14 Points

W. Edwards Deming’s 14 management practices to help organizations increase their quality and productivity: 1) Create constancy of purpose for improving products and services; 2) Adopt the new philosophy; 3) Cease dependence on inspection to achieve quality; 4) End the practice of awarding business on price alone; instead, minimize total cost by working with a single supplier; 5) Improve constantly and forever every process for planning, production and service; 6) Institute training on the job; 7) Adopt and institute leadership; 8) Drive out fear; 9) Break down barriers between staff areas; 10) Eliminate slogans, exhortations, and targets for the workforce; 11) Eliminate numerical quotas for the workforce and numerical goals for management; 12) Remove barriers that rob people of pride of workmanship and eliminate the annual rating or merit system; 13) Institute a rigorous program of education and self-improvement for everyone; and 14) Put everybody in the organization to work to accomplish the transformation.

A

Acceptance Number

The maximum number of defects or defectives allowed in a sample from a lot (batch) of product to consider that lot acceptable.

Acceptance Quality Limit (AQL)

Also known as Acceptable Quality Limit, Acceptance Quality Level, Acceptable Quality Level, or AQL level.

The AQL is the lowest tolerable average (mean) of a process in percentage or ratio that is still considered acceptable.

Acceptance Sampling

A method of inspection in which statistical sampling of a lot (batch) of product is used to determine whether that lot of product is acceptable. Acceptance sampling comprises two types: attribute sampling and variable sampling.

Attribute sampling is a statistical method by which the lot is accepted or rejected based on one sample. The sample is recorded as a pass or fail depending on the number of defects or defectives found within that sample when compared to the Acceptance Number. Attribute inspections are typically subjective (visual) interpretations of the product.
Variable sampling is similar to attribute sampling. However, rather than recording the number of defects, each piece within the sample from the lot of product is measured and those values are assessed against a specification limit. The result of that assessment may indicate the lot passes or fails. Sample sizes for variable sampling are usually smaller than attribute sampling because measurements are more accurate than subjective interpretation.

Acceptance Sampling Plan

The specific criteria by which a product is to be examined for acceptance utilizing Acceptance Sampling methods. The size of the lot (batch) of product combined with the Acceptance Quality Limit, as well as other considerations (depending on the plan being used and the characteristics being inspected), determine the sample size as well as the acceptance number. Some of the most commonly used standards today are ANSI/ASQ z1.4 (Attributes), ANSI/ASQ z1.9 (Variables), Lot Tolerance Percent Defective (LTPD), and Zero Acceptance Number (as described by Nicholas Squeglia in Zero Acceptance Number Sampling Plans, ASQC Quality Press).

Accuracy

The difference of agreement between an observed value and an accepted reference value.

Alpha value

The risk of being wrong when completing a hypothesis test.

The chi-square table is computed in such as way that if the assumption of “normal data” is true for a given X-bar and sigma, the results of the chi-square test will be incorrectly rejected only 5% of the time. This calculation reflects the alpha value.

Analysis of Means (ANOM)

A statistical procedure for troubleshooting industrial processes and analyzing the results of experimental designs with factors at fixed levels. When you need to compare multiple group means, you can use the ANOM as an alternative to the one-way analysis of variance F.

Analysis of Variance (ANOVA)

Also known as Variance Analysis, ANOVA Variance, ANOVA Analysis.

A basic statistical technique for determining the proportion of influence that a factor, or set of factors, has on total variation. ANOVA tests for differences between means; it’s similar to many other tests and experiments in that its purpose is to determine whether the response variable (i.e., your dependent variable) is changed by manipulating the independent variable.

AS9100

Also known as AS9100 Standard and AS9100 Quality.

A widely adopted and standardized quality management system for the aerospace industry. It is known as EN9100 in Europe and JISQ9100 in Japan.

Assignable cause

An assignable cause is a source of variation that is intermittent, not predictable. It is sometimes called “special cause” variation. On a control chart, an assignable cause is signaled by points beyond the control limits or nonrandom patterns within the control limits.

Attribute Data

Also known as Go/No-Go information.

Qualitative data that can be counted for recording and analysis. Control charts based on attribute data include: percent chart, number of affected units chart, count chart, count-per-unit chart, quality score chart, and demerit chart. Also see Go/No-Go.

Attributes data

Attributes data is data that can be classified and counted. There are two types of attributes data: counts of defects per item or group of items (nonconformities) and counts of defective items (nonconforming). For example, yes/no, good/bad, pass/fail, and go/no go.

Average

Another term for a mean, it is an indicator of the center of a set of data points. It is found by adding all the individual values and dividing by the number of values.

B

Average Outgoing Quality (AOQ)

Also known as Average Outgoing Quality Formula.

The expected average quality level of an outgoing product for a given value of incoming product quality. Depends on the incoming quality, the probability that the lot will be accepted, and the sample and lot sizes.

Average Outgoing Quality Limit (AOQL)

Represents the maximum percent defective in the outgoing product. AOQL is the maximum average outgoing quality over all possible levels of incoming quality for a given acceptance sampling plan and disposal specification.

Average Run Lengths (ARL)

The number of points, on average, that will be plotted on a control chart before an out-of-control condition is indicated (e.g., a point plotting outside the control limits).

Averages Chart

Also known as Averages Control Chart.

A control chart in which the subgroup average, X-bar, is used to evaluate the stability of the process level. Also see X-Bar Chart.

B

Bell curve

Another term for the shape formed by a normal distribution when drawn as a histogram.

Bias

Something that influences the selection of certain items when collecting a sample.

Bimodal distribution

A distribution that has two modes. Drawn as a histogram, this condition is reflected by two peaks or high points.

C

Binomial Distribution

Also known as Binomial Distribution Formula.

A discrete probability distribution used for counting the number of successes and failures or conforming and nonconforming units. This distribution underlies the p-chart and the np-chart.

Blemish

An imperfection severe enough to be noticed but that should not cause any real impairment with respect to the intended normal, or reasonably foreseeable, use. Also see Defect, Imperfection, and Nonconformity.

Box and Whisker Plot

A plot used in exploratory data analysis to picture the centering and variation of the data based on quartiles. After the data are ordered, the 25th, 50th, and 75th percentiles are identified. The box contains the data between the 25th and 75th percentiles.

C

c-chart

An attributes control chart that is used to monitor the number of nonconformities, such as defects per subgroup. The subgroup size must remain constant for this type of chart.

Calibration

The comparison of a measurement instrument or system of unverified accuracy to a measurement instrument or system of known accuracy to detect any variation from the required performance specification.

Capability

The capability of a process is how the process performs when compared to specification limits or requirements. It uses a series of indices: Cp, Cpk, Cr, and Cpm.

Capability analysis

A set of statistical calculations performed on a set of data to assess how the distribution formed by the data compares to specifications or requirements.

Capable process

A process is said to be capable if nearly 100% of its output falls within specification limits.

Cause

An identified reason for the presence of a defect or problem.

Cause-and-Effect Diagram

Also called a fishbone diagram or an Ishikawa diagram (after its developer).

A quality control tool used to analyze potential causes of problems in a product or process.

Centerline

A line on a graph that represents the overall average (mean) operating level of the process.

Central Limit Theorem

Also known as Central Limit Theorem Formula.

An important statistical theorem that states that subgroup averages tend to be normally distributed even if the output overall is not. This concept allows control charts to be widely used for process control even if the underlying process is not normally distributed.

Central location

Central location is the center of a set of data points. Mean, median, and mode are the statistics used to describe it.

Central Tendency

Also known as Measures of Central Tendency.

The tendency of data gathered from a process to cluster toward a middle value somewhere between the high and low values of measurement.

Characteristic

A factor, element, or measure that defines and differentiates a process, function, product, service, or other entity.

Chart

A tool for organizing, summarizing, and depicting data in graphic form.

Check Sheet

A simple data recording device. The check sheet is custom-designed by the user, which allows him or her to readily interpret the results.

Chi-square

A goodness-of-fit-test statistic used to test the assumption that the distribution of a set of data is similar to the expected distribution, such as a normal distribution.

Classification of Defects

The listing of possible defects of a unit, classified according to their level of severity. Commonly used classifications include: A, B, C, or D; critical, major, minor, or incidental; and critical, major, or minor. A separate acceptance sampling plan is generally applied to each class of defects.

Coefficient of variance

A ratio that measures the significance of the standard deviation in relation to the mean.

Common cause

A source of variation that is inherent in a system and is predictable. A control chart identifies a system with only common causes of variation. Common causes of variation affect all individual values of a system, and can be eliminated only by a systemic change.

Consumer’s Risk

Pertains to sampling and the potential risk that bad products will be accepted and shipped to the consumer.

