IS 397-4: Method for Statistical Quality Control During Production, Part 4: Special Control Charts by Attributes

27 Pages·2003·2 MB·English

by  Bureau of Indian Standards

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timely dissemination of this information in an accurate manner to the public.
“जान1 का अ+धकार, जी1 का अ+धकार” “प0रा1 को छोड न’ 5 तरफ”
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“The Right to Information, The Right to Live” “Step Out From the Old to the New”
IS 397-4 (2003): Method for Statistical Quality Control
During Production, Part 4: Special Control Charts by
Attributes [MSD 3: Statistical Methods for Quality and
Reliability]
“!ान $ एक न’ भारत का +नम-ण”
Satyanarayan Gangaram Pitroda
““IInnvveenntt aa NNeeww IInnddiiaa UUssiinngg KKnnoowwlleeddggee””
“!ान एक ऐसा खजाना > जो कभी च0राया नहB जा सकता हहहहै””ै”
Bhartṛhari—Nītiśatakam
“Knowledge is such a treasure which cannot be stolen”

IS 397 (Part 4): 2003

Indian Standard
METHODS FOR STATISTICAL QUALITY
CONTROL DURING PRODUCTION
PART 4 SPECIAL CONTROL CHARTS BY ATTRIBUTES
(First Revision)
ICS 03.120.30

0 BIS2003
BUREAU OF INDIAN STANDARDS
MANAK BHAVAN, 9 BAHADUR SHAH ZAFAR MARG
NEW DELHI 110002

Price Group 9
December 2003
Statistical Methods for Quality and Reliability Sectional Committee, MSD 3
FOREWORD
This Indian Standard (Part 4) (First Revision) was adopted by the Bureau of Indian Standards, after the draft
finalized by the Statistical Methods for Quality and Reliability Sectional Committee had been approved by the
Management and Systems Division Council.
The efficacy of control charts m regulating production is quite well known. Part 2 of this standard covers
traditional control charts forattributes. ThisPart4ofthestandard dealingwith special control chartsbyattributes
has been prepared for use inthose circumstances wherein the traditional control charts are not applicable, less
efficient or more time consuming.
Sincethebasicphilosophy fortheuseofcontrol chartsinmanufacturing operations remains unaltered-irrespective
ofthetype of chart used, this Part 4 should beread along with Part 2 forobtaining an integrated approach tothe
theory and practice of control charts.
Part 2 of the standard is therefore necessary adjunct to this standard since many of the basic principles inthe
construction of control charts and their interpretation explained inPart 2have not been repeated.
This standard wasoriginally published in 1987. Inviewofthe experience gained withthe useofthis standard in
course ofyears, itwasfeltnecessary torevisethisstandard soastomaketheconcepts more up-to-date. Following
changes have been made inthis revision:
a) Demerit control chart has been included,
b) Standardized p-chart has been included, and
c) Many editorial mistikes have been corrected.
Inaddition to this Part, IS 397 has the four parts. The other parts are:
IS No. Title
397 Methods for statistical quality control during production:
(Part O):2003 Guidelines for selection of control charts (jirst revision)
(Part 1): 2003 Control charts for variables (second revision)
(Part 2): 2003 Control charts for attributes and count of defects (third revision)
(Part 3) :2003 Special co n trol charts by variables (&w revision)

