spc glossary

8/9/2019 SPC Glossary

1/8

r

Appendix

Glossary

l erms nd ymbols

,4

Constants used in the calculation

of the control line€ for mean,

mov-

ing

mean, median and mid'rang€

contol chart, with vadous

suffixes.

Accrldcy Associa

ed

with

the nearnes6

oI a

process

o the tatget value.

Action

Limit

(line)

Line on a conhol

chaft bevond which the

Drobabil-

ily

of

tinding

an observation s such hat

t indicates hat a

changeha'

occurred

to the

prccess

and that action

should be taken to investigate

and

/or

correct for the change.

Aclion zoke The

zones outside the action limits/lines

on a

control

chart where a result is a clear indication of the need for action.

,4RL

The average run lentth

to detection of a change in

a

process.

Assigtlable

a

ses

Sourcesof va-riatiori or which an

explicit reasonexist6.

Attrib

te clhlts Control drarb

used to assesshe caDabilitv and

monitor

the

performance

of parameters

a66€6sed s attdbutes or discrete

data,

Attribute doto

DiscEte data which

can be counted or classified in

some

meaningful

way which doeBnot include measurement.

ALErage SeeMearr,

B

Corutants used in the calculation

of conEol chart Iines for

standard

deviation charts.

Bar A bar placed

aboveany mathematical

ymbol ndicates hat it is

the meanvalue,

Bal chart

Adiagtarnwhich represents

the lelative frequency

oI data.

Binomkl

distribution A prcbability

distribution for

6amplesof attrib-

utes which

applies when both

the number of conforming

and non-

conJorming tems s known,

Braiflstormi g

An activity, normally

carded out in groups, in which

the

participants

are mcouraged to allow

their experi€nce and imagination

to run wild, while

centred around specific

aspectsof a problem

or effect.

c crrll A control chart

used for attributes when

the sample is

constant

and only the number

of non-conformances is

l


2/8

t

IPPendes 443

control procedure to detect change is consistent with the requirements

of the specification.

Atuseand

effect iagram A

Braphic

display which illustrat€s

he

rela-

tionship

betwe€nan effect

and ts contributory

causes.

Central cwlency Th€

clust€rin8of

a

population

about

someprefered

Centn: ine

(CL)

A line

on a control chart at

the value of the process

Creclllsl A list used

to ensur€ hat a l

steps n a prcc€dur

are caftied ou

.

Commoncauses ??Random

causes,

Confotrting Totally )^ ageemmt with the specificafionor r€quircments.

Continuaus ata

Quantitative

data conccming

a

parameter

n

which

all measured

aluesarc possible,

ven f limited

to a specific ange.

Corflol The

ability or need to observe/monitor

a process,

ecord hc

data obsewcd, in

terpret the data rccorded

and take action

on the process

ifjustified.

Conlral hart Agraphical

method

ol

recording

esults n

order toread-

ily distinguishbetween

andom and assignable

auscs

f variation.

Conlrcl inlits

line

Limits

or

lines

s€ton control

chartswhic:h cparate

the zones

of stability

(no

action required).

wahing

(possible

roblems

and the need

o seekadditional

nformaiion) and

action.

Countable afi A form

of discrete

data where occu[ences

or evcnts

can only be

counted

sce

lsoAttdbute

data).

Cp

A process

apability ndex

basedon the ratio

of the spread

of a fre-

quency

distribution to the width

of the spccification.

Cpt A process

capability ndcx basedon

both thc ccntring

of a frc-

quency

distribution and

he

ratio

of thespread

of thc distribution

b the

width

of the sp€cification.

Cusunt hdrt

A graphic pesentation

of the cusum

scorc.The cusum

chart is parti.ularly

sensitive

to the det€ction

of small sustained

chanSes.

C suntscore The cumulativc sum of the differenccs

etween

a series

ofobserved

valu€sand a predetermined

arg€t

or average alu€.

d,

or

d2

Symbolswhich represent

Harttey's

constant, he elarionship

between

he standard

deviation

(d)

and he mean

ange

R).

D Symbol which

represents the

constant used to determinc

the con-

trol limits on a rangc

chart,with various

suffixes.


3/8

I

I

lqq

Stat t ica

process

Control

Data FacE.

DeJecl

A fa'Jlt

or flaw which

is not

permitted

by rhe

specification

requirements.

D$ectiLv

An ltem vthich

contains

one

or morc defecb

and/or is

judged

to be

non-conforming.

Defeclio, The

act of discovering.

De?latio, The

dispersion

betwem

two

or mor€ data.