Continuous Flow Process

A method of manufacturing that aims to move a single unit in each step of a process, rather than treating units as batches for each step.

Continuous Improvement (CI)

Also known as Continuous Quality Improvement and Continual Improvement.

The ongoing improvement of products, services, or processes through incremental (over time) and/or breakthrough (all at once) improvements.

Continuous Sampling

Used when the product is manufactured in a continuous flow and is not able to be grouped into lots (batches). Two parameters are considered: Frequency (f) and Clearing Number (i). This is a progressive type of plan in which the Clearing Number is X (example = 60) and the frequency is 1/X (example = 1/20). The manufacturer inspects 100 percent of the product until (i)=60 is reached. If defect-free, the Frequency (example = 1/20) applies and now every (f)=20th sample is inspected. If at least one defect is found in the first (i)=60, 100-percent inspection continues until the Clearing Number is reached.

Control chart

A control chart is a graphical representation of a characteristic of a process, showing plotted values of some statistic, a central line, and one or two control limits. It is used to determine whether a process has been operating in statistical control and is an aid to maintaining statistical control.

Control Limit

Also known as Process Control Limit and Natural Process Limit.

The boundaries of a process within specified confidence levels expressed as the Upper Control Limit (UCL) and the Lower Control Limit (LCL).

Control limits

Lines on a control chart used as a basis for judging whether variation in data on a chart is due to special or common causes. These limits are calculated from data collected from the system, they are not specifications or limits set by customers or management.

Control Plan (CP)

Written descriptions of the systems for controlling part and process quality by addressing the key characteristics and engineering requirements.

Corrective Action

A solution meant to reduce or eliminate an identified problem.

Correlation (Statistical)

A measure of the relationship between two data sets of variables.

Cost of Quality (COQ)

A means to quantify the total cost of quality-related efforts and deficiencies. Considered by some to be synonymous with COPQ.

Costs of Poor Quality (COPQ)

The costs that would disappear if systems, processes, and products were perfect. These costs are organized into four categories: internal failure costs (costs associated with defects found before the customer receives the product or service); external failure costs (costs associated with defects found after the customer receives the product or service); appraisal costs (costs incurred to determine the degree of conformance to quality requirements); and prevention costs (costs incurred to keep failure and appraisal costs to a minimum).

Count Chart

A Control Chart for evaluating the stability of a process in terms of the count of events of a given classification occurring in a sample. Commonly referred to as a c-chart.

Count Data

See Attribute Data.

Count-Per-Unit Chart

Also known as a u-chart.

A type of control chart used to monitor count-type data where the sample size is greater than one, typically the average number of nonconformities per unit.

Cp

A capability index that compares the width of a two-sided specification with the variation in the process. Estimated standard deviation is used to calculate the process variation. A Cp larger than 1 indicates that the process variation is narrower than the specification.

Cpk

Cpk is a capability index that tells how well a system can meet two-sided specification limits. Because it takes the target value into account, the system does not have to be centered on the target value for this index to be useful. It is calculated with estimated standard deviation. A Cpk greater than 1 indicates that the process can meet the specification.

Cpk Index

Also known as Process Capability Index.

Equals the lesser of the Upper Specification Limit minus the mean divided by 3 sigma or the mean minus the Lower Specification Limit divided by 3 sigma. The greater the Cpk value, the better.

Cpl

A capability index that compares the variation in the process to the lower specification. Estimated standard deviation is used to calculate the process variation. A Cpl greater than 1 indicates the process is capable of meeting the lower specification.

Cpm

Cpm is a capability index that shows how well the system can produce output within specifications while taking the target into account. Its calculation uses sigma calculated from the target value instead of the mean.

Cpu

A capability index that compares the variation in the process to the upper specification. Estimated standard deviation is used to calculate the process variation. A Cpu greater than 1 indicates the process is capable of meeting the upper specification.

Cr

Capability ratio compares the variation in a process with the width of a two-sided specification. Estimated standard deviation is used to calculate the process variation. It is the inverse of Cp.

D

Cumulative Sum Control Chart (CUSUM)

A type of control chart used to monitor small shifts in the process mean. It uses the cumulative sum of deviations from a target.

D

Data

Collected facts.
There are two basic kinds of numerical data: measured or variable data (such as 12 ounces, 10 miles, and 0.50 inches) and counted (or attribute) data (such as 112 defects).

Data Collection and Analysis

The process to determine what data are to be collected, how the data are collected, and how the data are to be analyzed.

Data Collection and Analysis Tools

A set of tools that help with data collection and analysis. These tools include check sheets, spreadsheets, histograms, trend charts, and control charts.

Defect

A product’s or service’s nonfulfillment of an intended requirement or reasonable expectation for use, including safety considerations. There are four classes of defects: Class 1, very serious, leads directly to severe injury or catastrophic economic loss; Class 2, serious, leads directly to significant injury or significant economic loss; Class 3, major, is related to major problems with respect to intended normal or reasonably foreseeable use; and Class 4, minor, is related to minor problems with respect to intended normal or reasonably foreseeable use. Also see Blemish, Imperfection, and Nonconformity.

Defective

A unit of product that contains one or more quality characteristic defects.

Deming Cycle

Also known as the Plan-Do-Study-Act cycle, popularized by W. Edwards Deming.
Also see Plan-Do-Check-Act Cycle.

Deviation

The difference or distance of an individual observation or data value from the center point (often the mean) of the set distribution.

Discrimination

This refers to a description of the capability of a measurement system.

Dispersion

Statistics such as the range and standard deviation (sigma) are said to be measures of dispersion.

Distribution

Distribution is a way of describing the output from a system of variation. The distribution’s location, shape, and spread may be evaluated by statistics such as the mean, median, sigma, and range.

E

DMAIC

Also known as Six Sigma DMAIC.
Define, Measure, Analyze, Improve, and Control. A data-driven quality strategy for improving processes, and an integral part of a Six Sigma quality initiative.

E

Estimated sigma

This is an estimate of the standard deviation calculated by dividing the average range by the tabular constant d2 (R-bar/d2).

H

EWMA Charts

Also known as EWMA Control Charts.
An Exponentially Weighted Moving Average control chart uses current and historical data to detect small changes in the process. Typically, the most recent data are given the most weight, and progressively smaller weights are given to older data.

F

F Distribution

The F distribution is the probability distribution associated with the F statistic.

F Statistic

An F statistic is a value you get when you run an Analysis of Variance (ANOVA) test or a regression analysis to find out whether the means between two populations are significantly different.

Failure

The inability of an item, product, or service to perform required functions on demand due to one or more defects.

Feature

See Characteristic.

First Pass Yield (FPY)

Also referred to as the quality rate.
The percentage of units that completes a process and meets quality guidelines without being scrapped, rerun, retested, returned, or diverted into an offline repair area. Calculated by dividing the units entering the process minus the defective units by the total number of units entering the process.

First Time Quality (FTQ)

Also known as First Time Quality Formula.
Calculation of the percentage of good parts at the beginning of a production run.

Fitness for Use

The degree to which a product or service meets the requirements for its intended use.

Frequency Distribution (Statistical)

A list, table, or graph that displays the frequency of various outcomes in a sample.

G

Gauge Repeatability and Reproducibility (R&R)

A gauge R&R indicates whether the inspectors are consistent in their measurements of the same part (repeatability) and whether the variation between inspectors is consistent (reproducibility).

Repeatability—How much variability in the measurement system is caused by the measurement device.
Reproducibility—How much variability in the measurement system is caused by differences between operators.
Whether your measurement system variability is small compared with the process variability.
Whether your measurement system is capable of distinguishing between different parts.

Geometric Dimensioning and Tolerancing (GD&T)

A language of symbols and standards designed and used by engineers and manufacturers to describe a product and facilitate communication between entities working together to produce something.

Go/No-Go

State of a unit or product. Two parameters are possible: Go (conforms to specifications) and No-Go (does not conform to specifications).

Green Belt (GB)

See Six Sigma Green Belt.

H

Histogram

A histogram is a bar chart that represents the frequency distribution of data. The height of each bar corresponds to the number of items in the class or cell. The width of each bar represents a measurement interval. The histogram shows basic information such as central location, shape, and spread of the data being examined.

I

In control

A process is said to be “in control” or “stable” if it is in statistical control. If a process is in statistical control, a control chart will have no subgroups falling outside the control limits, no runs, and no nonrandom patterns.

Individuals control chart

The individual portion of an X-MR control chart. The individual data points are plotted onto the chart and compared with control limits.

Hypothesis Testing

A procedure that is used on a sample from a population to investigate the applicability of an assertion (inference) to the entire population. Hypothesis testing can also be used to test assertions about multiple populations using multiple samples.

