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<p class="MsoNormal"><span lang="EN-US">This TR provides an overview of the use of prior information in acceptance sampling. The methods described in the present TR can be applied for the inspection of both processes and lots.</span></p>
<p class="MsoNormal"><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">Not only do manufacturing or production processes lie within the scope of the present TR; but the scope also covers any process whose outcome are discrete physical or digital units whose conformity can be assessed. In particular, the method described in the present TR can also be applied to AI-based classification systems. The production unit would then consist of the pair (object to be assigned to a class, assigned class) and a conforming unit would be defined as a correct classification.</span></span></p>
<p class="MsoNormal"><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">As far as lots are concerned, the scope of the present TR includes both the inspection of isolated lots and serial lot inspection. The term “isolated lot inspection” does not mean that the consumer has no access to information regarding lot quality prior to the inspection of the current lot. Rather “isolated lot inspection” means that there are no switching rules and that the acceptance sampling plan is calculated separately for each new lot. In particular, the consumer having past experience with or knowledge regarding the <em>producer</em> of the lot currently under inspection is perfectly compatible with the concept of “isolated lot inspection.”</span></span></p>
<p class="MsoNormal"><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">This TR consists of three main parts.</span></span></p>
<p class="MsoNormal"><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">First, a risk-based approach is described (Section </span></span><!-- [if supportFields]><span
style='mso-bookmark:_Hlk187681878'></span><span style='mso-element:field-begin'></span><span
style='mso-bookmark:_Hlk187681878'><span lang=EN-US><span
style='mso-spacerun:yes'> </span>REF _Ref187325464 \r \h <span
style='mso-element:field-separator'></span></span></span><![endif]--><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">7<!-- [if gte mso 9]><xml>
<w:data>08D0C9EA79F9BACE118C8200AA004BA90B02000000080000000E0000005F005200650066003100380037003300320035003400360034000000</w:data>
</xml><![endif]--></span></span><!-- [if supportFields]><span style='mso-bookmark:
_Hlk187681878'></span><span style='mso-element:field-end'></span><![endif]--><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">). This approach is based on concepts (such as specific consumer’s risk and conformance probability) defined in JCGM 106. It is shown how the sample size and the acceptance number can be calculated once a region for lot conformance and a tolerance for the specific consumer risk have been specified. In addition, an overview of information-based risks is provided.</span></span></p>
<p class="MsoNormal"><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">Second, a utility-based approach is described (Section </span></span><!-- [if supportFields]><span
style='mso-bookmark:_Hlk187681878'></span><span style='mso-element:field-begin'></span><span
style='mso-bookmark:_Hlk187681878'><span lang=EN-US><span
style='mso-spacerun:yes'> </span>REF _Ref193969454 \r \h <span
style='mso-element:field-separator'></span></span></span><![endif]--><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">8<!-- [if gte mso 9]><xml>
<w:data>08D0C9EA79F9BACE118C8200AA004BA90B02000000080000000E0000005F005200650066003100390033003900360039003400350034000000</w:data>
</xml><![endif]--></span></span><!-- [if supportFields]><span style='mso-bookmark:
_Hlk187681878'></span><span style='mso-element:field-end'></span><![endif]--><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">). This approach replaces the underlying principle of risk aversion with a rational cost-benefit calculus. Indeed, risk-based approaches consider neither the testing & sampling costs, nor hidden costs such as administrative overhead, nor the potential benefits associated with lot acceptance. By contrast, in the utility-based approach, all potential benefits, costs, losses and damages—including testing & sampling costs, potential costs associated with recalling a lot or healthcare, reputational costs, costs caused by the ingestion of contaminated food, and the bureaucratic and administrative costs associated with the implementation of regulations—are internalized in one utility function. In this sense, the utility approach bridges the gap between the “old world” of risks and the “new world” of utility. Tables with standard plans for various cost-structures and lot size values are provided.</span></span></p>