DifeNnce

chart A

control

chart for differences

fiom

a target

value.

Discrct?data

Data not

available

on a continuous

scale

(9ee

lsoAttribute

data).

Dispelsio, The

spread

or scatter about

a cmtral

tendency,

DM,4IC

Six sigma improvemmt

model

-

Define, Measure,

Analyse,

Improve,

Conhol.

Frequency

Ho\\t

olte samething

occurs,

Frcquencyistributio.a

A table

or

graph

which

displays

how frequently

somevalues

occur

by comparisonwith

others,Common

distributions

include

normal, binomial

and Poisson.

Gnnil

mean The

mean of

either a whole

population

or the

mean of a

series

of samples

taken from

the population.

The grand mean is an esti-

mate

ofthe true

mean

sse

Mu).

Histografi

A diagram

which represents

the relative

frequ€ncy

of data.

Individual

An isolated,

esult

or observation.

IndfuAuols lot

A graph

showing a

set of individual

results.

L,4L Lower

action limit

or line.

LCL Lower control

imit

or line.

LSL Lowff specification

imit.

LWI

Lower warning limit

or line.

&R Median

of the sample

mid-ranges.

Meaa

The average

of a set oI individual

results,

calculated by

adding

together

all the individual

rcsults and

dividinS by

the number

o]

iesults.

Means arc r€presented

by

a series

of symbols

and often

carry a

bar above

the symbol

which indicates

ihat it is

a mea]l

value.

aPr

Mod

byr

ste

by*

step

Mu(

ofaf

nn

ment

requ

The

n

popt

valu

and

9

asa

items


4/8

r

I

ppendices

45

Mun chatt Agtaphwith conrrollinesused o monitor the accuracv f

a proc€ss/

eingassessed

y a ptotofsample

m€ans.

M.ar? 'dr.qe

The

mean

ofa

series f

sample anges.

Mu

satnple

izt

The average

r mean

of rh€

sample

sizes.

Mcdid,

The

central

value

within n

poputation

above

and

b€Iow

which

there

are an

equal number

of member;

of the

popularion.

Mode

The

most frequcntly

occurring

vatue

within

a population.

MaDi gt

ean

Am 'anvatue

calculated

rom

a sedes

f individua

vatues

by moving

the sampl€

or

calcuiation

of the

m€an

hrough

he

series n

sicps

ofone

individual

value

and

without

changing

heiample

size.

Mooittg

anY

A range

vatue

calculr tcd

from

a seri€s

of individ

uai values

by moving

ihe

sample

orcatcuhtion

of the ranSe

hrouSh

he scries

n

steps

of one ndividual

value

and wiihour

chan;ing

the'sample

ize.

Mll

(/i)

The

Grcek

etter

usedas

he symbol

o represcnt

he rue

mcan

oi

a

population

as

opposed

o the

various

estimntes

f this

value

whjch

measLrrement

nd

calculation

make

possjble.

, The

number

of

indivjduals

within

a samplc

of size r. , _bar n)

is

th€ averate

sizeofa

series

f sarhples,

Nan-conf)tnifig

Not in

conformance

with the

specification/require_

Non-conl,rmititi

Defects,

tort faults

with

respect

o the

spccification

Nor

wl dislribution

Also

known

as he

Gaussian

istribution

of a coniin_

uous

variable

nd sometimes

eferred

o

as he

bellshaped,

djstribution.

The

normal

disdiblrrion

has

the

characteristic

hat

68.2;per

ceni

of thc

population

s

contained

within

1

one standard

eviation

rom

thc

mean

value,

95.45

per

cent within

a

hvo standard

deviations

from

the mean

and 99.73per

cent withhin 1

thrle

standard

deviations

ftom

rhe

mean.

l]/ .rali

A

controi

chart

used for

attdbutes

when

the

sample

siz€ s

constanl

and

the number

of

conforming

and non-conJorming

tems

wthin

a samplearebothknown. /r s th€ sampte izeand pis the proportionof

non-contormtng

tems.

p':rdlt

A control

chaft

used for

attribur€s

showing

the proporrion

oI

non{onformins

item. in

d sample.

L

the

proporrion,rf

non_conJormin

rtem,.rnd -bJr t)

r, .pre,enr.

heavcrrge

f

d serie\ f

vdtuc.

ot

p.

Parcta

ana.lysis.

technique

of ranking

data in

order to

disthguish

b€tween

the

vital few

and

the trivial

many.


5/8

I

I

446

Stal isticatrocess

onlroi

Poissonistib tion A probability diBtribution or samples I attributes

which

applieswh€n

only ihe number

of non-confomities

s known.