I

Imperfection

A quality characteristic’s departure from its intended level or state without any association to conformance to specification, requirements, or to the usability of a product or service. Also see Blemish, Defect, and Nonconformity.

In control

In-Control Process

A process in which the statistical measure being evaluated is in a state of statistical control; in other words, the variations among the observed sampling results can be attributed to a constant system of chance causes. Also see Out-of-Control Process.

Individual

A single unit or a single measurement of a quality characteristic, usually denoted as X. This measurement is analyzed using an Individuals Chart, CUSUM, or EWMA chart.

Individuals Chart

Also called an I-chart or X-chart.
A control chart for processes in which individual measurements of the process are plotted for analysis.

Individuals control chart

The individual portion of an X-MR control chart. The individual data points are plotted onto the chart and compared with control limits.

K

Inspection

A verification activity.
For example, measuring, examining, testing, and gauging one or more characteristics of a product or service and comparing the results with specified requirements to determine whether conformity is achieved for each characteristic.

Inspection Cost

The cost associated with inspecting a product to ensure it meets the internal or external customer’s needs and requirements; an appraisal cost.

Inspection Lot

This is the lot or batch of product to be inspected for acceptance.

Inspection States

>In the ANSI/ASQ and ISO Acceptance Sampling Standards there are three Inspection States (or statuses): Normal, Tightened, and Reduced. The definitions for each state are found in the applicable standard under a heading called Switching Rules.

Normal: Per the ANSI/ASQ z1.4, “Normal inspection will be used at the start of inspection unless otherwise directed by the responsible authority.”
Normal to Tightened: Per the ANSI/ASQ z1.4, “When Normal inspection is in effect, tightened inspection shall be instituted when 2 out of 5 or fewer consecutive lots or batches have been non-acceptable on original inspection.”
Tightened to Normal: Per the ANSI/ASQ z1.4, “When tightened inspection is in effect, normal inspection shall be instituted when 5 consecutive lots or batches have been considered acceptable on original inspection.”
Normal to Reduced: This switching rule requires several different things to happen. When normal inspection is in effect and the following apply, the state may change to Reduced if:

The preceding 10 lots or batches (or more) have all been accepted on original inspection
The total number of nonconforming units in the samples from those 10 preceding lots is equal to or less than the applicable limit number given (depending on the standard)
Production is at a steady rate
Reduced inspection is desired by responsible authority

International Organization for Standardization (ISO)

An independent, nongovernmental international organization with a membership of 161 national standards bodies that unites experts to share knowledge and develop voluntary, consensus-based, market-relevant international standards, guidelines, and other types of documents.

ISO 9000 Series Standards

A set of international standards on quality management and quality assurance developed to help organizations effectively document the quality system elements to be implemented to maintain an efficient quality system. The standards, initially published in 1987, are not specific to any particular industry, product, or service. The standards were developed by the International Organization for Standardization (ISO). The standards underwent major revision in 2000 and now include ISO 9000:2005 (definitions), ISO 9001:2008 (requirements), ISO 9004:2009 (continuous improvement) and ISO 9001: 2015 (risk management).

ISO 9001

A voluntary quality management system standard developed by the International Organization for Standardization (ISO). First released in 1987 and one of several documents in the ISO 9000 family.

J

Just-In-Time Manufacturing (JIT)

Also known as Just-In-Time Production.
A methodology aimed primarily at reducing flow times within a production system, as well as response times from suppliers and to customers.

K

Key Process Characteristic

A process parameter that can affect safety or compliance with regulations, fit, function, performance or subsequent processing of product.

Key Product Characteristic

A product characteristic that can affect safety or compliance with regulations, fit, function, performance or subsequent processing of product.

Kruskal-Wallis Test

A non-parametric test for determining whether samples originate from the same distribution. It is used for comparing two or more independent samples of equal or different sample sizes. While analysis of variance tests depends on the assumption that all populations under comparison are normally distributed, the Kruskal-Wallis test places no such restriction on the comparison. It is a logical extension of the Wilcoxon Mann-Whitney Test.

Kurtosis

Kurtosis is a statistic that is used to measure the “flatness” or “peakedness” of a set a of data. It represents a measure of the combined weight of the tails relative to the rest of a distribution. As the tails of a distribution become heavier, the kurtosis will increase. As the tails become lighter, the kurtosis value will decrease.

L

Lot

Also known as a Batch.

A defined quantity of product accumulated under conditions considered uniform for sampling purposes.
Items constituting a defined quantity of uniform product for purposes of proceeding collectively through a process.

Lot Quality

The value of percentage defective or defects per hundred units in a lot.

Lot Size

Also referred to as N.

The number of units in a lot.

Lot Tolerance Percentage Defective (LTPD)

Expressed in percentage defective, the poorest quality in an individual lot that should be accepted.

Note: LTPD is used as a basis for some inspection systems and is commonly associated with a small consumer risk.

Lower control limit

A line on a control chart used as a basis for judging whether variation from the data on the chart is due to special or common causes. Any point beyond the lower control limit is an indication of a special cause occurring. This limit is calculated from data collected on the system, it is not a specification or limit set by customers or management. The symbol is LCL.

Lower Control Limit (LCL)

Control limit for points below the central line in a Control Chart.

Lower specification limit

The lower limit of a specification. This limit is set as an aim for a system or process, it is usually set by the customer of the process, engineering, or management. The symbol for the lower specification is LSL – lower specification limit.

M

Maximum acceptable subgroup size

When a varying sample size is being used in a p or u-control chart, the maximum acceptable sample size is usually a sample size that is twenty-five percent larger than the average sample size. Any subgroup with a sample size larger than the maximum acceptable subgroup size has to have control limits calculated specifically for that subgroup.

Mean

Another term for average, it is an indicator of the central location of a set of data. It is found by adding all the individual values and dividing by the number of values.

Measure

The criteria, metric, or means to which a comparison is made with output.

Measurement

The act or process of determining a value. An approximation or estimate of the value of the specific quantity subject to measurement, which is complete only when accompanied by a quantitative statement of its uncertainty.

Measurement System

All operations, procedures, devices, and other equipment, personnel and environment used to assign a value to the characteristic being measured.

Measurement Uncertainty

In metrology, a non-negative parameter characterizing the dispersion of the values attributed to a measured quantity.

Median

The middle number in a set of data when it is ranked from lowest to highest, it is an indicator of central location in a data set.

Minimum acceptable subgroup size

When a varying sample size is being used in a p or u-control chart, the minimum acceptable sample size is usually a sample size that is twenty-five percent smaller than the average sample size. Any subgroup with a sample size smaller than the minimum acceptable subgroup size has to have control limits calculated specifically for that subgroup.

Mode

Is the number that occurs most frequently in a data set. It is usually an indicator of central location.

Moving Range

A measure used to help calculate the variance of a data population; the distance or difference between consecutive points. The moving range chart is typically used with an Individual X (IX) chart for single measurements.

Moving range chart

The moving range portion of an individuals and moving range control chart. The moving ranges are plotted on the chart and compared with control limits.

N

Moving Sigma

A measure used to calculate variation using the standard deviation between two consecutive points from an IX control chart. The calculations are then plotted and analyzed on a time-ordered Moving-s control chart.

Multivariate Control Chart

A control chart for evaluating the stability of a process in terms of the levels of two or more variables or characteristics.

N

Negatively skewed distribution

A distribution of data where most of the data appears on the right hand side of the distribution and then tails off to the left. Also known as a skewed left distribution.

Nonconforming

Nonconforming data is a count of defective units. It is often described as go/no go, pass/fail, or yes/no, since there are only two possible outcomes to any given check. You can track either the number of defective units or the number of nondefective units.

Nonconforming Unit

A unit with one or more nonconformities or defects. Also called a reject.

Nonconformities

Nonconformities data is a count of defects per unit or group of units. It can refer to defects or occurrences that should not be present but are, or any characteristic that should be present but is not.

Nonconformity

A specified requirement that is not fulfilled. Also see Blemish, Defect, and Imperfection.

Nondestructive Testing and Evaluation (NDT, NDE)

Testing and evaluation methods that do not damage or destroy the test specimen.

Nonnormal data

Data that does not form a normal distribution.

Nonnormal data distribution

Any data set that does not show a normal, bell-shaped distribution.

Nonparametric Tests

All tests involving ranked data (data that can be put in order). Nonparametric tests are often used in place of their parametric counterparts when certain assumptions about the underlying population are questionable.

Nonrandom pattern

A pattern in data that is repeating, or is not due to normal variation.

Normal curve

This bell-shaped curve is used to illustrate the shape of a normal distribution.

Normal distribution

A data distribution that is bell shaped and symmetrical, the normal distribution is the basis for control chart and capability analysis.

