Mitutoyo Glossary

8/12/2019 Mitutoyo Glossary

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Mitutoyo Glossary

Analysis of Variance (ANOVA)

Statistical method to evaluate the data from a designed experiment.

Apparent Resolution

The size of the smallest increment on the measuring device.

Appraiser Variation

Variation due to the difference in techniques in the inspection method. This is calculated as thevariation to reproduce the measurements of another appraiser or inspector. Appraiser variation isreferred to as "Reproducibility".

Assignable cause

(... of variation) Those causes of variation in a process which are not random, i.e. which havesome source which can be determined and perhaps eliminated.

Attribute

(Quality ...) Data coming from yes/no, or pass/fail determinations of whether the units conform tostandards. May or may not include weighting by seriousness of defect, etc.

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Bell-shaped curve

Plotted curve or distribution showing a central peak and tapering off smoothly and symmetricallyto "tails" on wither side. A normal curve is an example.

Bilateral tolerance

A condition where both an upper and lower tolerance are specified. In contrast, a unilateraldistribution is one-sided. See also Unilateral distribution.

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c

(Count - Attribute data) The count or number of events of a given classification occurring in a

sample. More than one event may occur in a unit (area of opportunity), and each such eventthroughout the sample is counted.

Capability

(...of a data set) The ability of the process to stay within a given specification range. Capability isan evaluation function, and as such will become true or false, depending on the result of theevaluation. The actual test for capability is made by the equality:Cp>=1.0 (Cp is greater than or equal to one)

Centerline

For control charts: the horizontal line marking the center of the chart, usually indicating thenominal expected value of the quality being charted.


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Characteristic

A property which helps to differentiate between items of a given sample or population.

Charts

Shewart control charts for plotting subgroups means or variances against the control limits orZone chart for color display of individual observations about target value.

Common causes

Those sources of variability in a process which appear to be random, i.e. inherent in the processitself; these causes produce the variability within the 3 sigma limits.

Control

(Charts) Plot of some parameter of process performance, usually determined by regular sampling

of the product as a function (usually) of time or unit number or other chronological variable. Thecontrol limits are also plotted for comparison. The parameter plotted may be the mean value of aparticular measurement for a product sample of specified size (x chart), the range of values in thesample (R chart), the percent of defective units in the sample (p-chart), etc.

Control Chart

A graphical method for evaluating whether a process is or is not in a "state of statistical control."

The determinations are made through comparison of the values of some statistical measure for anordered series of samples or subgroups with control limits.

Control limits

Limits on a control chart which are used as criteria for signaling the need for action, or for judgingwhether a set of data does or does not indicate a "state of statistical control." Note: When warning

limits are used, the control limits are often called action limits. Action may be in the form ofinvestigation of the source(s) of an assignable cause, making a process adjustment, orterminating a process. Criteria other than control limits are also used frequently.

Cp

A process capability index defined only if the process is in a state of control and normallydistributed. Cp tells how many process bell curves will fit into the specification range.Consequently, a value of 1.33 or greater is generally considered desirable. Cp only addresses the

issue of whether the process spread is acceptable. It does not address the issue of whether thelocation of the process center is acceptable.

By formula, Cp = specification range / 6 sigma. Where sigma = /d2

Cpk

A process capability index defined only if the process is in a state of control, is normallydistributed, and has a target at the midpoint of the specification. It indicates whether the process

will produce units within the tolerance limits. Cpk has a value equal to Cp if the process iscentered on the mean specification; if Cpk is negative, the process mean is outside thespecification limits; if Cpk is between 0 and 1, then some of the 6 sigma spread falls outside thetolerance limits. If Cpk is larger than 1, the 6 sigma spread is completely within the tolerancelimits.By formula, Cpk = Min (ZU, ZL)/3

Where ZU = (UTL - )/sigma ; ZL = ( -LTL)/sigma; where sigma = /d2

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Database


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A collection of interrelated data items. Specifically, the contents and structure of a number oftables with columns as fields (part_id, feature_id, etc...) and rows that contain data (manifold,bore depth, etc). The MEASURLK.DB database houses all the information necessary for datacollection and receives the data once collected.

Defect

A departure of a quality characteristic from its intended level or state that occurs with a severitysufficient to cause an associated product or service not to satisfy intended normal, or reasonably

foreseeable, usage requirements.

Designed Experiment

A plan to conduct tests that involves all of the prework that must be done prior to conducting any

tests. Prework requirements are writing questions; data collection sheets are prepared; analysis ofdata is organized; and the limitations of the test are determined.

Detail Window

A window that can display any control chart, statistics, observations, etc.

Discrimination

The larger of the apparent and effective resolutions for single reading systems. Also referred to asthe minimum accuracy of any given measuring device. The number of data categories is oftencalled the "discrimination ratio" since it describes the number of classifications that can be reliablydistinguished given an observed process variation.

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Effective Resolution

The size of the data category when the total measurement system variation is considered.

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Frequency distribution

A set of all the various values that individual observations may have and the frequency of theiroccurrence in the sample or population.

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Global Variable View

A Manager View that displays a Cpk bar graph of all characteristics in the current inspection runfrom worst case to best case.