<p class="MsoNormal"><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">Third, an approach for serial lot inspection is described (Section 9). In this approach, a Bayesian updating framework is provided in which data-ageing is reflected in a downweighting mechanism for older data.</span></span></p>
<p class="MsoNormal" style="margin-bottom: 0cm;"><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">Prior to these three parts, there are five preliminary sections:</span></span></p>
<ul>
<li class="MsoListParagraphCxSpFirst" style="text-indent: -18pt;"><span style="mso-bookmark: _Hlk187681878;"><!-- [if !supportLists]--><span lang="EN-US" style="font-family: Symbol; mso-fareast-font-family: Symbol; mso-bidi-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt 'Times New Roman';"> </span></span></span><!--[endif]--><span lang="EN-US">Introduction (Section </span></span><!-- [if supportFields]><span
style='mso-bookmark:_Hlk187681878'></span><span style='mso-element:field-begin'></span><span
style='mso-bookmark:_Hlk187681878'><span lang=EN-US><span
style='mso-spacerun:yes'> </span>REF _Ref193969493 \r \h <span
style='mso-element:field-separator'></span></span></span><![endif]--><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">2<!-- [if gte mso 9]><xml>
<w:data>08D0C9EA79F9BACE118C8200AA004BA90B02000000080000000E0000005F005200650066003100390033003900360039003400390033000000</w:data>
</xml><![endif]--></span></span><!-- [if supportFields]><span style='mso-bookmark:
_Hlk187681878'></span><span style='mso-element:field-end'></span><![endif]--><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">)</span></span></li>
<li class="MsoListParagraphCxSpMiddle" style="text-indent: -18pt;"><span style="mso-bookmark: _Hlk187681878;"><!-- [if !supportLists]--><span lang="EN-US" style="font-family: Symbol; mso-fareast-font-family: Symbol; mso-bidi-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt 'Times New Roman';"> </span></span></span><!--[endif]--><span lang="EN-US">Background information regarding the plans in the ISO 2859 and ISO 3951 standards (Section </span></span><!-- [if supportFields]><span
style='mso-bookmark:_Hlk187681878'></span><span style='mso-element:field-begin'></span><span
style='mso-bookmark:_Hlk187681878'><span lang=EN-US><span
style='mso-spacerun:yes'> </span>REF _Ref187317559 \r \h <span
style='mso-element:field-separator'></span></span></span><![endif]--><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">3<!-- [if gte mso 9]><xml>
<w:data>08D0C9EA79F9BACE118C8200AA004BA90B02000000080000000E0000005F005200650066003100380037003300310037003500350039000000</w:data>
</xml><![endif]--></span></span><!-- [if supportFields]><span style='mso-bookmark:
_Hlk187681878'></span><span style='mso-element:field-end'></span><![endif]--><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">)</span></span></li>
<li class="MsoListParagraphCxSpMiddle" style="text-indent: -18pt;"><span style="mso-bookmark: _Hlk187681878;"><!-- [if !supportLists]--><span lang="EN-US" style="font-family: Symbol; mso-fareast-font-family: Symbol; mso-bidi-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt 'Times New Roman';"> </span></span></span><!--[endif]--><span lang="EN-US">Background regarding prior and posterior distributions (Section </span></span><!-- [if supportFields]><span
style='mso-bookmark:_Hlk187681878'></span><span style='mso-element:field-begin'></span><span
style='mso-bookmark:_Hlk187681878'><span lang=EN-US><span
style='mso-spacerun:yes'> </span>REF _Ref193969590 \r \h <span
style='mso-element:field-separator'></span></span></span><![endif]--><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">4<!-- [if gte mso 9]><xml>
<w:data>08D0C9EA79F9BACE118C8200AA004BA90B02000000080000000E0000005F005200650066003100390033003900360039003500390030000000</w:data>
</xml><![endif]--></span></span><!-- [if supportFields]><span style='mso-bookmark:
_Hlk187681878'></span><span style='mso-element:field-end'></span><![endif]--><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">)</span></span></li>
<li class="MsoListParagraphCxSpMiddle" style="text-indent: -18pt;"><span style="mso-bookmark: _Hlk187681878;"><!-- [if !supportLists]--><span lang="EN-US" style="font-family: Symbol; mso-fareast-font-family: Symbol; mso-bidi-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt 'Times New Roman';"> </span></span></span><!--[endif]--><span lang="EN-US">Overall framework in which the classical and information-based risks can be seen as complementary (Section </span></span><!-- [if supportFields]><span
style='mso-bookmark:_Hlk187681878'></span><span style='mso-element:field-begin'></span><span
style='mso-bookmark:_Hlk187681878'><span lang=EN-US><span
style='mso-spacerun:yes'> </span>REF _Ref193204606 \r \h <span
style='mso-element:field-separator'></span></span></span><![endif]--><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">5<!-- [if gte mso 9]><xml>