The composition of the Committee responsible for the formulation ofthis standard isgiven inAnnex B.
IS 397 (part 4): 2003
Indian Standard
METHODS FOR STATISTICAL QUALITY
CONTROL DURING PRODUCTION
PART 4 SPECIAL CONTROL CHARTS BY AITRIBUTES
(First Revision)
1 SCOPE judgment by the timely identification of the ‘vital’
situations requiring action. This system is essentially
Thisstandard (Part 4) describes thefollowing control
a quality information feedback and i$based on the
‘k-+” .vith examples:
routine inspection data and as such it involves no
Master control systems chart for controlling additional effort.
the quality during production and
4.2 The two main features of master control systems
determining significant cause(s) of variation
chart are asfollows:
affecting quality.
a) Master control sheet, and
Demerit control chart.
b) Principle of pyramiding.
Standardized p-chart.
4.2.1 Master Control Sheet
2 REFERENCES
4.2.1.1 The master control sheet canbe explained best
The following standards contain provisions, which by an example from speedometer assembly. Table 1
through reference inthis text constitute provisions of forms a typical master control sheet.
this standard. Atthe time ofpublication, the editions
4.2,1.2 The lower portion ofthe master control sheet
indicated were valid. All standards are subject to
containsatableandupperportion achart (seeTable 1).
revision and parties to agreements based on this
The main body of the table gives the number of
standard are encouraged to investigate the possibility
non-conformities on each day due to various types of
of applying the most recent editions of the standards
non-conformities, such as, incorrect reading,
indicated below:
sticking and carried oscillation. The total number of
IS No. Title non-conformities, number ofunitsproduced eachday
397(Part 2): 2003 Methods f o r statistical quality and number of non-conformities per 100 units are
control during production: Part2 entered inthe COIS27, 28 and 29ofTable 1.Col29of
Control charts for attributes and Table 1gives the standard values of average number
count of defects (third revision) of non-conformities per 100 units for each type of
7920 Statistical vocabulary and non-conformity, based onpastexperiencefrecords and
symbols: usedforcalculating the control limits for the current
(Part 1): 1994 Probability andgeneral statistical month. Col 28 of Table 1gives the actual values of
terms (second revision) average number ofnon-conformities per 100units for
each type of non-conformity during the month.
(Part 2): 1994 Statistical qualitycontrol(second
revision) 4.2.1.3 While writing down the number of non-
conforrnities, theupper control limit(t/CL) andlower
3 TERMINOLOGY
control limit (LCL), corresponding to the number of
For the purpose ofthis standard the definitions given units produced and the standard value of average
inIS 7920 (Part 1)and IS 7920 (Part 2) shall apply. number of non-conformities per 100 units, are
calculated with the help of following relationship:
4 MASTER CONTROL SYSTEMS CHART
E Ci
4.1 Master control systems make use of enormous Central line (CL) =E F=—
amountofattribute typeofdata for designing aquality () n
control systemsoastoprovide afactualbasisonwhich
production people should act to prevent non-
conformities, serve asan instrument of accountability
for supervision at all levels and provide an aid to LCL = .?-3 (loo~)~
Table 1 Main Assembly Speedometer
(Clauses 4.2.1.1,4.2.1.2,4.2. 1.4and4.2. 1.7)
,,
Dates~ 2 3 4 5 6 7 9 10 11 12 13 14 16 17 18 19 20 21 23 24 25 26 27 28 29 Corrected ~ Standard
Non-conformities Total z
:)
(2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15) (16) (17) (18) (19) (20) (21) (22) (23) (24) (25) (26) (27) (28) (29)
Incorrectreading 11 18 24 19 24 52 42 35 29 9 41 32 15 29 30 23 28 23 26 73 42 12 23 31 50 551 5.32 5.63
Sticking 3618141883 4526 ~5628412 11 25 6 14 4 12 151 1.33 1.49
Carriedoscillation 6 2 0 0 23 6 4 19 15 13 23 14 10 9 11 23 5 10 12 5 8 3 1 5 13 171 1.74 1.92
O-Mark 30 FTO 04000 00000000 0 0 13 6 6 5 14 10 0.10 0.22
Odometer 30 30 27 21 7 11 12 5 3 8 17 12 4 7 14 5 23 26 59 41 19 16 20 5 ~ 275 3.34 3.48
Frontring 4 10 6 8 26 13 12 XT 9 31 9 17 17 19 17 13 12 6 3 6 1 6 2 3 182 1,64 1.90
Glass 9 8 8 6 8 0 9 10 14 11 33 9 1 9 12 9 11 7 1 14 10 8 5 2 0 171 1.43 1.55
Dial 32300042 20128241 94120401 7 38 0.35 0.44
Pointer 596387116 839075312 82484002 0 130 1.04 1.04
Dialshiftorslant 55123 1104027 6245154 6877132 89 0.71 0.75
Ratio 00000200 00100000 04030000 0 1 0.01 0.05
Otherdefects 6 19 12 9 13 7 9 10 15 16 15 19 13 12 15 17 25 15 17 11 13 20 8 11 26 327 2.73 2.73
Freeplay 131315127604 7101260254 831106460 4 145 1.20 1.33
Odoreversenot 12012102 10201210 00000000 0 16 0.13 0.13
working
Lampposition 00011000 00003014 00222020 0 14 0.12 0.14
m Total non- 99 124 131 100 121 114 115 108 96 86 194 115 —86 103 126 112 143 114 147 191 155 87 92 71 133
conformities
Total assembled 386 555 547 534 433 414 612 548 531 305 524 377 588 536 441 591 548 440 478 634 605 427 S22 411 486
No.of Non- 25.6 22.5 23.9 18.7 27.9 27.5 18.6 19.7 18.1 28.2 37.0 30.5 14.6 19.2 28.6 19.0 26.1 25.9 30.8 30.1 25.6 20.4 17.6 17.3 27.4
conformities
per 100units