Normal Distribution (statistical)

The charting of a data set in which most of the data points are concentrated around the average (mean), thus forming a bell-shaped curve.

Normal probability plot

A normal probability plot is a graphical method for showing a frequency distribution. The scaling is set up so that if the distribution is normal, a straight line will result.

np-chart

An attributes control chart that plots the number of items that are defective or possess a characteristic of interest. The subgroup size must remain constant for this type of chart to be used.

O

Observation

An observation is a single piece of data, usually a count or a measurement. It is also known as a reading.

Operating Characteristic Curve (OC curve)

Also known as Operating Curve.

A graph to determine the probability of accepting lots as a function of the lots’ or processes’ quality level when using various sampling plans. There are three types: type A curves, which give the probability of acceptance for an individual lot coming from finite production (will not continue in the future); type B curves, which give the probability of acceptance for lots coming from a continuous process; and type C curves, which (for a continuous sampling plan) give the long-run percentage of product accepted during the sampling phase.

Operational definition

When applied to data collection, it is a clear, concise, and detailed definition of a measure. It ensures that those collecting data do so consistently.

Out-of-control

When applied to a control chart, out of control means that at least one special cause of variation is present.

Out-of-Control Process

A process in which the statistical measure being evaluated is not in a state of statistical control. In other words, the variations among the observed sampling results cannot be attributed to a constant system of chance causes. Also see In-Control Process.

Out-of-Spec

A term that indicates a unit does not meet a given requirement or specification.

Outlier

An outlier is a point on a chart that does not fall into the pattern of the rest of the data.

Outliers

Unusually large or small observations relative to the rest of the data.

Over Control

An element often introduced into a process by a well-meaning operator or controller who considers any appreciable deviation from the target value as a special cause. In this case, the operator is incorrectly viewing common-cause variation as a fault in the process. Over control of a process can actually increase the variability of the process and is viewed as a form of tampering.

Overall Equipment Effectiveness (OEE)

Used to measure manufacturing productivity; identifies the percentage of manufacturing time that is truly productive. An OEE score of 100% means you are manufacturing only Good Parts, as fast as possible, with no Stop Time. In the language of OEE that means 100% Quality (only Good Parts), 100% Performance (as fast as possible), and 100% Availability (no Stop Time).

Overcontrol

Over reaction to a set of data. For example, in a control chart, it would be reacting to a common cause as if it were a special cause.

P

p-chart

An attributes control chart that plots the number of items possessing a characteristic of interest. The subgroup size may vary.

Pareto Chart

Also known as the 80-20 rule.

A graphical tool for ranking causes from most significant to least significant. It is based on the Pareto principle, named after 19th century economist Vilfredo Pareto, and suggests that most effects come from relatively few causes; that is, 80% of the effects come from 20% of the possible causes.

Parts Per Million (PPM)

A metric reporting the number of defects normalized to a population of one million for ease of comparison.

Parts per Thousand (PPT)

A ratio often used to refer to the concentration of solutes in solutions, such as salts in water (i.e., salinity).

Percent Chart

Also referred to as a proportion chart.

A control chart for evaluating the stability of a process in terms of the percentage of the total number of units in a sample in which an event of a given classification occurs.

Percentiles

Percentiles divide the ordered data into 100 equal groups. The kth percentile pk is a value such that at least k% of the observations are at or below this value and (100-k)% of the observations are at or above this value.

Plan-Do-Check-Act (PDCA) Cycle

Also known as PDCA Model.

A four-step process for quality improvement. In the first step (plan), a way to effect improvement is developed. In the second step (do), the plan is carried out. In the third step (check), a study takes place between what was predicted and what was observed in the previous step. In the last step (act), action should be taken to correct or improve the process.

Poisson Distribution

A discrete probability distribution that expresses the probability of a number of events occurring in a fixed time period if these events occur with a known average rate and are independent of the time since the last event.

Positively skewed distribution

A distribution of data where most of the data appears on the left hand side of the distribution and then tails off to the right. Also known as a skewed right distribution.

Pp

Pp is a capability index, similar to Cp, that is a measure of process performance. Pp tells how well a system can meet two-sided specification limits, assuming that the average is centered on the target value. It is calculated with the actual sigma (using the actual individual values) rather than the estimated sigma. A Pp larger than 1 indicates that the process variation is narrower than the specification.

Ppk

Similar to Cpk, Ppk is a capability index that indicates whether a process is capable of meeting two-sided specification limits. However, Ppk uses actual standard deviation to calculate the process variation, whereas Cpk uses an estimated standard deviation. The target value is taken into account with Ppk, so the system does not have be center on the target value to be useful. A Ppk greater than 1 indicates that the process can meet the specification.

Ppl

A capability index similar to Cpl in that it compares the variation in the process to the lower specification. However, Ppl uses standard deviation to calculate the process variation, whereas Cpl uses an estimated standard deviation. A Ppl greater than 1 indicates the process is capable of meeting the lower specification.

Ppu

A capability index similar to Cpu in that it compares the variation in the process to the upper specification. However, Ppu uses standard deviation to calculate the process variation, whereas Cpu uses an estimated standard deviation. A Ppu greater than 1 indicates the process is capable of meeting the upper specification.

Pr

A capability ratio similar to Cr in that it compares the variation in a process with the width of a two-sided specification. However, Pr uses standard deviation to calculate the process variation, whereas Cr uses an estimated standard deviation. It is the inverse of Pp.

Precision

The amount of variation that exists in the values of multiple measurements of the same characteristic or parameter. Greater precision means less variation between measurements.

Probability (statistical)

The likelihood of occurrence of an event, action, or item.

Process

A process is the combination of people, equipment, materials, methods, and environment that produce output—a given product or service. The words process and system are often used interchangeably.

Process Average Quality

Expected or average value of process quality.

Process capability

Process capability is the 6 sigma range of common cause variation for statistically stable processes only. Sigma is usually estimated by R-bar/d2.

Process Capability Index

The value of the tolerance specified for the characteristic divided by the process capability. The several types of process capability indexes include the widely used Cpk and Cp.

Process Control

The method for ensuring that a process meets specified requirements.

Process Improvement

Actions taken to increase the effectiveness or efficiency of a process in meeting specified requirements.

Process performance

The process performance is the 6 sigma range of inherent variation for statistically stable processes only, where sigma is usually estimated by the sample standard deviation.

R

Proportion Chart

See Percent Chart.

Q

Quality

A subjective term for which each person or sector has its own definition. In technical usage, quality can have two meanings: 1) the characteristics of a product or service that bear on its ability to satisfy stated or implied needs; 2) a product or service free of deficiencies. According to Joseph Juran, quality means “fitness for use;” according to Philip Crosby, it means “conformance to requirements.”

Quality Assurance/Quality Control (QA/QC)

Quality assurance is all the planned and systematic activities implemented within the quality system that can be demonstrated to provide confidence that a product or service will fulfill requirements for quality. Quality control is comprised of the operational techniques and activities used to fulfill requirements for quality. Quality Assurance and Quality Control are often used interchangeably, referring to the actions performed to ensure the quality of a product, service, or process.

Quality Management System Glossary

Every manufacturing quality management professional who uses statistical process control (SPC) runs into questions occasionally. That’s why we’ve compiled this SPC glossary to serve as a quick reference when you’re looking for an answer, need to explain a concept to a colleague—or just can’t remember that term that’s on the tip of your tongue.

Feel free to bookmark this reference so you always have the definition you’re looking for—and be sure to visit our other SPC reference resources.

WHAT IS STATISTICAL PROCESS CONTROL?
Learn the definition of SPC and what this industry-standard methodology is used for.

SPC 101
Dig in deeper to understand why and how SPC is used in manufacturing quality control.

DEFINITIVE GUIDE TO SPC CHARTS
Learn why and how to use different control charts, see examples, and explore use cases.

Quality Management System Glossary: A-B

A

Acceptance Number

The maximum number of defects or defectives allowed in a sample from a lot (batch) of product to consider that lot acceptable.

Acceptance Quality Limit (AQL)

Also known as Acceptable Quality Limit, Acceptance Quality Level, Acceptable Quality Level, or AQL level.

The AQL is the lowest tolerable average (mean) of a process in percentage or ratio that is still considered acceptable.

Acceptance Sampling

Attribute sampling is a statistical method by which the lot is accepted or rejected based on one sample. The sample is recorded as a pass or fail depending on the number of defects or defectives found within that sample when compared to the Acceptance Number. Attribute inspections are typically subjective (visual) interpretations of the product.
Variable sampling is similar to attribute sampling. However, rather than recording the number of defects, each piece within the sample from the lot of product is measured and those values are assessed against a specification limit. The result of that assessment may indicate the lot passes or fails. Sample sizes for variable sampling are usually smaller than attribute sampling because measurements are more accurate than subjective interpretation.