<w:data>08D0C9EA79F9BACE118C8200AA004BA90B02000000080000000E0000005F005200650066003100390033003200300034003600300036000000</w:data>
</xml><![endif]--></span></span><!-- [if supportFields]><span style='mso-bookmark:
_Hlk187681878'></span><span style='mso-element:field-end'></span><![endif]--><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">)</span></span></li>
<li class="MsoListParagraphCxSpLast" style="text-indent: -18pt;"><span style="mso-bookmark: _Hlk187681878;"><!-- [if !supportLists]--><span lang="EN-US" style="font-family: Symbol; mso-fareast-font-family: Symbol; mso-bidi-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt 'Times New Roman';"> </span></span></span><!--[endif]--><span lang="EN-US">Guidance for deriving a prior distribution and selecting an appropriate approach for the design of an acceptance sampling plan (Section </span></span><!-- [if supportFields]><span
style='mso-bookmark:_Hlk187681878'></span><span style='mso-element:field-begin'></span><span
style='mso-bookmark:_Hlk187681878'><span lang=EN-US><span
style='mso-spacerun:yes'> </span>REF _Ref200702258 \r \h <span
style='mso-element:field-separator'></span></span></span><![endif]--><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">6<!-- [if gte mso 9]><xml>
<w:data>08D0C9EA79F9BACE118C8200AA004BA90B02000000080000000E0000005F005200650066003200300030003700300032003200350038000000</w:data>
</xml><![endif]--></span></span><!-- [if supportFields]><span style='mso-bookmark:
_Hlk187681878'></span><span style='mso-element:field-end'></span><![endif]--><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">)</span></span></li>
</ul>
<p class="MsoNormal"><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">Throughout this TR, the aim is to propose relatively straightforward and pragmatic methods for the design of acceptance sampling plans. Nonetheless, in parallel to the approach, the background theory is provided and illustrated with examples.</span></span></p>
<p class="MsoNormal"><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">The present TR focuses on lots consisting of discrete items and lot inspection by attributes. The methods presented here can be extended for lots consisting of bulk material and for inspection by variables. This will be the subject of subsequent work.</span></span></p>
<p class="MsoNormal"><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">Measurement and inspection error are not considered in this TR. The methods described here can be adjusted to take various error sources into account. This will be the subject of subsequent work.</span></span></p>
<p class="MsoNormal"><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">Finally, in this TR, the testing outcome is usually considered to follow a binomial distribution. Strictly speaking, this is more appropriate for the underlying process than for the lot. The methods described in this TR can be adjusted in such a way that the testing outcome is modelled via the hypergeometric distribution, see Section </span></span><!-- [if supportFields]><span
style='mso-bookmark:_Hlk187681878'></span><span style='mso-element:field-begin'></span><span
style='mso-bookmark:_Hlk187681878'><span lang=EN-US><span
style='mso-spacerun:yes'> </span>REF _Ref199848949 \r \h <span
style='mso-element:field-separator'></span></span></span><![endif]--><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">5.4.2<!-- [if gte mso 9]><xml>
<w:data>08D0C9EA79F9BACE118C8200AA004BA90B02000000080000000E0000005F005200650066003100390039003800340038003900340039000000</w:data>
</xml><![endif]--></span></span><!-- [if supportFields]><span style='mso-bookmark:
_Hlk187681878'></span><span style='mso-element:field-end'></span><![endif]--><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">.</span></span></p>
<p class="MsoNormal"><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">A glossary of the most important terms and notation is provided at the end for convenient reference (Section </span></span><!-- [if supportFields]><span
style='mso-bookmark:_Hlk187681878'></span><span style='mso-element:field-begin'></span><span
style='mso-bookmark:_Hlk187681878'><span lang=EN-US><span
style='mso-spacerun:yes'> </span>REF _Ref193969761 \r \h <span
style='mso-element:field-separator'></span></span></span><![endif]--><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">10<!-- [if gte mso 9]><xml>
<w:data>08D0C9EA79F9BACE118C8200AA004BA90B02000000080000000E0000005F005200650066003100390033003900360039003700360031000000</w:data>
</xml><![endif]--></span></span><!-- [if supportFields]><span style='mso-bookmark:
_Hlk187681878'></span><span style='mso-element:field-end'></span><![endif]--><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">).</span></span></p>
