ASTM E300-03(2022)

This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the
Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.
Designation: E300 − 03 (Reapproved 2022)
Standard Practice for
Sampling Industrial Chemicals
This standard is issued under the fixed designation E300; the number immediately following the designation indicates the year of
original adoption or, in the case of revision, the year of last revision.Anumber in parentheses indicates the year of last reapproval.A
superscript epsilon (´) indicates an editorial change since the last revision or reapproval.
This standard has been approved for use by agencies of the U.S. Department of Defense.
1. Scope 2. Referenced Documents
2.1 ASTM Standards:
1.1 This practice covers procedures for sampling several
D270Methods of Sampling Petroleum and Petroleum Prod-
classes of industrial chemicals. It also includes recommenda-
ucts (Withdrawn 1984)
tionsfordeterminingthenumberandlocationofsuchsamples,
D2234/D2234MPractice for Collection of a Gross Sample
to ensure their being representative of the lot in accordance
of Coal
with accepted probability sampling principles.
E180Practice for Determining the Precision of ASTM
1.2 Although this practice describes specific procedures for
Methods for Analysis and Testing of Industrial and Spe-
sampling various liquids, solids, and slurries, in bulk or in
cialty Chemicals (Withdrawn 2009)
packages,theserecommendationsonlyoutlinetheprinciplesto
be observed. They should not take precedence over specific
3. Terminology
sampling instructions contained in other ASTM product or
3.1 Definitions:
method standards.
3.1.1 simple liquid—a single-phase liquid having a Reid
1.3 These procedures are covered as follows: vaporpressureoflessthan110kPaat37.8°C(16psiat100°F)
and a Saybolt viscosity of less than 10 000 s (2160 cSt) at
Sections
Statistical Considerations 7–11
25°C.
Simple Liquids 12–27
3.1.2 lot—a discreet quantity of material. It may contain a
Solids 28–35
Slurries 36–41
singlebatchorseveralbatches,orbetheproductofcontinuous
processbrokenintounitsonthebasisoftimeorshipment.Itis
1.4 This standard does not purport to address all of the
very desirable that individual batches in a lot be specifically
safety concerns, if any, associated with its use. It is the
identifiedsothattheymaybecomeindividualorstratifiedunits
responsibility of the user of this standard to establish appro-
for inspection.
priate safety, health, and environmental practices and deter-
mine the applicability of regulatory limitations prior to use.
3.1.3 average sample—one that consists of proportionate
Specific precautionary statements are given in Sections 6, 19,
parts from all sections of the container.
20, 30, 34 and 37.
3.1.4 spotsample—asampletakenataspecificlocationina
1.5 This international standard was developed in accor-
tank or from a flowing stream in a pipe at a specific time.
dance with internationally recognized principles on standard-
3.1.5 composite sample—a blend of spot samples mixed in
ization established in the Decision on Principles for the
proportion to the volumes of material from which the spot
Development of International Standards, Guides and Recom-
samples were obtained.
mendations issued by the World Trade Organization Technical
3.1.6 all-levels sample—one obtained by submerging a
Barriers to Trade (TBT) Committee.
closed sampler to a point as near as possible to the draw-off
level,thenopeningthesamplerandraisingitataratesuchthat
This practice is under the jurisdiction ofASTM Committee D16 on Aromatic,
Industrial, Specialty and Related Chemicals and is the direct responsibility of For referenced ASTM standards, visit the ASTM website, www.astm.org, or
Subcommittee D16.08 on Handling and Sampling Aromatic and Cyclic Hydrocar- contact ASTM Customer Service at service@astm.org. For Annual Book of ASTM
bons. Standards volume information, refer to the standard’s Document Summary page on
CurrenteditionapprovedJuly1,2022.PublishedJuly2022.Originallyapproved the ASTM website.
in 1966. Last previous edition approved in 2017 as E300–03 (2017). DOI: The last approved version of this historical standard is referenced on
10.1520/E0300-03R22. www.astm.org.
Copyright © ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959. United States
E300 − 03 (2022)
TABLE 1 Sampling Instructions for Horizontal Cylindrical Tanks
it is about three fourths full as it emerges from the liquid. An
all-levels sample is not necessarily an average sample because Sampling Level, Percent of Composite Sample
Liquid Depth,
Diameter Above Bottom Proportionate Parts of
Percent of
the tank volume may not be proportional to the depth and
Diameter
Upper Middle Lower Upper Middle Lower
becausetheoperatormaynotbeabletoraisethesampleratthe
100 80 50 20 3 4 3
variable rate required for proportionate filling. The rate of
90 75 50 20 3 4 3
filling is proportional to the square root of the depth of
80 70 50 20 2 5 3
immersion. 70 . 50 20 1 5 4
60 . 50 20 . 5 5
NOTE 1—The tube sampling procedure, 26.3, may be used to obtain an 50 . 40 20 . 4 6
all-levels sample from a drum. 40 . . 20 . . 10
30 . . 15 . . 10
3.1.7 upper sample—a spot sample obtained from the
20 . . 10 . . 10
middle of the upper third of the tank contents (Fig. 1). 10 . . 5 . . 10
NOTE 2—The taking of samples from various levels of the tank permits
the detection of variation in composition of the contents caused by
stratification. If it is known that the contents are not subject to this
variation, the taking of samples at multiple levels may be eliminated.