Pop latiotl

The tullset

of data from

which

samplesmay

be taken.

P/ecision

Associated

with

the scatter

abouta

central mdency.

Prcpention

The act

of seekint

to stop

somethint

occurrint.

Probability

A rneaswe

f the ilelihood

of an

occturence

l incident.

P/ocess

Any actjvity

which

converts nputs

into

outputs.

Prccess

apability

A measure

f the capability

of a proc$s

achiev€d

by

assessing

he

statisticalstate

of control

of theprocess

nd the

amount

of

randomvariation ptesent. t rnay also efer o the tolerance

llowed

by

thespecification,

Prccess

,pability ndet

An index

of capability

(

see

Cpa A Cpkr.

Processontrol

Themanagement

f a

proce66

y observatio&

analysis.

interprtation

and action

designed

o limit variation.

Process ean

The avetate

value

of an attribute

or a variable

within

a

prccess.

Ptoportion

hf?ctive

The ratio

of the

defective

to the

sample size,

rc,presented

y

the symbolp.

p-bar

p

) rcpresenis he

average

Ja sericu

or

values

tp,

Qlrlliy

Meeting

hecustomer

equirements.

R The ange

fvalues

n a sample.

R-rar

R)

The

symbol or

ihemean

f a series

f sampleanges.

F The

median f

sampleanges.

Randofi

causes The contributions

to vadation

which

are random

in

theirbehaviour,

.e.

not structured

r assitnable.

RangeR) Thedifference etweenhe argestand he smallest esult n

a

Eample f individuals

an approximate

ndeasy

measur€

I the de$ee

oI

scatter.

Rafige

hort A gaph\Njth

control

lines

used o monitor

ihe precision

of a

process,

eing assessed

y

a

plot

of

sample anges.

Rm A s€t

of

results

which

appea$

to lie in

an order€d

series.

R

cirl, A graph

wirh contlol

lines used

o plot individuat

iesulrs.

Sahple

is

often

of the

w

Sample

or the

si

Scattet

Scatter

the

othe

Shewh

posedby

Sigma

o

a popul

Six

sigtt

focussin

Stuwed

about

h

Special

SpeciJic

inputsor

Spnlad

SQC

St

on produ

Stuble

n

Stable

on

chartand

Standad

deviation

Standa

el

ure

of

th

rePresent

Statistical

the

origin


6/8

a

Tppend

es 447

SdrTph A group of individunl rcsults,obsenationsor data. sample

is oftcn

used or assessm€nt ith a licw

to determining he properties

of thc whole population

or univcrbc rom

which it is drawn.

Sn

rylcsize

n)

The

number of indiv ualresults

ncluded n a sarnple,

or thc

sizcof the sample aken.

S.iitfcr Rcfers o

the dispersionof a distribution.

ScattrtLliagrnm Th€ picturc {,hich results

'hen simultancous

esulis

for

h\rc varyint param€tcrsare plotted

together/ ne on thc r

axis and

theother on the

v

axis.

Sh.lrlhart

hltts

Thecontrolchnrts or

a tributesand varhb lcs irst pro

posed

by Shewhart. hcsc nclLrdemean

and range, p, p,. and

r/ charts.

sn,'d

(d)

The

Creek eit€r used k) signify

the standarddcviati()n

of

-Sijr

sLg , A disciplined

approach for improving performance

bv

focussinS n producingbetterproducts

nnd soviccs faster

and chcnp.'r.

Skttrcd islribuliott A frcquency

distribution r41ich s not

symmerrical

about hcmc.rn . lue.

SPC SccStntistical rocess

oitrol.

Sfr0nl fnrs(N

SccAssignablc auscs.

Sl)cct1.'rtuirrThc relluirement

against which thf acceptability

of thc

inputs or ouiputs of a process ro k) b(' udgod.

Spard lt{rfcrs o the dispersion

ofn distribution.

SQC

Statisticalqualitycontrol

-

similar

to SPCbut with an emphasis

on product qu.ility

and less€mphasison proccss

onirol.

St,b/. The erm used odescribca proccss

when noeviLlence

a.ssign

ablc causess present.

Stdbl.'rott' The centralzone

between ho warning limiis on a

control

chart and within which most of ihc rcsults

are expected o fall-

Stnru1afl1

f i|tion

(o)

A measufeof thc

spreador scatterof a popula-

tion around its

central tendency.Various

cstimatesof the standard

deviationair ropresented y symbolssuchas d, diri r)and s.