Reģistrācijas numurs (WIID)
88684
Darbības sfēra
<p class="MsoNormal"><span lang="EN-US">This TR provides an overview of the use of prior information in acceptance sampling. The methods described in the present TR can be applied for the inspection of both processes and lots.</span></p>
<p class="MsoNormal"><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">Not only do manufacturing or production processes lie within the scope of the present TR; but the scope also covers any process whose outcome are discrete physical or digital units whose conformity can be assessed. In particular, the method described in the present TR can also be applied to AI-based classification systems. The production unit would then consist of the pair (object to be assigned to a class, assigned class) and a conforming unit would be defined as a correct classification.</span></span></p>
<p class="MsoNormal"><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">As far as lots are concerned, the scope of the present TR includes both the inspection of isolated lots and serial lot inspection. The term “isolated lot inspection” does not mean that the consumer has no access to information regarding lot quality prior to the inspection of the current lot. Rather “isolated lot inspection” means that there are no switching rules and that the acceptance sampling plan is calculated separately for each new lot. In particular, the consumer having past experience with or knowledge regarding the <em>producer</em> of the lot currently under inspection is perfectly compatible with the concept of “isolated lot inspection.”</span></span></p>
<p class="MsoNormal"><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">This TR consists of three main parts.</span></span></p>
<p class="MsoNormal"><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">First, a risk-based approach is described (Section </span></span><!-- [if supportFields]><span
style='mso-bookmark:_Hlk187681878'></span><span style='mso-element:field-begin'></span><span
style='mso-bookmark:_Hlk187681878'><span lang=EN-US><span
style='mso-spacerun:yes'> </span>REF _Ref187325464 \r \h <span
style='mso-element:field-separator'></span></span></span><![endif]--><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">7<!-- [if gte mso 9]><xml>
<w:data>08D0C9EA79F9BACE118C8200AA004BA90B02000000080000000E0000005F005200650066003100380037003300320035003400360034000000</w:data>
</xml><![endif]--></span></span><!-- [if supportFields]><span style='mso-bookmark:
_Hlk187681878'></span><span style='mso-element:field-end'></span><![endif]--><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">). This approach is based on concepts (such as specific consumer’s risk and conformance probability) defined in JCGM 106. It is shown how the sample size and the acceptance number can be calculated once a region for lot conformance and a tolerance for the specific consumer risk have been specified. In addition, an overview of information-based risks is provided.</span></span></p>
<p class="MsoNormal"><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">Second, a utility-based approach is described (Section </span></span><!-- [if supportFields]><span
style='mso-bookmark:_Hlk187681878'></span><span style='mso-element:field-begin'></span><span
style='mso-bookmark:_Hlk187681878'><span lang=EN-US><span
style='mso-spacerun:yes'> </span>REF _Ref193969454 \r \h <span
style='mso-element:field-separator'></span></span></span><![endif]--><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">8<!-- [if gte mso 9]><xml>
<w:data>08D0C9EA79F9BACE118C8200AA004BA90B02000000080000000E0000005F005200650066003100390033003900360039003400350034000000</w:data>
</xml><![endif]--></span></span><!-- [if supportFields]><span style='mso-bookmark:
_Hlk187681878'></span><span style='mso-element:field-end'></span><![endif]--><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">). This approach replaces the underlying principle of risk aversion with a rational cost-benefit calculus. Indeed, risk-based approaches consider neither the testing & sampling costs, nor hidden costs such as administrative overhead, nor the potential benefits associated with lot acceptance. By contrast, in the utility-based approach, all potential benefits, costs, losses and damages—including testing & sampling costs, potential costs associated with recalling a lot or healthcare, reputational costs, costs caused by the ingestion of contaminated food, and the bureaucratic and administrative costs associated with the implementation of regulations—are internalized in one utility function. In this sense, the utility approach bridges the gap between the “old world” of risks and the “new world” of utility. Tables with standard plans for various cost-structures and lot size values are provided.</span></span></p>