3.1.13 outletsample—aspotsamplenormallyobtainedwith
3.1.8 middle sample—a spot sample obtained from the
the inlet opening of the sample apparatus at the level of the
middle of the tank contents (Fig. 1)(Note 2).
bottom of the tank outlet (either fixed or a swing line outlet)
3.1.9 lower sample—a spot sample of liquid from the
(Fig. 1).
middle of the lower one-third of the tank’s content (a distance
3.1.14 continuous sample—a spot sample obtained from a
of one-half of the depth of liquid below the liquid’s surface)
pipeline conveying the product in such a manner as to give a
(Fig. 1).
representative average of the stream throughout the period of
3.1.10 single-tank composite sample—a blend of the upper,
transit.
middle,andlowersamples.Foratankofuniformcrosssection,
3.1.15 jar sample—a spot sample obtained by placing a jar
such as an upright cylindrical tank, the blend consists of equal
into the path of a free-flowing stream so as to collect a definite
partsofthethreesamples.Forahorizontalcylindricaltank,the
volume from the full cross section of the stream.
blendconsistsofthethreesamplesintheproportionsshownin
Table 1. 3.1.16 mixed sample—a spot sample obtained after mixing
orvigorouslystirringthecontentsoftheoriginalcontainer,and
3.1.11 compartment-tank composite sample (ship, barge,
then pouring out or drawing off the quantity desired.
etc.)—a blend of individual all-levels samples from each
compartment, which contains the product being sampled, in
3.1.17 tube or thief sample—a spot sample obtained with a
proportion to the volume of material in each compartment. sampling tube or special thief, either as a core sample or spot
sample from the specified point in the container.
3.1.12 top sample—a spot sample normally obtained 150
mm (6 in.) below the top surface of the tank contents (Fig. 1).
3.1.18 drain sample—a spot sample obtained from the
draw-off or discharge valve. Occasionally, a drain sample may
be the same as a bottom sample, as in the case of a tank car.
3.1.19 bottom sample—a spot sample obtained from the
material on the bottom surface of the tank, container, or line at
itslowestpoint(Fig.1).(Drainandbottomsamplesareusually
taken to check for water, sludge, scale, etc.).
3.1.20 laboratory sample—thatportionofthesamplewhich
is sent for laboratory testing.
4. Summary of Practice
4.1 This practice describes procedures to be followed for
obtaining samples of several classes of industrial chemicals. It
addresses in detail the various factors which need to be
considered to obtain a representative laboratory sample. This
practicealsocoversthestatisticalconsiderationsinsamplingof
industrial chemicals whether they are liquids, solids or slurries
in bulk or in packages.
5. Significance and Use
5.1 Representative samples of industrial chemicals are re-
quired for the determination of chemical and physical proper-
ties which are used to establish standard volumes, prices, and
FIG. 1 Sampling Depths compliance with commercial and regulatory specifications.
E300 − 03 (2022)
5.2 The objective of sampling is to obtain a small portion STATISTICAL CONSIDERATIONS
(spot sample) of material from a selected area within a
7. Objectives
container which is representative of the material in the area or,
in the case of running or all-level samples, a sample whose 7.1 The sampling and testing of industrial chemicals may
composition is representative of the total material in the
have one or more of the following objectives:
container.Aseries of spot samples may be combined to create 7.1.1 The objective may be to estimate the average quality
a representative sample.
characteristic of a given lot of material and to establish
confidence limits for this average. This would be the main
5.3 Manual and Automatic Sampling Considerations—The
objective, for example, if a dollar value is to be placed on the
selection of manual or automatic sampling devices is part of
material for customs purposes or for sale.
establishing a sampling plan applied under all conditions
7.1.2 The objective may be to decide whether the average
within the scope of this practice provided that the proper
value for the lot meets a specification. This calls for an
sampling procedures are followed. Both types of sampling are
acceptancesamplingplanwiththecriterionbeingrelatedtothe
commonly used for liquid, solid, and slurry sampling and
estimated mean of the lot.
require adherence to the following:
7.1.3 The objective may be to estimate or make decisions
5.3.1 An adequate frequency of sampling must be selected.
about the variability of a quality characteristic within the lot.
5.3.2 The equipment to support manual or automatic sam-
7.1.4 Theobjectivemaybetoobtainsimultaneousestimates
pling systems may be obtained commercially, fabricated from
ofthemeanandvarianceortomakedecisionsaboutsomejoint
the designs presented in this practice, or constructed as needed
combination of these estimates.
to satisfy process design or other specific requirements.
7.1.5 Ifthematerialcomesincontainersorcanbeviewedas
5.3.3 The sampling equipment must be maintained on a coming in clearly demarked units, the objective may be that of
regular basis, and the sampling plan adopted must be strictly
estimating the number of such units outside of specifications,
followed. that is, the “fraction defective.”
NOTE3—Proceduresaregivenbelowforestimatingaveragequalityand
6. Safety Precautions
for applying acceptance sampling inspection based on the lot mean.
6.1 This practice covers procedures and sampling equip-
8. General Sampling Considerations
ment used to sample industrial chemicals that may be poten-
8.1 To obtain samples that are representative in a statistical
tially hazardous to personnel or the environment.Accordingly,
sense, one must consider such factors as physical form,
it is emphasized that all applicable safety rules, regulations,
uniformity, type and number of containers, etc. All of these
and procedures must be followed in handling and processing
factors influence the choice of method for performing the
the chemicals. Furthermore, this practice does not purport to
sampling operation, as well as the number and location of the
cover all safety aspects associated with sampling. However, it
required samples. Two commonly used practices for selecting
ispresumedthatthepersonnelperformingsamplingoperations
the sequence or location of the individual samples are de-
are adequately trained with regard to safe application of the
scribed.
procedurescontainedhereinforthespecificsamplingsituation.