Acceptance Sampling Plan

Accuracy

The difference of agreement between an observed value and an accepted reference value.

Analysis of Means (ANOM)

Analysis of Variance (ANOVA)

Also known as Variance Analysis, ANOVA Variance, ANOVA Analysis.

AS9100

Also known as AS9100 Standard and AS9100 Quality.

A widely adopted and standardized quality management system for the aerospace industry. It is known as EN9100 in Europe and JISQ9100 in Japan.

Assignable Cause

Also known as Assignable Cause Variation.

An identifiable, specific cause of variation in a given process or measurement. Also see Special Cause.

Attribute Data

Also known as Go/No-Go information.

Average

See Mean.

Averages Chart

Also known as Averages Control Chart.

A control chart in which the subgroup average, X-bar, is used to evaluate the stability of the process level. Also see X-Bar Chart.

Average Outgoing Quality (AOQ)

Also known as Average Outgoing Quality Formula.

Average Outgoing Quality Limit (AOQL)

Average Run Lengths (ARL)

The number of points, on average, that will be plotted on a control chart before an out-of-control condition is indicated (e.g., a point plotting outside the control limits).

B

Blemish

Bias

The offset of a measured value from the true population value.

Binomial Distribution

Also known as Binomial Distribution Formula.

A discrete probability distribution used for counting the number of successes and failures or conforming and nonconforming units. This distribution underlies the p-chart and the np-chart.

Box and Whisker Plot

Quality Management System Glossary: C

Calibration

Capability

The total range of inherent variation in a stable process; determined by using data from control charts.

Cause

An identified reason for the presence of a defect or problem.

Cause-and-Effect Diagram

Also called a fishbone diagram or an Ishikawa diagram (after its developer).

A quality control tool used to analyze potential causes of problems in a product or process.

C-Chart

See Count Chart.

Centerline

A line on a graph that represents the overall average (mean) operating level of the process.

Central Limit Theorem

Also known as Central Limit Theorem Formula.

Central Tendency

Also known as Measures of Central Tendency.

The tendency of data gathered from a process to cluster toward a middle value somewhere between the high and low values of measurement.

Characteristic

A factor, element, or measure that defines and differentiates a process, function, product, service, or other entity.

Chart

A tool for organizing, summarizing, and depicting data in graphic form.

Check Sheet

A simple data recording device. The check sheet is custom-designed by the user, which allows him or her to readily interpret the results.

Classification of Defects

Common Cause

Cause of variation that is inherent in a process over time. A common cause affects every outcome of the process and everyone working in the process. Also see Special Cause.

Consumer’s Risk

Pertains to sampling and the potential risk that bad products will be accepted and shipped to the consumer.

Continuous Flow Process

A method of manufacturing that aims to move a single unit in each step of a process, rather than treating units as batches for each step.

Continuous Improvement (CI)

Also known as Continuous Quality Improvement and Continual Improvement.

The ongoing improvement of products, services, or processes through incremental (over time) and/or breakthrough (all at once) improvements.

Continuous Sampling

Control Chart

A graph used to study how a process changes over time. Frequently shows a central line to help detect a trend of plotted values toward either upper or lower Control Limit.

Control Limit

Also known as Process Control Limit and Natural Process Limit.

The boundaries of a process within specified confidence levels expressed as the Upper Control Limit (UCL) and the Lower Control Limit (LCL).

Control Plan (CP)

Written descriptions of the systems for controlling part and process quality by addressing the key characteristics and engineering requirements.

Corrective Action

A solution meant to reduce or eliminate an identified problem.

Correlation (Statistical)

A measure of the relationship between two data sets of variables.

Costs of Poor Quality (COPQ)

Cost of Quality (COQ)

A means to quantify the total cost of quality-related efforts and deficiencies. Considered by some to be synonymous with COPQ.

Count Chart

A Control Chart for evaluating the stability of a process in terms of the count of events of a given classification occurring in a sample. Commonly referred to as a c-chart.

Count Data

See Attribute Data.

Count-Per-Unit Chart

Also known as a u-chart.

A type of control chart used to monitor count-type data where the sample size is greater than one, typically the average number of nonconformities per unit.

Cp

A measure of dispersion, sometimes described as the engineering tolerance divided by the natural tolerance. The ratio of tolerance to 6 sigma (i.e., the Upper Specification Limit [USL], minus the Lower Specification Limit [LSL], divided by 6 sigma.

Cpk Index

Also known as Process Capability Index.

Equals the lesser of the Upper Specification Limit minus the mean divided by 3 sigma or the mean minus the Lower Specification Limit divided by 3 sigma. The greater the Cpk value, the better.

Cumulative Sum Control Chart (CUSUM)

A type of control chart used to monitor small shifts in the process mean. It uses the cumulative sum of deviations from a target.

Quality Management System Glossary: D, E, F, G

D

Data

Collected facts.
There are two basic kinds of numerical data: measured or variable data (such as 12 ounces, 10 miles, and 0.50 inches) and counted (or attribute) data (such as 112 defects).

Data Collection and Analysis

The process to determine what data are to be collected, how the data are collected, and how the data are to be analyzed.

Data Collection and Analysis Tools

A set of tools that help with data collection and analysis. These tools include check sheets, spreadsheets, histograms, trend charts, and control charts.

Defect

Defective

A unit of product that contains one or more quality characteristic defects.

Deming Cycle

Also known as the Plan-Do-Study-Act cycle, popularized by W. Edwards Deming.
Also see Plan-Do-Check-Act Cycle.

Deviation

The difference or distance of an individual observation or data value from the center point (often the mean) of the set distribution.

Distribution

A mathematical model that relates the value of a variable with the probability of the occurrence of that value in the population.

DMAIC

Also known as Six Sigma DMAIC.
Define, Measure, Analyze, Improve, and Control. A data-driven quality strategy for improving processes, and an integral part of a Six Sigma quality initiative.

E

EWMA Charts

F

F Distribution

The F distribution is the probability distribution associated with the F statistic.

F Statistic

An F statistic is a value you get when you run an Analysis of Variance (ANOVA) test or a regression analysis to find out whether the means between two populations are significantly different.

Failure

The inability of an item, product, or service to perform required functions on demand due to one or more defects.

Feature

See Characteristic.

First Pass Yield (FPY)

First Time Quality (FTQ)

Also known as First Time Quality Formula.
Calculation of the percentage of good parts at the beginning of a production run.

Fitness for Use

The degree to which a product or service meets the requirements for its intended use.

14 Points

Frequency Distribution (Statistical)

A list, table, or graph that displays the frequency of various outcomes in a sample.

G

Gauge Repeatability and Reproducibility (R&R)

A gauge R&R indicates whether the inspectors are consistent in their measurements of the same part (repeatability) and whether the variation between inspectors is consistent (reproducibility).

Repeatability—How much variability in the measurement system is caused by the measurement device.
Reproducibility—How much variability in the measurement system is caused by differences between operators.
Whether your measurement system variability is small compared with the process variability.
Whether your measurement system is capable of distinguishing between different parts.

Geometric Dimensioning and Tolerancing (GD&T)

A language of symbols and standards designed and used by engineers and manufacturers to describe a product and facilitate communication between entities working together to produce something.

Go/No-Go

State of a unit or product. Two parameters are possible: Go (conforms to specifications) and No-Go (does not conform to specifications).

Green Belt (GB)

See Six Sigma Green Belt.

Quality Management System Glossary: H, I, J, K

H

Histogram

A diagram consisting of rectangles whose area is proportional to the frequency of a variable and whose width is equal to the class interval. Gives a rough sense of the density of the underlying distribution of the data and is often used for density estimation—that is, estimating the probability density function of the underlying variable. The total area of a histogram used for probability density is always normalized to 1.

Hypothesis Testing

I

Imperfection

In-Control Process

Individual

A single unit or a single measurement of a quality characteristic, usually denoted as X. This measurement is analyzed using an Individuals Chart, CUSUM, or EWMA chart.

Individuals Chart

Also called an I-chart or X-chart.
A control chart for processes in which individual measurements of the process are plotted for analysis.

Inspection

Inspection Cost

The cost associated with inspecting a product to ensure it meets the internal or external customer’s needs and requirements; an appraisal cost.

Inspection Lot

This is the lot or batch of product to be inspected for acceptance.