<p class="MsoNormal"><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">Third, an approach for serial lot inspection is described (Section 9). In this approach, a Bayesian updating framework is provided in which data-ageing is reflected in a downweighting mechanism for older data.</span></span></p>
<p class="MsoNormal" style="margin-bottom: 0cm;"><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">Prior to these three parts, there are five preliminary sections:</span></span></p>
<ul>
<li class="MsoListParagraphCxSpFirst" style="text-indent: -18pt;"><span style="mso-bookmark: _Hlk187681878;"><!-- [if !supportLists]--><span lang="EN-US" style="font-family: Symbol; mso-fareast-font-family: Symbol; mso-bidi-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt 'Times New Roman';"> </span></span></span><!--[endif]--><span lang="EN-US">Introduction (Section </span></span><!-- [if supportFields]><span
style='mso-bookmark:_Hlk187681878'></span><span style='mso-element:field-begin'></span><span
style='mso-bookmark:_Hlk187681878'><span lang=EN-US><span
style='mso-spacerun:yes'> </span>REF _Ref193969493 \r \h <span
style='mso-element:field-separator'></span></span></span><![endif]--><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">2<!-- [if gte mso 9]><xml>
<w:data>08D0C9EA79F9BACE118C8200AA004BA90B02000000080000000E0000005F005200650066003100390033003900360039003400390033000000</w:data>
</xml><![endif]--></span></span><!-- [if supportFields]><span style='mso-bookmark:
_Hlk187681878'></span><span style='mso-element:field-end'></span><![endif]--><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">)</span></span></li>
<li class="MsoListParagraphCxSpMiddle" style="text-indent: -18pt;"><span style="mso-bookmark: _Hlk187681878;"><!-- [if !supportLists]--><span lang="EN-US" style="font-family: Symbol; mso-fareast-font-family: Symbol; mso-bidi-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt 'Times New Roman';"> </span></span></span><!--[endif]--><span lang="EN-US">Background information regarding the plans in the ISO 2859 and ISO 3951 standards (Section </span></span><!-- [if supportFields]><span
style='mso-bookmark:_Hlk187681878'></span><span style='mso-element:field-begin'></span><span
style='mso-bookmark:_Hlk187681878'><span lang=EN-US><span
style='mso-spacerun:yes'> </span>REF _Ref187317559 \r \h <span
style='mso-element:field-separator'></span></span></span><![endif]--><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">3<!-- [if gte mso 9]><xml>
<w:data>08D0C9EA79F9BACE118C8200AA004BA90B02000000080000000E0000005F005200650066003100380037003300310037003500350039000000</w:data>
</xml><![endif]--></span></span><!-- [if supportFields]><span style='mso-bookmark:
_Hlk187681878'></span><span style='mso-element:field-end'></span><![endif]--><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">)</span></span></li>
<li class="MsoListParagraphCxSpMiddle" style="text-indent: -18pt;"><span style="mso-bookmark: _Hlk187681878;"><!-- [if !supportLists]--><span lang="EN-US" style="font-family: Symbol; mso-fareast-font-family: Symbol; mso-bidi-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt 'Times New Roman';"> </span></span></span><!--[endif]--><span lang="EN-US">Background regarding prior and posterior distributions (Section </span></span><!-- [if supportFields]><span
style='mso-bookmark:_Hlk187681878'></span><span style='mso-element:field-begin'></span><span
style='mso-bookmark:_Hlk187681878'><span lang=EN-US><span
style='mso-spacerun:yes'> </span>REF _Ref193969590 \r \h <span
style='mso-element:field-separator'></span></span></span><![endif]--><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">4<!-- [if gte mso 9]><xml>
<w:data>08D0C9EA79F9BACE118C8200AA004BA90B02000000080000000E0000005F005200650066003100390033003900360039003500390030000000</w:data>
</xml><![endif]--></span></span><!-- [if supportFields]><span style='mso-bookmark:
_Hlk187681878'></span><span style='mso-element:field-end'></span><![endif]--><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">)</span></span></li>
<li class="MsoListParagraphCxSpMiddle" style="text-indent: -18pt;"><span style="mso-bookmark: _Hlk187681878;"><!-- [if !supportLists]--><span lang="EN-US" style="font-family: Symbol; mso-fareast-font-family: Symbol; mso-bidi-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt 'Times New Roman';"> </span></span></span><!--[endif]--><span lang="EN-US">Overall framework in which the classical and information-based risks can be seen as complementary (Section </span></span><!-- [if supportFields]><span
style='mso-bookmark:_Hlk187681878'></span><span style='mso-element:field-begin'></span><span
style='mso-bookmark:_Hlk187681878'><span lang=EN-US><span
style='mso-spacerun:yes'> </span>REF _Ref193204606 \r \h <span
style='mso-element:field-separator'></span></span></span><![endif]--><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">5<!-- [if gte mso 9]><xml>