8.2 RandomSamplingisachievedwheneverypartofthelot
6.2 The characteristics of the material to be sampled will
has an equal chance of being drawn into the sample.
govern the type of protective equipment required. Since
8.2.1 Designate all units in the lot, choosing numbers in
sampling may present such hazards as splashing or spilling,
sequence or other serial code so that sampling by random
protectiveclothingmustbewornwhenthechemicaliscapable
numbers can be employed.
of producing eye or skin irritation or burns. During such
8.2.2 Preferably,thissequenceshouldbeindirectrelationto
potential exposures, chemical-type goggles or face shield and
orderofmanufactureofpackagingasanaidtoobserving,from
protective gloves, or combination thereof, must be worn.
the sample results, any evidence of stratification.
6.3 Respiratory protection, where required, must be in good
8.2.3 Random selection of the numbers should be accom-
condition and must be suitable to protect against chemicals plishedbychanceorpreferablybytheuseofatableofrandom
being handled.
numbers.
8.3 StratifiedSamplingcanbeemployedtoestimateaverage
6.4 When sampling chemicals that may be dangerous to life
quality when it is known or suspected that the value of a
by skin absorption, oral ingestion, or by breathing the vapor,
propertyofthematerialvariesinnon-randomfashionthrough-
unusual precautions will be indicated. In such cases, full-body
out the lot for the following typical reasons: (a) the lot may
protection such as supplied by a gas-tight or one-piece air-
supplied suit should be worn. A second person must be
continuously present to summon help and render aid in the 4
Prepared by an Ad Hoc Committee of ASTM Committee E11 on Statistical
event of an emergency. Methods.
E300 − 03 (2022)
2 2 2
contain several production batches, (b) the lot may contain σ 5 σ /n 3 N 2 n /N 1 σ /n (2)
~ ! @~ ! # ~ !
x¯ b b b t t
units produced by different procedures, equipment, shifts, etc.,
9.1.3 If n =N, Eq 1 and Eq 2 reduce, respectively, to Eq 3
b
or (c) the lot may be non-uniform because of subsequent size
and Eq 4:
segregation, moisture pickup, surface oxidation, etc. If the
2 2 2
σ 5 σ / n 3n 1 σ /n (3)
assumedpatterniscorrect,thevarianceofthepopulationmean
@ ~ !# ~ !
¯x w b w t t
estimatewillbelessthanthatbasedonrandomsampling.Ifthe 2 2
σ 5 σ /n (4)
x¯ t t
assumptions are incorrect, the estimate of the mean may be
9.2 Determination of n,n , and n When Basic Variances
b w t
biased. A stratified sample can be obtained as follows:
2 2
are Known—Whenreliableestimatesofthevariances σ , σ ,
b w
8.3.1 Based on the known or suspected pattern, divide the
and σ are available from experience with lots of the type
t
lot into a number of real or imaginary strata.
involved,asetofequivalentcombinationsofn ,n ,andn may
b w t
8.3.2 If these sections are not equal in size, the number of
be calculated from Eq 1, each combination based on the same
samples to be taken from each stratum must be proportional to
desiredorspecifiedvarianceofthemean, σ .Similarly,setsof
x¯
the size of the various strata.
equivalent combinations may be calculated from Eq 2 and Eq
8.3.3 Further subdivide the major strata into real or imagi-
3.
nary subsections and select the required number of samples by
chance or preferably by means of a table of random numbers.
NOTE6—Iftheprecisionofthetestmethodhasbeenproperlyevaluated
in accordance with Practice E180, an adequate estimate of σ can be
t
obtained from the repeatability standard deviation (s ) based on approxi-
9. Estimate of Average Quality a
mately 30 degrees of freedom.
9.1 DeterminationoftheVarianceofaSampleMean—Ifthe
9.2.1 Choice of a particular combination in a set for a
material comes in, or can be viewed as coming in, realizable
specific lot is optional. In general, one combination in a set is
primary units, each of which are to be divided into realizable
most economical under given cost conditions and is therefore
secondary units, and if n primary units are selected at random
b
to be preferred.
from a lot of N primary units, and if n secondary units are
w
selected from each primary unit with k tests being made on 9.3 Procedure When Basic Variances are Unknown:
each secondary unit drawn, then the variance of the mean of
9.3.1 Selectatrandomalikelyorconvenientnumber,n (10
the results is given as follows (Note 4 and Note 5): ormore),ofprimaryunitsfromthelot,takeonesecondaryunit
2 2 2 2 from each, and test each secondary unit. Estimate the variance
σ 5 σ /n 3 @~N 2 n !/N#1@σ /~n 3n !#1 σ /n (1)
~ ! ~ !
¯x b b b w b w t t
of a measurement of a primary unit, s (a variance that
where:
includes between and within unit variability as well as test
σ = variance of the mean, variability), using Eq 5:
x¯
σ = variance of primary units (the material in cars, tanks,
b
2 ¯
s 5 ~X 2 X ! / n 2 1 (5)
~ !
1 1 1
(
cans, drums, bottles, or other containers) in the lot,
σ = average variance of secondary units (all-level, tube,
¯
w where X is the mean of the individual test results on the n
1 1
thief, or similar samples) from a primary unit,
primary units, with one secondary unit per primary unit and
σ = variance of tests on a homogeneous sample,
t
one test per secondary unit.