----
UCL

A CL
-----” ----- .... .. .. ...- - LCL
$
04
=
1 234567 8910111213141516 171819202122232425
OAY
CONTROL CHART
IS 397 (Part 4) :2003
where FIisthe standard value of the average number with amaster control sheet pertaining tohis sphere of
ofnon-conformities per 100units and nisthe number responsibility. Persons at the lower levels of the
of units produced. organization havetoactually initiate corrective action.
Hence the information given to them should be more
NOTE—Tofacilitate computations, UCLandLCLhavebeen
pin-pointing. At higher levels, unnecessary details
computed inAnnexA.
shall be avoided and information just sufficient to
4.2.1.4 Ifthenumber ofnon-conformities exceeds the monitor the situation be provided.
upper control limit, a continuous circle is put around
4.2.2.2 Figure 1 illustrates how the principle of
the actual number of non-conformities and it falls
belowthelowercontrol limit,thedotted circleisdrawn. pyramiding for master control systems works. Charts
At the end of the month, the figures in each row are 1through 11are the foremen’s charts. Chart 12-isfor
added horizontally eliminating the figures which are vendor non-conformities. Chart 13 is for non-
conformities whose sources are undetermined, design
circled and the average number of non-conformities
per 100units calculated and written down inCO128 quality and comprising standards. Charts 14through
17are the charts for the superintendents. Charts 18
of Table 1.The new set of average number of non-
and 19are for the assistant managers. Chart 22 isfor
conformities per 100 units so calculated is compared
with the corresponding standard values.This new set the manager, the apex of the pyramid. Number 20 is
forinspectionand21isforengineering. Theforemen’s
ofcalculated values istaken asstandard values forthe
totals are pyramided to form the superintendent’s
next month provided these do not exceed the
charts. The superintendent’s totals are likewise,
corresponding standard values for the current month.
In case of significant increase in the average number pyramided toformtheassistant manager’s charts. The
twoassistant manager’s totals andthetotals forvendor
of non-conformities per 100 units for any particular
non-conformities and engineering non-conformities
non-conformity, corrective actions are initiated.
are pyramided to form the manager’s chart.
4.2.1.5 Intheupper portion ofthemaster control sheet,
4.2.2.3 Table 2 shows the manager’s control chart for
thatisthecontrol chartfornumber of non-conformities
December. It can be observed that the total for the
per 100 units are plotted. Once again, points out of
manager is out of control on the high side for.3
upper control limitarecircled continuously and those
outoflower control limit arecircled withdotted lines. December. This could berapidly traced downthrough
the pyramid to the three principal non-conformities at
While acontinuous circle in amaster control sheet is
fault simply by following the continuous circles.
anindication forthe concerned supervisor oftheneed
forimmediate action, value ofany dotted circleshould Figure 2 shows the excerpts from the master control
not be underestimated. A dotted circle represents a systems that pin-point these three causes.
change for better performance. Ittells the supervisor 4.2.2,4 The-lowerthe levelofthechart inthepyramid,
that opportunity existsto discov e r the causeandmake the more sensitive the control becomes. Hence, the
ita permanent feature inthe proces s. men who need to take action have the pin-pointing
4.2.1.6 Insteadofnumber ofnon-conformities wherein information to guide them daily. As the level in the
pyramid becomes higher, the more details are
equal importance is given to each type of non-
conformity, average demerit score may.becalculated eliminated. The charts are so directly connected to
each other that the entire data directly below aperson
bygivingdemerit scoretoeachtype ofnon-conformity
(depending upon its criticality). For fhrther details, in the pyramid becomes easily and immediately
see 5. available to him at his discretion.
4.2.1.7 One important feature of the master control 4.2.2.5 The importance ofeachsenior discussing each
sheet is the increases in sensitivity obtained by the circle on his chart daily with the subordinates
breakdown of the total number of non-conformities. concerned cannot be over-emphasized. Any person
As may be seen from Table 1, the frequency of inthepyramid canactivate that portion directly below
occurrence for out of control points daily for total him by following the rule. A plant manager thus
number of non-conformities during the month is far devoting afewminutes per daycanbe assured that all
lessthanthatofeachtypeofnon-conformity. Breaking the meninhis organization areregularly investigating
downthenon-conformities duetoindividual operations andtaking action ontheout-of-control conditions that
or sources could increase the sensitivity further. are indicated by their respective charts.
4.2.2 Principle of Pyramiding 4.3 Examples
4.2.2.1 The central idea behind the principle of The master control sheet is firther illustrated with a
pyramiding isthat, as far as practicable, each person variety ofexamples. Table 3gives the master.control
inthemanufacturing organization should beprovided sheet for a textile mill manufacturing sarees wherein
3
IS397 (Part 4): 2003
22
MANAGER
T FE
I
1 I
[
TTV7
I
r---
v)
.!4
.g
3 7
FIG. 1PYRAMIDIZATION OFINFORMATION