Inspection States

Normal: Per the ANSI/ASQ z1.4, “Normal inspection will be used at the start of inspection unless otherwise directed by the responsible authority.”
Normal to Tightened: Per the ANSI/ASQ z1.4, “When Normal inspection is in effect, tightened inspection shall be instituted when 2 out of 5 or fewer consecutive lots or batches have been non-acceptable on original inspection.”
Tightened to Normal: Per the ANSI/ASQ z1.4, “When tightened inspection is in effect, normal inspection shall be instituted when 5 consecutive lots or batches have been considered acceptable on original inspection.”
Normal to Reduced: This switching rule requires several different things to happen. When normal inspection is in effect and the following apply, the state may change to Reduced if:

The preceding 10 lots or batches (or more) have all been accepted on original inspection
The total number of nonconforming units in the samples from those 10 preceding lots is equal to or less than the applicable limit number given (depending on the standard)
Production is at a steady rate
Reduced inspection is desired by responsible authority

International Organization for Standardization (ISO)

ISO 9000 Series Standards

ISO 9001

A voluntary quality management system standard developed by the International Organization for Standardization (ISO). First released in 1987 and one of several documents in the ISO 9000 family.

J

Just-In-Time Manufacturing (JIT)

Also known as Just-In-Time Production.
A methodology aimed primarily at reducing flow times within a production system, as well as response times from suppliers and to customers.

K

Key Process Characteristic

A process parameter that can affect safety or compliance with regulations, fit, function, performance or subsequent processing of product.

Key Product Characteristic

A product characteristic that can affect safety or compliance with regulations, fit, function, performance or subsequent processing of product.

Kruskal-Wallis Test

Quality Management System Glossary: L, M, N, O

L

Lot

Also known as a Batch.

A defined quantity of product accumulated under conditions considered uniform for sampling purposes.
Items constituting a defined quantity of uniform product for purposes of proceeding collectively through a process.

Lot Quality

The value of percentage defective or defects per hundred units in a lot.

Lot Size

Also referred to as N.

The number of units in a lot.

Lot Tolerance Percentage Defective (LTPD)

Expressed in percentage defective, the poorest quality in an individual lot that should be accepted.

Note: LTPD is used as a basis for some inspection systems and is commonly associated with a small consumer risk.

Lower Control Limit (LCL)

Control limit for points below the central line in a Control Chart.

M

Mean

The arithmetic average of a discrete set of values in a data set.

Measure

The criteria, metric, or means to which a comparison is made with output.

Measurement

Measurement System

All operations, procedures, devices, and other equipment, personnel and environment used to assign a value to the characteristic being measured.

Measurement Uncertainty

In metrology, a non-negative parameter characterizing the dispersion of the values attributed to a measured quantity.

Median

The center value of a set of data in which all the data are arranged in sequence.

Mode

The value occurring most frequently in a data set.

Moving Range

Moving Sigma

Multivariate Control Chart

A control chart for evaluating the stability of a process in terms of the levels of two or more variables or characteristics.

N

n

The number of units in a sample.

N

The number of units in a population.

Nonconforming Unit

A unit with one or more nonconformities or defects. Also called a reject.

Nonconformity

A specified requirement that is not fulfilled. Also see Blemish, Defect, and Imperfection.

Nondestructive Testing and Evaluation (NDT, NDE)

Testing and evaluation methods that do not damage or destroy the test specimen.

Nonparametric Tests

Normal Distribution (statistical)

The charting of a data set in which most of the data points are concentrated around the average (mean), thus forming a bell-shaped curve.

np-Chart

A control chart based on counting the number of defective units in each constant size subgroup. The np-chart is based on the binomial distribution.

O

Operating Characteristic Curve (OC curve)

Also known as Operating Curve.

Outliers

Unusually large or small observations relative to the rest of the data.

Out-of-Control Process

Out-of-Spec

A term that indicates a unit does not meet a given requirement or specification.

Overall Equipment Effectiveness (OEE)

Over Control

Quality Management System Glossary: P, Q, R

P

Pareto Chart

Also known as the 80-20 rule.

Parts Per Million (PPM)

A metric reporting the number of defects normalized to a population of one million for ease of comparison.

Parts per Thousand (PPT)

A ratio often used to refer to the concentration of solutes in solutions, such as salts in water (i.e., salinity).

P Chart

See Percent Chart.

Percent Chart

Also referred to as a proportion chart.

A control chart for evaluating the stability of a process in terms of the percentage of the total number of units in a sample in which an event of a given classification occurs.

Percentiles

Plan-Do-Check-Act (PDCA) Cycle

Also known as PDCA Model.

Poisson Distribution

Precision

The amount of variation that exists in the values of multiple measurements of the same characteristic or parameter. Greater precision means less variation between measurements.

Probability (statistical)

The likelihood of occurrence of an event, action, or item.

Process

A set of interrelated work activities that transform inputs into outputs.

Process Average Quality

Expected or average value of process quality.

Process Capability

A statistical measure of the inherent process variability of a given characteristic.

Process Capability Index

The value of the tolerance specified for the characteristic divided by the process capability. The several types of process capability indexes include the widely used Cpk and Cp.

Process Control

The method for ensuring that a process meets specified requirements.

Process Improvement

Actions taken to increase the effectiveness or efficiency of a process in meeting specified requirements.

Proportion Chart

See Percent Chart.

Q

Quality

Quality Assurance/Quality Control (QA/QC)

Quality of Conformance

The ability of a product, service, or process to meet its design specifications. Design specifications are an interpretation of what the customer needs.

Quality Rate

See First Pass Yield.

Quartile

Quartiles divide the ordered data into 4 equal groups. The second quartile (Q2) is the median of the data.

R

Random Cause

A cause of variation due to chance and not assignable to any factor.

Random Sampling

A commonly used sampling technique in which sample units are selected so all combinations of n units under consideration have an equal chance of being selected as the sample.

Range (statistical)

The measure of dispersion in a data set (the difference between the highest and lowest values).

Range Chart (R Chart)

Also known as Range Control Chart.

A control chart in which the range (R) of a subgroup is used to track instantaneous variations and to evaluate the stability of the variability within a process.

Regression Analysis

A set of statistical processes for estimating the relationships among variables.

Rejection Number

The smallest number of defectives (or defects) in the sample or samples under consideration that will require rejection of the lot.

Repeatability

The variation in measurements obtained when one measurement device is used several times by the same person to measure the same characteristic on the same product.

Reproducibility

The variation in measurements made by different people using the same measuring device to measure the same characteristic on the same product.

Root Cause

A factor that caused a nonconformity and should be addressed with corrective action.

Root Cause Analysis

The method of identifying the initiating cause of a problem, which leads to preventing it from occurring again.

Run

A consecutive number of points consistently increasing or decreasing. A run can be evidence of the existence of special causes of variation that should be investigated.

Run Chart

A chart showing a line connecting numerous data points collected from a process running over time.

Quality Management System Glossary: S

Sample

In acceptance sampling, one or more individual units (pieces) of product drawn from a lot for purposes of inspection to reach a decision regarding acceptance of the lot.

Sample Size [n]

The number of units (pieces) in a sample.

Sample Standard Deviation Chart (s chart)

The s chart tracks subgroup standard deviations; the plot point represents the calculated sample (n-1) standard deviation of the subgroup.

Sampling at Random

As commonly used in acceptance sampling theory, the process of selecting sample units so all units under consideration have the same probability of being selected.

Note: Equal probabilities are not necessary for random sampling; what is necessary is that the probability of selection be ascertainable. However, the stated properties of published sampling tables are based on the assumption of random sampling with equal probabilities. An acceptable method of random selection with equal probabilities is the use of a table of random numbers in a standard manner. A simple random sample is a set of n objects in a population of N objects where all possible samples are equally likely to happen.

Example: 100 objects (n) in a population of 10,000 objects (N). In Acceptance Sampling, the Lot size combined with the AQL defines how many “random” samples to inspect.

Sampling Distribution

The probability distribution of a statistic. Common sampling distributions include t, chi-square (c2), and F. Also known as finite-sample distribution, sampling distribution is the probability distribution of a given random-sample-based statistic. Sampling distributions are important in statistics because they provide a major simplification en route to statistical inference.

Sampling, Single

Sampling inspection in which the decision to accept or reject a lot is based on the inspection of one sample. A single sampling plan is specified by the pair of numbers (n,c). The sample size is n, and the lot is rejected if there are more than c defectives in the sample. It is referred to as single, because the decision is made on one inspection (visual or measured) of 1 or more pieces.

Example:
Lot size = 500, AQL is 0.25, sample size (n) = 50, c=1. If any piece is outside specification, the lot (or sample) fails.

Sampling, Unit

Sequential sampling inspection in which, after each unit is inspected, the decision is made to accept a lot, reject it or inspect another unit. See Single Sampling above.