N = number of primary units in the lot,
9.3.2 Decidetoestimatethemeanofthelotfromsingletests
n = number of randomly selected primary units from
b
on single secondary units from n primary units where n > n
2 2 1
which secondary units are drawn,
and the n units include the n preliminary units, the value on
2 1
n = numberofrandomlydrawnsecondaryunitsfromeach
w
n being determined from Eq 6:
of the n primary units, and
b
n 5 s /T 2 (6)
n = total number of tests made on all units, including
2 1 S x¯
t
replicates.
where T is the target value of an estimate of the variance
S x¯
¯
9.1.1 Eq 1 is also applicable when the n ×n secondary
of X. The target value T 2 will depend on the width of the
b w
S x¯
units are composited into a single sample before testing. If
desired confidence interval. If it is hoped to have a 0.95
thereisnocompositingandktestsaremadeoneachsecondary
confidence interval of width 2∆, then for n > 30, T should
2 S x¯
¯
unit, Xwill be an arithmetic average of n =k×n ×n test
t b w betakenas(∆/1.96) .Forsmallervaluesof n ,the1.96should
results. If the secondary units are composited and k tests are
be replaced by the 0.025 values from a t-table.
c
¯
madeonthecompositesample,Xwillbeanarithmeticaverage
9.3.3 Estimate the variance of the mean after n tests from
of n =k results.
t c Eq 7:
NOTE 4—Uniform quantities (weight or volume, as appropriate) in the
2 ¯
~ !
s 5 X 2 X /n ~n 2 1! (7)
x¯ ( 2 2
primary units and in the secondary units are assumed. If the departure
fromuniformityissuchthatamaterialerrorwouldbeintroducedbyusing
9.4 A Confidence Limits for the Mean of the Lot:
a simple mean, a weighted average should be used or, if the secondary
9.4.1 If the basic variances are known and two-stage sam-
units are composited, proportional compositing must be adhered to.
pling (primary and secondary units) is employed, then 0.95
NOTE 5—The factor (N−n )/N is the correction for sampling from a
b
confidence limits for the mean of the lot µ are given by Eq 8:
finite population. A corresponding correction is generally not necessary
for secondary units and tests.
¯
0.95confidencelimitsforµ 5 X61.96 σ (8)
2 x¯
9.1.2 Forhomogeneousliquids σ =0,sothatEq1reduces
w
to Eq 2: where σ is obtained from the σ value given by Eq 1.
x¯ x¯
E300 − 03 (2022)
A
TABLE 2 Values of Sample Size (n) for Agreed Upon Values
9.4.2 Ifthebasicvariancesareunknownandthevarianceof
of ∆
¯
X is estimated as in 9.3 (n sample primary units with one
s
λ = ∆/σˆ Sample Size (n)
secondary unit per sample primary unit and one test per
2.76 3
secondaryunit),then0.95confidencelimitsforthemeanofthe
2.16 4
lot µ are given by Eq 9:
1.61 5
1.26 7
¯
0.95 confidencelimitsfor µ 5 X6t s (9) 1.00 10
0.025 x¯
0.79 15
0.68 20
where s is obtained from the s value given by Eq 7 and
x¯ x¯
0.54 30
t can be taken as equal to 1.96 if n is greater than 30, but
0.025 2
0.42 50
otherwise should be taken from a table of t-values for n −1
0.33 75
B
0.29 100
degrees of freedom.
A
Values of λ were read from Fig. 13.31 of Bowker and Lieberman, Handbook of
Industrial Statistics.
10. Acceptance Sampling for a Lot Mean—Basic
B 2 2 2
For larger size samples, take n = (2.927) /λ =8.57 ⁄λ .
Variances Unknown
NOTE 7—This section describes a simple random sampling plan for the
acceptance inspection of an isolated lot and provides for buyer’s and
seller’s risks of making a wrong decision. If a series of lots is to be
inspected and knowledge of the basic variances is available, significant
10.2.1.5 Step 5—Randomly select n −n additional units
2 1
savings may be realized by testing composites.
from the lot. Compute
10.1 Introduction—If a specification requires, for example,
n
¯
that the average purity or assay of a lot be no less than 98.0%,
X 5 X /n , and (13)
2 ( 1 2
i51
it it sometimes assumed that the sampling and testing plan will
n
accept all lots of 98.0% or higher, but will detect or reject any
¯
s 5Π~X 2 X! / n 2 1 (14)
~ !
2 ( i 2
lot falling below this value. This ideal situation is not statisti-
i51
cally realistic, as the required degree of discrimination can be
10.2.1.6 Step 6—Check on the adequacy of n by taking
approachedonlyifthelotunitsareessentiallyuniformandthe
σˆ =s . Compute λ = ∆⁄ σˆ . Enter Table 2 and find the value
2 2 2 2
test procedure is capable of attaining a very high level of
ofncorrespondingto λ .Callthisn.Ifn ismuchgreaterthan
2 3 3
precision. It is necessary, therefore, that the contracting parties
n , for example, more than 20%, randomly select n −n
2 3 2
realize that any sampling plan based on a low probability of
additional units from the lot and return to Step 5. If n is not
rejectingalotwhich,infact,is98.0%orhigherinpurity,may
much greater than n , proceed with Step 7.
also permit acceptance of some lots below this specification
10.2.1.7 Step 7—Using the final values obtained above,
minimum.Accordingly, such specifications must be viewed as
calculate the following and accept the lot if
incorporating both a buyer’s and seller’s risk. The following
procedures are based on this concept. ¯
~L 2 X!/ s =n # t (15)
@ ~ !#
x¯ 0.05
10.2 Single Lower Specification Limit (L); Simple Random
where n=n , n,or n , whichever is applicable, t is the
1 2 3 0.05
Sampling from a Large Lot:
upper 0.05 point of a t-distribution for n−1 degrees of
10.2.1 Procedure:
freedom, and s=s or s whichever is applicable. Otherwise,
2 1
10.2.1.1 Step 1—Note the value of the lower specification
reject the lot.
limit for average lot quality and designate it by L.Assume this
10.2.2 Example:
value to represent a quality level for which the probability of
10.2.2.1 Assume that a contract covered the purchase of a
acceptance should be high and the risk of rejection low. In this
packaged material with a minimum purity specification of
procedure, the seller’s risk is taken to be 0.05.
