data such as name of your school, type of car you drive or name of a book. This one is easy to remember because nominal sounds like name (they have the same Latin root).

Ordinal

Data that is arranged in order (and differences between values cannot be determined or are meaningless). Refers to quantities that have a natural ordering. The ranking of favorite sports, the order of people's place in a line, the order of runners finishing a race or more often the choice on a rating scale from 1 to 5. You cannot state with certainty whether the intervals between each value are equal. For example, we often using rating scales (Likert questions). On a 10 point scale, the difference between a 9 and a 10 is not necessarily the same difference as the difference between a 6 and a 7. This is also an easy one to remember, ordinal sounds like order.

Problem Statement

Details the issue that the team wants to improve and a reference to the baseline measurement

Process Variation Establishment

Determined by examining the variation between part averages that are averaged among inspectors

Reproducibility

Determined by examining the variation between the average of the individual inspectors for all parts measured

Repeatability

Determined by examining the variation between the individual inspectors and within their measurement readings

Venn Diagram (AKA Set Diagram)

Diagrams that show all possible logical relations between a finite collection of sets (aggregation of things). Typically circles.

Histogram (Relative frequency chart or graph)

Displays the distribution of a sample (not a population), often the readings are grouped into uniform intervals

Scatter Diagram

Displays the relationship between variables; produces correlation coefficients

Process Shift

Due to rapid shifts in the process pattern being plotted. Events that could prompt such a change include a change in crew (machine settings) or a change in measuring device or method (not gradual tool wear or a reduction in defective level due to Kaizen techniques).

Calibration department duties

Ensuring traceability of all calibrations to a standard laboratory, maintaining and adequate record system, suspending measuring equipment from use when conditions warrant, identifying equipment with a label indicating calibration status

Recording Checksheets

Generally used for tally counts or attribute data, including machine, operator, characteristic, and so on; subjective data can be recorded on a checksheet; can record variable, attribute, and locational data

Accuracy

Getting an unbiased true value; The accuracy level of an instrument when compared to a standard can only be less than or equal to the standard to which it is compared

Precision

Getting consistent results repeatedly, the agreement or closeness of measurements on the same item

Stem and Leaf Plot

Graphical data method that can show the value of all individual readings

Cumulative Distribution Function

Graphical display of the total percentage of results below a certain measurement value

Discrete (attribute based) Distributions

Hypergeometric, binomial, and Poisson

Measles Charts

Identify locational data; useful to show visually where x occurs

Matrix (AKA Prioritization Matrix) Diagrams

Identify the impact that various process input variables could have on key process output variables

Benchmarking

Normally undertaken by a company or organization for the purpose of finding a leader in an area felt to be deficient, developing methods of measuring performance, and identifying gap between the present and desired performance; typically ignored because of the perceived barriers to sharing internal company information; Sequence: Understand your own processes, identify improvement criteria, measure competitive performance, and implement significant improvements

Skewed

Not symetrical and not normal

Checklists

Often used for attribute or counted information

Problem with Complaint Cards

Only 10% of the complaints are recorded

Parameter

Population value

Main disadvantage of presenting a team with an initial project lasting more than 160 days

Possibility that the team will expand the project boundaries

Normally distributed process

Predictable

Sensitivity

Reading to one decimal greater than the reported dimension; the ability to detect differences in measurement

Standardization

Reduces the nuber of characteristics or features of a system

R&R Study allows you to determine

Reproducibility, Process Variation, and Repeatability; can determine measurement error

Alpha Risk (AKA Type I)

Risk to reject a true hypothesis

Best approach when selecting quality measuring devices

Select those which integrate most efficiently with the entire quality system

Project Business Case

Short summary of strategic reasons for the project

Indicating Gage

Shows the amount of variation in size from the specification

House of Quality

Side walls = indicated by customer needs and customer competitive assessment; foundation = the technical competitive assessment; ceiling = design features

Focus Groups

Small groups with a specific topic

Cultural Needs

Status of the product (a BMW)

Total Defects Per Unit (TDPU) Formula

TDPU = -ln(RTY)

Capability

The long term performance level after a process has attained statistical control.

Weibull Scale Parameter

The point at which 63.21% of all values fall below

General term for the binomial distribution

The probability of occurrence of an event of interest (termed as a success) with n trials and with f failures, then the number of occurrences follows this type of distribution

Rolled Throughput Yield Calculation

The product of the yields of all process steps

Beta Risk (AKA Type II)

The risk of a hypothesis not being rejected when it is false. The risk when the null hypothesis is not rejected and it should be.

Coefficient of Variation

The standard deviation as a percent of the mean; = (Standard Deviation / Mean) * 100

Variance

The sum of the squared deviations of a group of measurements from their mean divided by the number of measurements

Master (AKA Reference Gage)

The working gage for accuracy prior to measuring the product

Random Selection

Theoretically means that each item in the lot had an equal chance to be selected

Process Management

Ties together the activities of a company

F distribution

To test for equality of variances from two normal populations

Business Process Management

Understanding, controlling and improving an organization's processes to create value for all stakeholders

Poisson Distribution

Used to model rates. The probability of exactly r events occuring can be computed using this (get a Poisson Table); has a mean equal to the variance; use ex: can tell you the # of defects per disk drive or the # of defects per automobile; widely used in queuing theory

Pareto Diagram

Used to prioritize problems

Process Mapping

Used to visualize the process being described, check current processes for duplication or redundancy (unnecessary complexity), and to assist in work simplification

Hypergeometric distribution

Used when there are two possible outcomes on each trial, but the probability of success on each trial differs because there is sampling without replacement; can model discrete data when the population size is small compared to sample size

Real Needs

What the customer really wants (transportation)

Perceived Needs

What the customer thinks is desired (a new car)

Stated Needs

What the customers say they want (a car)

Mode

measure of the central location for the nominal scale, a very low level statistic

Lifetime worth

the best measurement of the value of a customer

Cumulative Frequency Graph (AKA Ogive)

the frequencies are cumulative, each class frequency is added to the total of all previous class frequencies

t distribution

to compensate for error in the estimated standard deviation of small sample size

Chi-square distribution

to make decisions and construct confidence intervals by summing the square of normal random variables

Sampling plans for both inspection and auditing consider three things

validity, applicability, and known risks