Standd el

)r

The standarddeviation

ofsample meanvtrlues-a mcas-

urc oi their spread or scatter

around the

grand

or processmcan,

rcpresented y the symbol

SE

or

di).

Statisti?l canttol A

cond tion des{dbing a prGess for

which th€ observed

valuesare scattefed

bout a mean value n such

a way as o imply that

theoriBinofthe variaiions

s entirely andom with no

assignable auses

ol variation an.l no runs

or trends.


7/8

I

I

c la

Stal rs t icalrocess

onl rot

Statistical laccss ontlal The us€ of sratistically asedrechniquesor

the control

of a process

or

hansfomint

inputs

nto

outputs.

Sfallsti.s The

colleciion

and use

of data

-

methods

of distillin8

infor-

mation

from

data.

f The

valu€ of

d statistic

alculated

o test

the significance

f the djf_

f€rcnce

etw€en

haromeans.

T

Asymbolused

to repres€nt

toterance

imit

(1?).

Ir l /ui4r4

A.implcto,, l

or

e(

^rdLnF,

\(nts

ds he)

o.curortoe\fract

trcquencies

r,)m

\ist intsisrs

r

data

ftrycf The objective o be achi€vedand againsrwhich pcrformance

will be

assessed,

ften thc mid-point

of a

specification.

Tblerance

The

d,lffercnce

etween

he lowest

and/or

the

highestvalue

stated

n the

specification

nd the

mid-point

of the

specification.

?erd

A series

of rcsults which

show

an upward

or downward

tendency.

ll crarf

Acontrolchart

used

or attributes

when

the

sample

size s not

constant

and only

the number

of non-conformities

s

kn;wn.

,1 s the

symbol wfuch

represents

he

numb€r

of non-conformities

ound

in a

single

sampleand -bar (t)

r€presents

he meanvaluc

of r.

UAI

Upper

action imit

or line.

IJCL

Upper control

irhit

or line.

llri.,e/se

SrePopulation.

USL

Upper specification

imit.

UIVL Upper

waming limit

or line.

V-ftarft

_A

device

used n

conjunction

with

a cusum

chart

to identify

trends

of known

significance.

Varitble ata

Datawhich

is assessed

y

measurement.

Vatianca A measure of spread equal to the standard deviation

squarcd

d:).

Variatiotl

The

inevitable

differences

b€tweer

ourpurs.

Waming

Linit

(liae)

Lines

on a control

cha4

on each

side

of the cenhal

Iine-

and within

which most

results

are

expected

to fatl but

beyond

which

the

probabiljty

of finding

anobseffation

s such

hat t should

be

regarded

as a waming

of a possible

problem

X

(r

,\ :

X-

i

X

Z

z.


8/8

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i&

l \ ' r r r , r , .

r r r ,

I r ( / rnx,s

rr

. r r r l f , ) l

n.Liorr , , i i ls , )

nl

\ i t l r n r \

r l ,h I r . \L, l l

ApNeid

rs

i tJ l t

L r r t l rct$1,fn lr . r ' , rr ) r r r . r r r l j ( ,

{ r i tgt \ i \

t r ,

l rNsr l r i l

\ rn

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r , \ ' r

i f t l i \ i ( lL / , r

. r lu f , ) l

, r \ , , i r . r l j l ( .

I i r r

r \ r l lx

lr( . ,1r \ . r

( ,

(Jl

, . . , , I j l r t ( . ,

j )nr( . t , , , , , \

t r . . . \ j j r t r j

\

l , , r l

\ / r , / ,

1 ' , r r \ r

lh |

r ; r . | r r i or

l ,

r \ ( . r rr i | .

: ( f I1.r1, , , , , .

I r .

r \ r) j t r j

I l l r .nr( \ l

, , i \ , r

L i , . , , r

i : , | |1 ,1.

\ lhrgr, rrr , lor l , r \ t ,s. . , , r .LI i , r I \ i l r ( . , i l , r \ i r j r f t , .

, / l l , ( . : l , l r l . r , l r1t \ l

, i , , r i , r

\ , i , . r t ( .

t r . | |nr l . , , , t

: t , r , rL i , rn, t , , \ i , l

l r i r rs

l ,1s(r . I

lh( nojrr . t

, j l j j r l , j l

L l

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r

L I

. , l l j t t j ( . r

, t ( r \ l

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1. ,

( I

r ,

I l r f l r .

/ i r rr l

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l , l i l ( \ i ( t j i t , . r . l ( t - . l , i ,nr, r t , , j .L \ , , t ( ( ,

spc glossary

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