98.0%. The buyer and seller agreed that the probability of
10.2.1.2 Step 2—Establish a lower value for the barely
rejecting a lot of 98.0% purity should be no greater than 0.05
tolerablelotqualityforwhichthelevelofacceptanceshouldbe
and that of accepting a lot as low as 97.0% should be no
low and designate it by L− ∆. Here, this buyer’s risk is taken
greater than 0.10. In this case, the pertinent levels are:
to be 0.10.
L 5 98.0 (16)
10.2.1.3 Step3—Takeapreliminarysampleofn (equals10
or more) units at random from the lot and compute
L 2 ∆ 5 97.0
n
¯
X 5 X /n , and (10)
( i 1
∆ 5 1.0
i51
n
10.2.2.2 On testing samples from ten units, selected at
¯
~ !
s 5ΠX 2 X /~n 2 1! (11)
random, the lot standard deviation was estimated to be:
i ( i 1
i51
s 5 s 50.8 (17)
x¯ 1
Set σˆ 5 s (12)
1 1
¯
The values for X and λ were also calculated:
10.2.1.4 Step 4—Note the value of ∆ agreed to in Step 2.
Compute λ = ∆⁄ σˆ and find from Table 2 the value of n that
¯
1 1
X 5 97.5% (18)
comes closest to that given by the computed value of λ . Call
this n . λ 5 ∆/s 5 1.0/0.8 5 1.25
2 1 1
E300 − 03 (2022)
10.2.2.3 Entering Table 2, the sample size n for λ =1.25 is 11. Acceptance Sampling for the Mean of a Lot from a
found to be 7. Accordingly, no further sampling is required. Stream of Batched Material for Which the Basic
Variances Have Been Previously Estimated
10.2.2.4 Substituting the above values in Eq 15:
11.1 SomeBasicConsiderations—Tounderstandtherecom-
¯
~ ! ~ = ! ~ = !
L 2 X / sx¯/ n 5 ~98.0 2 97.5!/ 0.8/ 10 (19)
mendations of this section, it is helpful to review briefly the
nature of an operating characteristic (OC) curve for an accep-
5~0.5 3=10!/0.8 5 1.97
tance sampling plan.
11.1.1 The OC curve of acceptance sampling plan gives the
Since1.97isgreaterthan1.833(thevaluefortheupper0.05
probability of acceptance of a lot with reference to a hypo-
point of the t-distribution for 9 degrees of freedom), the lot
thetical stream of lots. Two types of streams are generally
should be rejected.
considered.ThesearedesignatedasTypeAandTypeB.AType
10.3 Single Upper Specification Limit (U); Simple Random A stream is a stream of lots that are identical in every respect
to the lot currently being inspected.AType B stream of lots of
SamplingfromaLargeLot—Theproceduresof10.2willapply
thesamesizeasthelotcurrentlybeinginspectedthatwouldbe
hereexceptthat Uwillreplace Land U+ ∆willreplace L− ∆.
generated by a controlled process.When we are faced with the
The criterion for acceptance will be:
inspection of an isolated lot, it seems appropriate to view the
¯
~X 2 U!/ s /=n # t (20)
~ !
x¯ 0.05 risks of the sampling inspection with reference to a Type A
stream. We have little or no knowledge of the process from
10.4 Both Lower and Upper Specification Limits: Simple
which the lot came and a decision on the lot would seem best
Random Sampling from a Large Lot—Use the following
based on data from that lot alone. This is the case considered
¯
sampling plan: Determine n, X, and s as in 10.2.1. Accept the
in Section 10 of this practice; the isolated lot with unknown
lot if
standard deviation.
¯ 11.1.2 Inthepresentsection,referenceistoaprocessthatis
~L 2 X!/ s /=n # t , and (21)
~ !
x¯ 0.05
producing a stream of lots in batches. We assume that the
¯
~X 2 U!/~s /=n!# t (22) within-batchandbetween-batchvariationsareindependentand
x¯ 0.05
random with constant variances and on the basis of these
for n−1 degrees of freedom. Otherwise, reject the lot.
assumptions we run a pilot study of variances that we take to
holdvalidforsubsequentlotsfromtheprocess.Thecurrentlot
10.5 General Remarks:
beinginspectedisrecognizedfromthestartasbeingoneofthe
10.5.1 If ∆ is small relative to the lot standard deviation, a
stream of lots coming from the given process and, as such, we
large sample size will be required to attain the low 0.10
arewillingtouseinformationaboutwithin-batchandbetween-
consumer’s and 0.05 producer’s risks.