Example from the web:
In the context of market research, a sampling unit is an individual person. The term sampling unit refers to a singular value within a sample database. For example, if you were conducting research using a sample of university students, a single university student would be a sampling unit.

Scatter Plots

A graphical technique used to visually analyze the relationship between two variables. Two sets of data are plotted on a graph: the y-axis indicates the variable to be predicted, and the x-axis indicates the variable to make the prediction.

Short-Run Techniques

Adaptations made to control charts to help determine meaningful control limits when only a limited number of parts are produced, or when a limited number of services are performed. Short-run techniques usually focus on the deviation (of a quality characteristic) from a target value.

Sigma

One standard deviation in a normally distributed process.

Six Sigma

A rigorous, data-driven approach (and methodology) for analyzing and eliminating the root causes of business problems.

Six Sigma Black Belt (BB)

Also known as Lean Six Sigma Black Belt and Black Belt Six Sigma.

Certified Lean Six Sigma designation. A full-time team leader responsible for implementing process improvement projects—define, measure, analyze, improve and control (DMAIC) or define, measure, analyze, design and verify (DMADV)—within a business to drive up customer satisfaction and productivity levels.

Six Sigma Green Belt (GB)

An employee who has been trained in the Six Sigma improvement method and can lead a process improvement or quality improvement team as part of his/ her full-time job.

Six Sigma Master Black Belt (MBB)

Also known as Lean Six Sigma Master Black Belt.

A problem-solving subject matter expert responsible for strategic implementations in an organization. This Six Sigma pro is typically qualified to teach other facilitators the statistical and problem-solving methods, tools, and applications to use in such implementations.

Six Sigma Tools

The problem-solving tools used to support Six Sigma and other process improvement efforts: voice of the customer, value stream mapping, process mapping, capability analysis, Pareto charts, root cause analysis, failure mode and effects analysis, control plans, statistical process control, 5S, mistake proofing, and design of experiments.

Six Sigma Yellow Belt

Refers to someone who has attained Six Sigma yellow belt certification. A team member who supports and contributes to Six Sigma projects, often helping to collect data, brainstorm ideas, and review process improvements.

Skewness

Asymmetry in a statistical distribution. Skewed data may affect the validity of control charts and other statistical tests based on the normal distribution.

Special Cause

Cause of variation that arise because of special circumstances. They are not an inherent part of a process. Special cause is also referred to as assignable cause. Also see Common Cause.

Specification

A document that states the requirements to which a given product or service must conform.

Spread

Also known as dispersion, variability, or scatter.

The extent to which a distribution is stretched or squeezed.

Stability

A stable process is said to be in control. A process is considered stable if it is free from the influences of special causes.

Standard Deviation (statistical)

A measure that is used to quantify the amount of variation or dispersion of a set of data values.

Statistic

A single measure of some attribute of a sample—used to make inferences about the population from which the sample came. Sample mean, median, range, variance, and standard deviation are commonly calculated statistics.

Statistical Process Control (SPC)

An industry-standard methodology for measuring and controlling quality during the manufacturing process.

Statistical Quality Control (SQC)

The application of statistical techniques to control quality. Includes acceptance sampling, which statistical process control does not.

Statistics

A branch of mathematics dealing with the collection, organization, analysis, interpretation, and presentation of data.

Subgroup

Another name for a sample from the population.

Supplier Quality Assurance

Confidence that a supplier’s product or service will fulfill its customers’ needs; achieved by creating a relationship between the customer and supplier that ensures the product will be fit for use with minimal corrective action and inspection.

According to quality management guru Joseph M. Juran, nine primary activities are needed: 1) define product and program quality requirements; 2) evaluate alternative suppliers; 3) select suppliers; 4) conduct joint quality planning; 5) cooperate with the supplier during the execution of the contract; 6) obtain proof of conformance to requirements; 7) certify qualified suppliers; 8) conduct quality improvement programs as required; and 9) create and use supplier quality ratings.

Supplier Quality Management

A system in which supplier quality is managed by using a proactive and collaborative approach. The costs of transactions, communication, problem resolution, the impact of switching suppliers, and overall cost. Also focuses on factors that impact supply-chain performance, such as the reliability of the supplier delivery, and the supplier’s internal policies regarding inventory levels.

Supply Chain

The system of organizations, people, activities, information, and resources involved in moving a product or service from supplier to customer.

Quality Management System Glossary: T, U, V, W, X, Y, Z

T

T-Distribution

Any member of a family of continuous probability distributions that arises when estimating the mean of a normally distributed population in situations where the sample size is small, and population standard deviation is unknown.

Tampering

An action taken to compensate for variation within the control limits of a stable system. Tampering increases (rather than decreases) variation, as in the case of Over Control.

Tolerance

The maximum and minimum limit values a product can have and still meet customer requirements.

Trend

The graphical representation of a variable’s tendency, over time, to increase, decrease, or remain unchanged.

Trend Control Chart

A control chart in which the deviation of the subgroup average, X-bar, from an expected trend in the process level is used to evaluate the stability of a process.

Type I Error

An incorrect decision to reject something (such as a statistical hypothesis or a lot of products) when it is acceptable.

Type II Error

An incorrect decision to accept something when it is unacceptable.

U

U-Chart

Count-per-unit chart.

Unit

An object for which a measurement or observation can be made; commonly used in the sense of a unit of product or piece, the entity of product inspected to determine whether it is defective or non-defective.

Upper Control Limit (UCL)

Control limit for points above the central line in a control chart.

V

Variable Data

Measurement information. Control charts based on variable data include average (X-bar) chart, range (R) chart, and sample standard deviation (or s) chart.

Variance

In probability theory and statistics, variance is the expectation of the squared deviation of a random variable from its mean. Informally, it measures how far a set of (random) numbers are spread out from their average value.

Variation

A change in data, characteristic or function caused by one of four factors: special causes, common causes, tampering, or structural variation.

W

Weibull Distribution

Named after Swedish mathematician Waloddi Weibull, the Weibull Distribution is a continuous probability distribution. Commonly used to assess product reliability, analyze life data, and model failure times.

X

X-Chart

A control chart used for process in which individual measurements of the process are plotted for analysis. Also called an Individuals chart or I-chart.

X-Bar Chart

A control chart used for processes in which the averages of subgroups of process data are plotted for analysis.

Z

Zero Defects

A management tool aimed at the reduction of defects through prevention. Directed at motivating people to prevent mistakes by developing a constant, conscious desire to do their job right the first time. Developed by quality expert Philip B. Crosby.

Z1.4 and Z1.9

ANSI/ASQ Z1.4-2003 (R2013): Sampling Procedures and Tables for Inspection by Attributes is an acceptance sampling system to be used with switching rules on a continuing stream of lots for the acceptance quality limit (AQL) specified.

ANSI/ASQ Z1.9-2003 (R2013): Sampling Procedures and Tables for Inspection by Variables for Percent Nonconforming is an acceptance sampling system to be used on a continuing stream of lots for the AQL specified.

Quality of Conformance

The ability of a product, service, or process to meet its design specifications. Design specifications are an interpretation of what the customer needs.

Quality Rate

See First Pass Yield.

Quartile

Quartiles divide the ordered data into 4 equal groups. The second quartile (Q2) is the median of the data.

R

Random Cause

A cause of variation due to chance and not assignable to any factor.

Random distribution

A distribution that forms no particular shape.

Random sample

A sample that allows every item in a population to have an equal chance of being selected, with no bias.

Random Sampling

A commonly used sampling technique in which sample units are selected so all combinations of n units under consideration have an equal chance of being selected as the sample.

Range

Range is an estimate of spread in a set of data points; the difference between the highest and lowest values in the data set.

Range (statistical)

The measure of dispersion in a data set (the difference between the highest and lowest values).

Range Chart (R Chart)

Also known as Range Control Chart.

A control chart in which the range (R) of a subgroup is used to track instantaneous variations and to evaluate the stability of the variability within a process.

Regression Analysis

A set of statistical processes for estimating the relationships among variables.

Rejection Number

The smallest number of defectives (or defects) in the sample or samples under consideration that will require rejection of the lot.

Repeatability

The variation in measurements obtained when one measurement device is used several times by the same person to measure the same characteristic on the same product.

Reproducibility

Reproducibility refers to variation in a series of measurements that have been taken with one gage measuring one characteristic of the same item by different people.

Root Cause

A factor that caused a nonconformity and should be addressed with corrective action.

Root Cause Analysis

The method of identifying the initiating cause of a problem, which leads to preventing it from occurring again.

Run

A consecutive number of points consistently increasing or decreasing. A run can be evidence of the existence of special causes of variation that should be investigated.

Run chart

A run chart is a simple line chart that plots one characteristic over time. It is used to plot individual observations and detect patterns in the data.