Graphic View

A window that displays a bitmap background on which call outs can be placed that represent thestatistical and measurement states of all characteristics in the current inspection run.

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Histogram

A plot of a frequency distribution in the form of rectangles whose bases are equal to the cellinterval and whose areas are proportional to the frequencies.

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Inspection

The process of measuring, examining, testing, gaging or otherwise comparing the unit with theapplicable requirements.

Inspection Run

All data that pertains to a given inspection routine, including measurement data, for a single RunID

Interaction

Correlation between the appraiser and the part. Appraiser differences should depend on the partbeing measured.

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LCL

Lower Control Limit. Control limit for points plotting below the center level.

Linearity

Difference in the bias values of a gage through the operating range of the gage.

Lot

A definite quantity of a product or material accumulated under conditions that are considereduniform for sampling purposes.

LTL

Lower Tolerance Limit. The lowest value of a product dimension or measurement which isacceptable. While LTL is now the preferred term, the term Lower Specification Limit, or LSL, wasat one time more frequently used.

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Manager View

A snapshot window display that shows all characteristics of the current inspection run. Up to 16snapshot windows can be viewed on the screen at once.

Mean

(Statistical) Average value of some variable. The mean is given by the formula: Mean = XBar =(X1 + X2 +X3 + . . . + XN) / N ,where N is the number of elements in the sample and XN areindividual observation values.

Measurement System Error

The combination gage bias, repeatability, reproducibility, stability and linearity.

Median

For an odd number of units: the middle value when all values have been arranged in order of size;for an ordered set X1, X2,. . . , X2k-1, Median = Xk. For an even number of values so arranged,the median is the average of the two middle units; for an ordered set X1, X2, ..., X2k, Median =(Xk + Xk+1) / 2.


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Menu

A list of available commands in an application window.

Menubar

The horizontal bar at the top of an application window, immediately beneath the title bar, whichlists the available menus.

Mixture

A combination of two distinct populations. On control charts, a mixture may be indicated by anabsence of points near the centerline.

Monitor

While primarily referred to as the cathode ray device which provides the user with information on

what is going on inside the computer (the "compute screen"), the term may refer to any softwareor hardware that observes, supervises, controls, or verifies the operations of a system.

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np

(Number of affected units) The total number of units (areas of opportunity) in a sample in whichan event of a given classification occurs. A unit (area of opportunity) is to be counted only onceeven if several events of the same classification are encountered therein.

Natural limits

Limits which include a stated fraction of the individuals in a population. Note: For populations with

a Normal (Gaussian) Distribution, the natural process limits ordinarily will be set at 3s (where s =

standard deviation). If placed around the standard level, these limits identify the boundarieswhich will include 99.7% of the individuals in a process that is properly centered and in a state ofstatistical control.

Nominal Dimension

For a product whose size is of concern: the "name" of that particular dimension. For example, withspecifications 20 (+2,-2), the nominal is 20; with specifications 30 (+5, 0), the nominal is 30.

Normal Distribution

A Gaussian distribution; A distribution that appears to be "bell shaped" . . . symmetric, mostreadings in the middle, tailing off at both ends. In most cases, a normal distribution is assumedfor individuals. The Central Limit Theorem expresses the fact that the distribution of subgroupmeans tends toward normality regardless of the distribution of the individuals.

Note

Remark or annotation attached to a subgroup to aid in the review of an output listing.

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Observation

1. The process of determining the presence or absence of attributes or making measurements of avariable.

2. A result of determining the presence or absence of attributes or making measurements of avariable.


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Out of control

Process which exhibits a lack of statistical control or uniformity. See State of Statistical Control.

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Periodicity

Tendency of recurring at regular intervals.

Process

The combination of people, equipment, materials, methods, and environment that produce output-- a given product or service. A process can involve any aspect of your business. A key tool formanaging processes is Statistical Process Control (SPC).

Process Capability

After the process is in control, process capability describes what the process is capable of doing,typically in terms of the natural limits for variables data and the process average for attribute

data. Capability is usually determined by performing measurements on some (or all) of theproduct units produced by the process. See also Cp and Cpk.

Process Control

Maintaining the performance of a process at its capability level. Process control involves a range ofactivities such as sampling the process product, charting its performance, determining causes ofany problems, and taking corrective actions.

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Quality

The totality of features and characteristics of a product or service that bear on its ability to satisfygiven needs.

Quality Control

The operational techniques and the activities which sustain a quality of product or service that willsatisfy given needs; also the use of such techniques and activities.

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R-chart

Control chart of the range of variation among the individual elements of a sample i.e., thedifference between the largest and smallest elements as a function of time, or lot number, orsimilar chronological variable.

Random

Varying with no discernible order or pattern.

Range

A measure of dispersion which is the difference between the largest observed value and thesmallest observed value in a given sample. While the range is a measure of dispersion in its own

right, it is sometimes used to estimate the population standard deviation, but is a biasedestimator unless multiplied by the factor (1/d2) appropriate to the sample size. Formula: R =largest observation minus smallest observation. Note: Because the range tends to be inefficient, it


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is not recommended that ranges be used for large sample sizes. A "rule of thumb" suggests amaximum sample size of 10.