batch variances obtained in the pilot study as part of the total
10.5.2 If the estimate of the lot standard deviation is less
information on which a decision about the lot is based. In this
than the true lot standard deviation, the sample size given by
section, therefore, the probability of acceptance will be with
theaboveprocedureswillproduceasamplingplanwhoserisks reference to a Type B stream of lots, that is, with reference to
willbedifferentfromthoseplannedfor.Therewillbeagreater a stream of lots from a controlled process. It follows in this
case that the variance of a sample lot mean will be a function
seller’sriskofhavingalotrejectedwhosemeanisequaltothe
of both the within-batch and between-batch variances.
desired Llevel.Also,thebuyer’sriskofacceptingalot,whose
11.1.3 The recommended procedures of 11.2 call for com-
mean is below the L− ∆ level for barely acceptable quality,
positing of increments and reduction for laboratory testing.As
will also be greater than 0.10 (how much greater depends on
in the case of the batch variability, a preliminary study is made
how far off the estimate of the lot standard deviation may be).
of the compositing and reduction processes and preliminary
10.5.3 If the estimate of the lot standard deviation is greater
estimates are made of the reduction variance and the testing
than the true lot standard deviation, then the above procedures
variance. It is again assumed that these same variances
will give a sample size (n) that is greater than necessary to
continue valid for the reduction and testing procedure em-
yield the agreed upon risks. It will thus unnecessarily increase
ployed in the inspection of the current lot. Recommended
sampling costs.
proceduresforestimatingthebatchvariancesandthereduction
10.5.4 The risks stated in this practice are based on the
and testing variances are given in the Annex. In the sections
assumption that variability among units of the lot follows a
thatfollow,itwillbeassumedtheseestimateshavebeenmade.
normal distribution and that the total quantity of material in
11.1.4 A Word of Advice—Before a particular program is
subsamples taken for testing does not exceed 10% of the total
instituted, it would be desirable to review it with a statistician
quantityinthelot.Ifvariabilityamongunitsshowsevidenceof
to be sure that the recommendations of Section 11 are
considerable skewness, the logarithms of the data (or other thoroughly understood.
transformation) should be used.
11.2 Acceptance Tests Based on Current Samples:
10.5.5 If the sample units are taken from bulk material by a
11.2.1 Introduction—Withknowledgeofthebasicvariances
given sampling device, these risks are also based on the
fortheproductandforthemethodofreductionandtesting,the
assumption that the sampling device is used in taking both the
acceptability of a current lot from the given stream of material
preliminary sample and the total sample. can be determined as follows:
E300 − 03 (2022)
11.2.2 Formation of Composite Samples—For the purpose same as that of 11.2.4 and the formula for n is the same. It is
of determining the acceptability of a current lot from the given assumed that the spread between specification limits is at least
stream of lots, proceed as follows: Let the lot consist of n 3 σ .
1 x¯
batches of material where n is an integer. Presumably n is 11.2.7 Sample Checks on the Basic Variances—Before us-
1 1
determined by the needs of the purchaser with respect to his ing Eq 1 in an acceptance test, a check should be made to see
2 2 2 2
inventories, production, etc. (Note 9). Let n increments of ifthevaluespreviouslydeterminedfor σˆ , σˆ , σˆ ,and σˆ are
2 b w r t
material be taken at random from each of the n batches that stillvalid.Tocheckon σˆ ,computethedifferencebetweenthe
1 t
make up the given lot and let n be an even number. (The two tests for composite A and also the difference between the
determination of n is discussed in 11.2.4). If the batches are two tests for composite B and plot the two differences on an
notdistinct,taken n incrementsatrandomfromthelot.Form extensionofControlChart(4)describedintheAnnex.Proceed
1 2
a composite of all the odd numbered increments and another onlyifbothofthetwodifferencesfallwithinthecontrollimits.
composite of all the even numbered increments. Call the first Tochecktheremainingvariances,setupachartcalledControl
composite A, the second composite B. Reduce each composite Chart (5); the limits for which shall be
separately and under uniform conditions run two tests on each 2 1/2
2 2
σˆ
2σˆ σˆ
b
w t
composite. 0 and3.686 1 1σˆ 1 (25)
S D
r
n n n 2
1 1 2
NOTE 8—A fraction of a batch should be treated as a whole batch in
and the central line on which shall be
determining n .
2 2 2 1/2
σˆ 2σˆ σˆ
b w t
11.2.3 Variance Formula—The variance formula for the
1.128 1 1σˆ 1 (26)
S r D
n n n 2
¯
1 1 2
mean (X) of the two composite samples with two tests per
composite is
Plot on this chart the absolute value of the difference
2 2 2 2
between the mean of composite A and the mean of composite
σˆ σˆ σˆ σˆ
b w r t
σ 5 1 1 1 … (23)
x¯
n n n 2 4 B. Again proceed only if the difference falls below the upper
1 1 2
limitanddoesnot,withpreviouspoints,yieldarunofsevenor
where:
more above the central line.
σˆ = estimate made in the preliminary study of the
b
NOTE 9—If a point falls above the upper limit, this means that the
between-batch variance,
2 purchaser’stestingvarianceisprobablygreaterthan σˆ Anestimateofthe
t
σˆ = estimate of the within-batch variance,
w
formerbasedonadditionaldatawouldconsequentlyhavetobemade.The
σˆ = estimate of the reduction variance, and
r
acceptance procedure could thus continue with the purchaser’s test
σˆ = estimate of the testing variance. 2
t varianceinplaceoftheoriginal σˆ .Thisnewestimateshouldbebasedon
t
at least 20 degrees of freedom.