S

Sample

A sample is a collection of one or more observations used to analyze the performance of a process, as opposed to the total populations. It is intended to represent the characteristics of the population. Sample is a synonym for “subgroup” in process control applications.

Sample size

The number of pieces of data taken at one time. For example five boxes are checked for stiffness every hour, the sample size in this case is five. If the temperature of a room is taken every hour, only one number is collected every hour, so the sample size is one.

Sample Size [n]

The number of units (pieces) in a sample.

Sample Standard Deviation Chart (s chart)

The s chart tracks subgroup standard deviations; the plot point represents the calculated sample (n-1) standard deviation of the subgroup.

Sampling at Random

As commonly used in acceptance sampling theory, the process of selecting sample units so all units under consideration have the same probability of being selected.

Example: 100 objects (n) in a population of 10,000 objects (N). In Acceptance Sampling, the Lot size combined with the AQL defines how many “random” samples to inspect.

Sampling Distribution

Sampling, Single

Example:
Lot size = 500, AQL is 0.25, sample size (n) = 50, c=1. If any piece is outside specification, the lot (or sample) fails.

Sampling, Unit

Sequential sampling inspection in which, after each unit is inspected, the decision is made to accept a lot, reject it or inspect another unit. See Single Sampling above.

Scatter Plots

Short-Run Techniques

Sigma

Sigma is the Greek symbol, sigma symbol , used to denote standard deviation. It is a measure of the variation or spread within a set of data.

Sigma of the individuals

Sigma of the individuals is standard deviation calculated from the individual data values in a data set. It is also known as actual or calculated sigma.

Six Sigma

A rigorous, data-driven approach (and methodology) for analyzing and eliminating the root causes of business problems.

Six Sigma Black Belt (BB)

Also known as Lean Six Sigma Black Belt and Black Belt Six Sigma.

Six Sigma Green Belt (GB)

An employee who has been trained in the Six Sigma improvement method and can lead a process improvement or quality improvement team as part of his/ her full-time job.

Six Sigma Master Black Belt (MBB)

Also known as Lean Six Sigma Master Black Belt.

Six Sigma Tools

Six Sigma Yellow Belt

Skewed distribution

A distribution that tails off to one side, either to the left or right.

Skewness

Skewness is a statistic that is used to measure the symmetry of the distribution for a set of data. A process that is skewed tails off to the left or to the right.

Special cause

Special cause variation is a source of variation that is intermittent, not predictable. Sometimes it is called “assignable cause” variation. On a control chart, a special cause is signaled by points beyond the control limits, runs, or nonrandom patterns within the control limits. A process that has special cause variation is said to be out-of-control, unstable, or unpredictable.

Specification

A document that states the requirements to which a given product or service must conform.

Specification limits

Specifications are boundaries, usually set by management, engineering, or customers, within which a system must operate. They are sometimes called engineering tolerances.

Spread

Also known as dispersion, variability, or scatter.

The extent to which a distribution is stretched or squeezed.

Stability

A stable process is said to be in control. A process is considered stable if it is free from the influences of special causes.

Stable process

A system, analysed by a control chart, with no special causes of variation present, this system is also said to be in control. Variation within a stable system is due to common causes, and is predictable.

Standard deviation

A statistic that describes the variation or spread within a data set. It can be used to indicate the variation in a process and to compare with specifications.

Standard Deviation (statistical)

A measure that is used to quantify the amount of variation or dispersion of a set of data values.

Statistic

Statistical control

Statistical control is a condition describing a process from which all special causes of variation have been removed and only common causes of variation remain. On a control chart, processes that are in statistical control show no subgroups outside the control limits, no runs, and no nonrandom patterns. This condition is also referred to as in control, stable, or predictable.

Statistical Process Control (SPC)

An industry-standard methodology for measuring and controlling quality during the manufacturing process.

Statistical Quality Control (SQC)

The application of statistical techniques to control quality. Includes acceptance sampling, which statistical process control does not.

Statistics

A branch of mathematics dealing with the collection, organization, analysis, interpretation, and presentation of data.

Subgroup

A subgroup is one or more occurrences or measurements taken at one time. Multiple subgroups are used to analyze the performance of a process. Subgroup is used as a synonym for “sample.”

Supplier Quality Assurance

Supplier Quality Management

Supply Chain

The system of organizations, people, activities, information, and resources involved in moving a product or service from supplier to customer.

Symmetrical distribution

A distribution that if cut in half, shows each side is the mirror of the other.

T

T-Distribution

Tampering

An action taken to compensate for variation within the control limits of a stable system. Tampering increases (rather than decreases) variation, as in the case of Over Control.

Target value

The exact value at which customers, engineering, or management want the system to operate.

Tolerance

The maximum and minimum limit values a product can have and still meet customer requirements.

Trend

The graphical representation of a variable’s tendency, over time, to increase, decrease, or remain unchanged.

Trend Control Chart

A control chart in which the deviation of the subgroup average, X-bar, from an expected trend in the process level is used to evaluate the stability of a process.

Trial limits

On a control chart, trial limits are calculated when there is insufficient data to calculate control limits. These give a temporary guide until sufficient data has been collected.

U

Type I Error

An incorrect decision to reject something (such as a statistical hypothesis or a lot of products) when it is acceptable.

Type II Error

An incorrect decision to accept something when it is unacceptable.

U

u-chart

An attributes control chart that is used to monitor the number of nonconformities per unit, such as defects per item. The subgroup size may vary.

Undercontrol

Not reacting to a set of data when the data is showing an issue or problem. For example, in a control chart, it would be ignoring a special cause of variation.

Uniform distribution

A distribution, when drawn as a histogram, has each bar at a similar frequency.

Unit

Unstable system

A system that contains special and common causes of variation; this system is also said to be out of control. An unstable system is unpredictable.

Upper control limit

A line on a control chart used as a basis for judging whether variation from the data on the chart is due to special or common causes. Any point beyond the upper control limit is an indication of a special cause occurring. This limit is calculated from data collected on the system, it is not a specification or limit set by customers or management. Its symbol is UCL.

Upper Control Limit (UCL)

Control limit for points above the central line in a control chart.

Upper specification limit

The upper limit of a specification. This limit is set as an aim for a system or process, it is usually set by the customer of the process, engineering, or management. The symbol for the upper specification is USL–upper specification limit.

V

Variability

Variability refers to the differences among individual outputs of a process. In control chart pairs, it refers to the differences between individual observations and is analyzed in range, sigma, and moving range charts.

Variable Data

Measurement information. Control charts based on variable data include average (X-bar) chart, range (R) chart, and sample standard deviation (or s) chart.

Variables

Variables data is data that is acquired through measurements, such as length, time, diameter, strength, weight, temperature, density, thickness, pressure, and height. X-bar and range, X-bar and sigma, and individuals and moving range charts are used to analyze variables data.

Variance

Variation

A change in data, characteristic or function caused by one of four factors: special causes, common causes, tampering, or structural variation.

W

Weibull Distribution

X

X-bar

X-bar is the average or mean of values in a group of observations.

X-bar chart

The X-bar chart is a variables control chart that shows the subgroup averages. The subgroup size for this chart must be larger than one and consistent.

Z

X-Chart

A control chart used for process in which individual measurements of the process are plotted for analysis. Also called an Individuals chart or I-chart.

Z

Z value

Used in capability analysis, it is the symbol for the number of standard deviations between the average and a specification limit for a normal distribution.

Z1.4 and Z1.9

Zero Defects

Zlower

The symbol for the Z value for the lower specification limit. It represents the number of standard deviations between the average and the lower specification limit.

Zmin

The minimum of the Z values, either Zupper or Zlower. It is used to calculate the Cpk index in capability analysis.

Zupper

The symbol for the Z value for the upper specification limit. It represents the number of standard deviations between the average and the upper specification limit.

Customers using Advantive in quality advisor

“Enact helps us quickly respond to quality issues, which saves us money.”

Jegadish Gunasagaran Quality Assurance Manager, Bakery on Main

““What sets Ben & Jerry’s apart from our competitors is not only our insistence on high-quality ingredients, but also the extra and unique flavours we use to create a euphoric customer experience. Ensuring the final product reflects the passion and quality that we put into each pint required a quality solution that emphasized the same attention to details that we do.””

Melissa Corcia, Quality Manager, Ben & Jerry’s

““By utilizing InfinityQS® ProFicient™ to implement SPC and Six Sigma best practices across our manufacturing processes, Ben & Jerry’s will continue to identify opportunities for cost savings and ensure the highest level of customer satisfaction. The result is the perfect pint for our customers.””

Nina King, Quality Supervisor, Ben & Jerry’s