<w:data>08D0C9EA79F9BACE118C8200AA004BA90B02000000080000000E0000005F005200650066003100390033003200300034003600300036000000</w:data>
</xml><![endif]--></span></span><!-- [if supportFields]><span style='mso-bookmark:
_Hlk187681878'></span><span style='mso-element:field-end'></span><![endif]--><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">)</span></span></li>
<li class="MsoListParagraphCxSpLast" style="text-indent: -18pt;"><span style="mso-bookmark: _Hlk187681878;"><!-- [if !supportLists]--><span lang="EN-US" style="font-family: Symbol; mso-fareast-font-family: Symbol; mso-bidi-font-family: Symbol;"><span style="mso-list: Ignore;">·<span style="font: 7.0pt 'Times New Roman';"> </span></span></span><!--[endif]--><span lang="EN-US">Guidance for deriving a prior distribution and selecting an appropriate approach for the design of an acceptance sampling plan (Section </span></span><!-- [if supportFields]><span
style='mso-bookmark:_Hlk187681878'></span><span style='mso-element:field-begin'></span><span
style='mso-bookmark:_Hlk187681878'><span lang=EN-US><span
style='mso-spacerun:yes'> </span>REF _Ref200702258 \r \h <span
style='mso-element:field-separator'></span></span></span><![endif]--><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">6<!-- [if gte mso 9]><xml>
<w:data>08D0C9EA79F9BACE118C8200AA004BA90B02000000080000000E0000005F005200650066003200300030003700300032003200350038000000</w:data>
</xml><![endif]--></span></span><!-- [if supportFields]><span style='mso-bookmark:
_Hlk187681878'></span><span style='mso-element:field-end'></span><![endif]--><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">)</span></span></li>
</ul>
<p class="MsoNormal"><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">Throughout this TR, the aim is to propose relatively straightforward and pragmatic methods for the design of acceptance sampling plans. Nonetheless, in parallel to the approach, the background theory is provided and illustrated with examples.</span></span></p>
<p class="MsoNormal"><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">The present TR focuses on lots consisting of discrete items and lot inspection by attributes. The methods presented here can be extended for lots consisting of bulk material and for inspection by variables. This will be the subject of subsequent work.</span></span></p>
<p class="MsoNormal"><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">Measurement and inspection error are not considered in this TR. The methods described here can be adjusted to take various error sources into account. This will be the subject of subsequent work.</span></span></p>
<p class="MsoNormal"><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">Finally, in this TR, the testing outcome is usually considered to follow a binomial distribution. Strictly speaking, this is more appropriate for the underlying process than for the lot. The methods described in this TR can be adjusted in such a way that the testing outcome is modelled via the hypergeometric distribution, see Section </span></span><!-- [if supportFields]><span
style='mso-bookmark:_Hlk187681878'></span><span style='mso-element:field-begin'></span><span
style='mso-bookmark:_Hlk187681878'><span lang=EN-US><span
style='mso-spacerun:yes'> </span>REF _Ref199848949 \r \h <span
style='mso-element:field-separator'></span></span></span><![endif]--><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">5.4.2<!-- [if gte mso 9]><xml>
<w:data>08D0C9EA79F9BACE118C8200AA004BA90B02000000080000000E0000005F005200650066003100390039003800340038003900340039000000</w:data>
</xml><![endif]--></span></span><!-- [if supportFields]><span style='mso-bookmark:
_Hlk187681878'></span><span style='mso-element:field-end'></span><![endif]--><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">.</span></span></p>
<p class="MsoNormal"><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">A glossary of the most important terms and notation is provided at the end for convenient reference (Section </span></span><!-- [if supportFields]><span
style='mso-bookmark:_Hlk187681878'></span><span style='mso-element:field-begin'></span><span
style='mso-bookmark:_Hlk187681878'><span lang=EN-US><span
style='mso-spacerun:yes'> </span>REF _Ref193969761 \r \h <span
style='mso-element:field-separator'></span></span></span><![endif]--><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">10<!-- [if gte mso 9]><xml>
<w:data>08D0C9EA79F9BACE118C8200AA004BA90B02000000080000000E0000005F005200650066003100390033003900360039003700360031000000</w:data>
</xml><![endif]--></span></span><!-- [if supportFields]><span style='mso-bookmark:
_Hlk187681878'></span><span style='mso-element:field-end'></span><![endif]--><span style="mso-bookmark: _Hlk187681878;"><span lang="EN-US">).</span></span></p>