11.2.4 Determination of the Value of n with a Single Lower
Specification Limit (L)—For a single lower specification limit, 11.2.8 Acceptance Test when there is a Single Lower Speci-
the procedure for determining the value of n is as follows: fication Limit(L):
11.2.4.1 Step 1—Note the value of the lower specification 11.2.8.1 Step 1—Compute
limitforaverageproductqualityanddesignateitbyL.Assume
¯ 2 2 2 2 1/2
X 5 L 2 1.645 σˆ /n 1σˆ /n n 1σˆ /21σˆ /4 … (27)
~ !
La b 1 w 1 2 r t
this value to represent a quality level for which the probability
¯ ¯
of lot acceptance should be high and the risk of lot rejection
11.2.8.2 Step 2—Accept the lot if X ≥ X .
L
a
low. In the procedure for determining n , the seller’s risk is
11.2.9 The Acceptance Test when there is a Single Upper
taken to be 0.05.
Specification Limit(U)
11.2.4.2 Step 2—Determine a barely tolerable product qual-
11.2.9.1 Step 1—Compute
ity for which the probability of lot acceptance should be low
2 2 2 2 1/2
¯
X 1U11.645 σˆ /n 1σˆ /n n 1σˆ /21σˆ /4 … (28)
~ !
Ua b 1 w 1 2 r t
anddesignatethisbyL− ∆.Herethebuyer’sriskistakentobe
0.10.
¯ ¯
11.2.9.2 Step 2—Accept the lot if X ≤ X .
Ua
11.2.4.3 Step 3—Take n as the even integer just greater
11.2.10 Acceptance Test when there are both a Lower
than
Specification Limit(L) and an Upper Specification Limit (U):
11.2.10.1 Step 1—Note whetherU−L is greater than
σˆ
w
n 5 …
2 2 2 2
2 2 2 2 1/2
n ~∆ /8.5673! 2 σˆ /n 2 σˆ /2 2 ~σˆ /4!
@ ~ ! ~ ! # 3 σˆ /n 1σˆ /n n 1σˆ /21σˆ /4 (29)
1 b 1 r t ~ !
b 1 w 1 2 r t
(24)
If it is, continue to Step 2. If it is not, do not continue.
¯ ¯
11.2.10.2 Step 2—Compute X and X as in 11.2.8 and
This n will for the stated variances make the probability of
L U
2 a a
11.2.9.
lot acceptance for product quality L equal approximately to
¯ ¯ ¯
11.2.10.3 Step 3—Accept the lot if X ≤ X ≤ X .
0.95 and the probability of lot acceptance for product quality
La Ua
L− ∆ equal to 0.10.
SIMPLE LIQUIDS
11.2.5 Determination of the Value of n with a Single Upper
Specification (U)—The procedure is the same as that of 11.2.4
12. Scope
except that U replaces L and U+ ∆ replaces L− ∆. The
formula for n is the same. 12.1 This procedure covers the sampling of industrial
11.2.6 Determination of the Value of n with Both a Lower chemicals which are single-phase liquids under the conditions
and Upper Specification Limit—The procedure is exactly the of sampling.
E300 − 03 (2022)
NOTE 10—This procedure is based on Method D270.
current of clean warm air through the container or by placing
it in a dust-free cabinet at 40°C or higher. Close containers as
13. Summary
soon as they are dry.
13.1 Samples of simple liquids are examined using various
14.3 Screw-Neck and Press-Cover Cans—Cans of tin plate
ASTMmethodsforthedeterminationofphysicalandchemical
with seams soldered on the outside must be used. The neck
characteristics. It is accordingly necessary that the samples be
shouldbeshapedtoreceiveascrewcaporpressedcover.Take
truly representative of the simple liquids in question. The
care to ensure that cans are clean, even when new. They may
precautions required to ensure the representative character of
be cleaned by washing with low-boiling, nonflammable sol-
thesamplesarenumerousanddependuponthetypeofproduct
vents and blowing dry with clean air. Cap the containers as
beingsampled,thetank,thecarrierorcontainerfromwhichthe
soon as they are dry.
sample is being obtained, the type and cleanliness of the
sample container, and the sampling procedure that is to be
15. Time and Place of Sampling
used. A summary of the sampling procedures and their appli-
15.1 Finished Products—When loading or discharging fin-
cation is presented in Table 3. Each procedure is suitable for
ished products, take samples from both shipping and receiving
sampling a number of specific products under definite storage,
tanks, and from the pipeline, if required.
transportation, or container conditions. The basic principle of
15.2 Ship or Barge Tanks—Sample each product immedi-
each procedure is to obtain a sample or a composite of several
ately after the vessel is loaded, or just before discharging.
samples in such manner and from such locations in the tank or
other container that the sample or composite will be truly
15.3 Tank Cars—Sample the product immediately after the
representativeoftheproduct.Althoughsingle-phaseliquidsare
car is loaded, or just before unloading.
homogeneous by definition, it may be desirable to check for
this condition by sampling from various sections of the
16. Number and Location of Samples
container.
16.1 Bulk Containers (Tanks, Tank Cars etc.)—Simple liq-
uids in bulk containers are frequently found to be homoge-
14. Sampling Equipment
neous and only limited sampling is usually required. Upper,
14.1 General Requirements—All sampling apparatus and
middle, and lower samples (22.3) or top and outlet samples
closures shall be clean, dry, free of contaminants, and con-
(22.5) can be individually tested to confirm this, by means of
structedofmaterialsthatareinerttotheproducttobesampled.
simple physical tests such as refractive index, density,
The sampling container and closure shall be clean, dry, and
viscosity, etc. Complete testing can then be performed on a
inert to the material being sampled.
composite prepared as described in 22.4.