Regression Analysis

A calculation to define the mathematical relationship between two or more variables.

Repeatability

Variation in measurements obtained with a single gage being used several times by one appraiserwhile measuring a single characteristic on a single part.

Reproducibility

Variation in the average of the measurements made by different appraisers while measuring asingle characteristic on a single part using one gage.

Resolution

The capability of the measurement system to detect and accurately indicate small changes of a

measured characteristic.

Run

1. Inspection Run - A collection of observations taken on a group of features.2. Seven consecutive points that fall above or below the centerline of a control chart.

Run ID

An unique identifier for a given inspection run. Similar to a Lot Number or Job order number.Defaults to the date and time from the computer.

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Sample

A group of units or observations taken from a larger collection of units or observations that servesto provide information that may be used as a basis for making a decision regarding the largerquantity.

SBG

Abbreviation for SUBGROUP.

Scatter Plot

A plot of two variables, one against the other, to display correlations.

Sigma

Standard deviation (of individuals, means, ranges, etc.) See Standard Deviation.

Sigma limits

Number of standard deviations of the variable being plotted(mean, range, etc.) used for

calculating the control limits.

Snapshot Window


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Manager view - A small window that displays all characteristics in an inspection routine in one ofthe following views: Box-Whisker, Meter chart, Histogram, Information.

Specification limit

Limits that define the conformance boundaries for an individual unit of a manufacturing or serviceoperation.

Stable process

Process that is in statistical control. A process is said to be stable if it shows no recognizablepattern or change.

Standard Deviation

A measure of variability (dispersion) of observations in the sample that is the positive square rootof the sample variance,standard deviation = sigma = s

where: N = the number of data elements; Xi = the ith item in the data set;XBar = mean or average of the data set.

Standard given

A control limit calculation method which is based on adopted standard values applicable to thestatistical measures plotted on the chart.

Statistic

A quantity calculated from a sample of observations, most often to form an estimate of somepopulation parameter.

State of Statistical control

A process is considered to be in a "state of statistical control" if, in the variations among theobserved sampling, the results from it can be attributed to a constant system of chance causes.

Statistical Process Control

(SPC) A technique used with the aid of measurements or factual data, which represents theprocess output characteristics; assignable causes of unpredictability are eliminated so that theprocess behaves in a state of statistical control.

Stratification

(... of a sample) If a sample is formed by combining units from several lots having differentproperties, the sample distribution will show a concentration or clumping about the mean value for

each lot: this is called stratification. In control charting, if there are changes between subgroupsdue to stratification, the R-chart points will all tend to be near the centerline.

Status bar

A horizontal bar beneath a window that displays status information.

Subgroup


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Subgroups are typically made up of consecutive pieces, although random samples are sometimesused. (Object Sense) A set of units or quantity of material obtained by subdividing a larger groupof units or quantity of material. (Measurement Sense) A set of groups of observations obtained bysubdividing a larger group of observations.

Subgroup Size

How many observations, events, or measurements are included in each subgroup.

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Target value X

Value within the specification limits which will be aimed for because it is decided that this is thebest value for that quality characteristic; not necessarily either the nominal or the midpoint of thespecifications.

Tolerance

The total allowable variation around a level or state (upper limit minus lower limit), or themaximum acceptable excursion of a characteristic.

Traceability

The ability to attach concise notes at various points of an inspection run. Traceability items

include; Assignable causes of variation, Operator names, Process centers, Customers andSuppliers, etc.

Trend

Gradual, systematic change with time or with another variable. Seven consecutive descending orascending variable observations constitutes a trend.

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u

(Count per unit) The average count, or average number of events of a given classification, perunit (unit area of opportunity) occurring within a sample. More than one event may occur in aunit, and each such event is recorded.

UCL

Upper Control Limit. Control limit for points plotting above the center level. See Control limits.

Unilateral tolerance

One-sided tolerance; that is, only one tolerance limit (either a minimum below the target, or a

maximum above the target) is specified. In contrast, a bilateral distribution is two-sided. See alsoBilateral Distribution.

UTL

Upper Tolerance Limit. The highest value of a product dimension or measurement which isacceptable. While UTL is now the preferred term, the term Upper Specification Limit, or USL, was

at one time more frequently used.

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Variability


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The property of exhibiting variation, i.e., in particular, changes or differences in the product of aprocess.

Variable

1. Quantity that is subject to change or variability.2. Measurement of quality by the method of variables consists of measuring and recording

the numerical magnitude of a quality characteristic for each of the units in the group underconsideration. his involves reference to a continuous scale of some kind.

Variance

Variance is a measure of dispersion. The actual formula used by the program for the calculation:

variance =

where N = the number of data elements; Xi = the ith item in the data set; Xbar = mean oraverage of the data set, and s = standard deviation.

Version

Refers to a particular programs age, the form or variation from the original program. Software is

usually given a new version designation with each new release or update, the newer versiontypically having a higher number. For some programs, may refer to a command which reports theprograms version to the user.

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