department-wise (weaving, dyeingan d printing) break- conformities. However, if the number of classes of
up of non-conformities ;Sgiven. Table 4 gives the non-conformities increase, itmay be ditllcult to have
master control sheet for one of these departments, so many control charts simultaneously. A simpler
namely,dyeingdepartment. Table 5isamaster control solutionistogivethedifferent demerit rating(weights)
sheet for a blade section wherein source-wise break- to each class of non-conformities and calculate the
up ofrejections is given. demerit score for each item. This demerit score may
be plotted onthe demerit control chart.
5DEMERIT CONTROL CHART
5.2 Incaseofdemerit score;the underlying distribution
5.1 In case of control chart for number of non- isalso Poisson type. The non-conformities are given
conformities, all the non-conformities on an item are weights since alltypes of non-conformities cannot be
counted and plotted on the control chart. This chart treated alike. The criteria for selection of demerit
has a disadvantage that it gives equal importance to weights isdiscussed in 5.2.1.
eachclassofnon-conformities. Butthe different non-
5.2.1 The method for selection ofdemerit weights for
conformities are unequal in their influence on costs.
various non-conformity depends on the type of
Somemaybe corrected bysimple inexpensive rework
products under consideration, Broadly, there are two
operation, othermayrequire costly rework, stillothers
typesofproducts. Inthe first instance, itispossible to
may involve the scrapping of the items inspected. A
rectify a non-conformity by either replacing a
practical solution to this problem is to classify the
component or by carrying out suitable rework. The
various non-conformities into some broad categories,
products of engineering industry involving assembly
like critical, major and minor non-conformities and
run separate control charts for each class of non- of large number of components is an example of this
4
IS 397 (Part 4) :2003
MANAGER (22)
I 100 p I I Actual No. ofDefectives I
3.7 AssistantManager(18) 180
1.4 AssistantManager(19) 56
0.3 Vendor 18
4.6 Engineering 142
10.0 Total 396
Assistant Manager (IS)
100p Number
2.1 Superintendent(14) 98
1.6 Superintendent(15) 82
3.7 Sub-total 180
v v
Superintendent (14) Superintendent (15)
100p Number 100p Number
0.5 Currentcoil 54 0.6 Electromagnet 20
1.4 Resistors 34 1.0 Testandrepair 62
0.2 Potentiometer 10 1.6 Sub-total 82
2.1 Sub-total 98

Current Coil Test and Repair
100p Number 100p Number
0.35 Rubber flows 46 0,2 Digitoffzero 3
0.10 Bentloads 6 0.3 Screwsloose 25
0.05 Miscellaneous 2 0.4 Pointeroffzero 32
0.50 Sub-total 54 0.1 Miscellaneous 2
1.0 Sub-total 62
FIG.2 BREAKDOWN OFREJECTIONS
type. Inthe second situation, itmaynotbepossible to Theapproach forselection ofdemerit weights forboth
carryouttherectification oftheend-product. Thepart the situations isexplained below.
ofthe end-product or item isgraded inthree or more
5.2.1.1 Incasesofthe firsttype ofproduct, the choice
grades and sold as such. The textile products are
examples of thix category. Most of the non- of demerit weights (wi) depends generally on the
conformities that arise inweaving, finishing, printing, criticality of the non-conformity, which is generally
etc, of fabric are graded and sold at varying prices. determined by taking into account various aspects of

5