14.2 Bottles and Jars—Bottles and jars may be made of
16.2 Packaged Materials (Drums, Cans, Bottles, etc.)—In
clear or brown glass or polyethylene with necks shaped to
thecaseoflotsofdrums,bottles,andcans,thehomogeneityof
receive a glass stopper or a screw cap made of metal or plastic
thelotcannotbeassumed,andtherequirednumberofsamples
material. Use of unprotected corks as closures is not recom-
shouldbedeterminedinaccordancewithSections7and8.The
mended for general use. Where safety indicates (such as for
specific containers to be sampled for individual testing should
peroxides) use corks covered with materials inert to the
be chosen by means of a table of random numbers.
sample, such as cellophane, polyethylene, or aluminum foil.
Clear glass is advantageous because the container may be
17. Sampling Operations
examined visually for cleanliness and the sample may be
17.1 Procedures for sampling cannot be made explicit
visuallyinspectedforforeignmatter.Brownglassaffordssome
enoughtocoverallcases.Extremecareandgoodjudgmentare
protectionforlight-sensitivematerials.Beforeusingabottleor
necessary to ensure samples are obtained which represent the
jar, examine it to see that it is scrupulously clean.Avariety of
general character and average condition of the material. Clean
methods for cleaning glass containers may be used: washing
hands are important. Clean gloves may be worn but only when
with detergents, water, acetone, etc. The specific method used
absolutely necessary, such as during cold weather, or for
will depend upon the material to be sampled. Care should be
reasons of safety. Select wiping cloths so that lint is not
taken that all of the cleaning agents are removed from the
introduced, thus contaminating samples.
container prior to use. Dry the container either by passing a
17.2 Sincethevaporsofsomeindustrialchemicalsaretoxic
and flammable, avoid breathing them, igniting them from an
open flame, burning embers, or a spark produced by static
TABLE 3 Summary of Sampling Procedures and Applicability
electricity.All safety precautions specific to the material being
Type of Container Type of Sampling Section
sampled must be followed.
Storage tanks (trucks, cars, ships, Bottle sampling, thief sampling 22, 23
barges, stationary)
17.3 When sampling relatively volatile products, the sam-
Storage tanks (trucks, cars, Tap sampling 24
pling apparatus shall be filled and allowed to drain before
stationary)
Pipe lines, filling lines, transfer Continuous sampling 25 drawing the sample. If the sample is to be transferred to
lines
another container, this container shall have been cleaned and
Drums, carboy, cans, bottles Tube sampling 26
dried as described in Section 14 and also be rinsed with some
Free or open-discharge streams Jar sampling 27
of the volatile product and then drained. When the actual
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sample is emptied into this container, the sampling apparatus 20. Shipping Precautions
should be upended into the opening of the sample container
20.1 To prevent the loss of liquid during shipment and to
and remain in this position until the contents have been
protectagainstmoistureanddust,covertheclosureoftheglass
transferred so that no unsaturated air will be entrained in the
bottle with plastic caps which have been swelled in water,
transfer of the sample.
wiped dry, placed over the top of the stoppered bottle, and
17.4 When sampling non-volatile liquid products, the sam- allowed to shrink tightly in place. Screw-top bottles are
pling apparatus shall be filled and allowed to drain before
recommended.The cap must be lined with material inert to the
drawing the actual sample. If the actual sample is to be sample. The screw caps must be secured by use of adhesive
transferred to another container, this container shall have been
tape or similar material.
cleanedanddriedasdescribedinSection14andalsoberinsed
NOTE 11—Shipping of any chemical must comply with current federal,
with some of the product to be sampled and drained before it
state, and local regulations for the specific material being shipped.
is filled with the actual sample.
21. Labeling Sample Containers
17.5 Asample shall be considered suspect under any of the
following circumstances and should be referred to the appro-
21.1 Label the container immediately after a sample is
priate supervisor before analysis:
obtained. Use waterproof and oil-proof ink or a pencil hard
17.5.1 The sample container is damaged or defective.
enough to dent the tag, since soft pencil and ordinary ink
17.5.2 There is any doubt as to the nature of the contents of
markings are subject to obliteration from moisture, oil
the sample container: for example, because of the presence of
smearing, and handling. If gummed labels are used, they
an old label, incorrect markings, or insufficient identification.
should be further secured with transparent sealing tape. Suffi-
17.5.3 There is evidence of an unexpected lack of unifor-
cient detail should be written on the label to completely
mity; for example, a separate layer or suspended matter.
identify the sample. The following information is frequently
17.5.4 Obvious and unusual variations are apparent in the
desired:
sample.
21.1.1 Date and time (and for continuous and dipper
17.5.5 Thecontainerclosureisloose,whetherornotthereis
samples the hour and minute of collection),
evidence of leakage.
21.1.2 Name of sampler,
17.5.6 Evidence that the closure or liner has been attacked.
21.1.3 Name or number and owner of the vessel, car, or
container,
18. Size of Sample
21.1.4 Brandname,gradeofmaterial,andcodenumber,and
18.1 The quantity of sample should be as specified by the
21.1.5 Reference symbol and necessary identification num-
test instructions, or at least three times greater than the
ber.
minimum necessary for the actual tests.
21.1.6 Hazard ratings.
19. Precautions
22. Bottle Sampling
19.1 Volatile Samples (Reid vapor pressure 14 to 110.3 kPa
22.1 The bottle sampling procedure is applicable for sam-
at 37.8°C (2 to 16 psi at 100°F))—It is necessary to
...