{"id":241113,"date":"2025-11-23T14:26:35","date_gmt":"2025-11-23T14:26:35","guid":{"rendered":"https:\/\/www.qcadvisor.com\/?p=241113"},"modified":"2026-03-09T22:43:23","modified_gmt":"2026-03-09T22:43:23","slug":"acceptable-quality-limit","status":"publish","type":"post","link":"https:\/\/www.qcadvisor.com\/es-mx\/blog\/acceptable-quality-limit\/","title":{"rendered":"Acceptable Quality Limit: Definition, Charts, Tables & Examples"},"content":{"rendered":"

[et_pb_section fb_built=”1″ _builder_version=”4.16″ da_disable_devices=”off|off|off” global_colors_info=”{}” theme_builder_area=”post_content” da_is_popup=”off” da_exit_intent=”off” da_has_close=”on” da_alt_close=”off” da_dark_close=”off” da_not_modal=”on” da_is_singular=”off” da_with_loader=”off” da_has_shadow=”on”][et_pb_row _builder_version=”4.16″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” global_colors_info=”{}” theme_builder_area=”post_content”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||” theme_builder_area=”post_content”][et_pb_text _builder_version=”4.27.5″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” global_colors_info=”{}” theme_builder_area=”post_content”]<\/p>\n

The <\/span>acceptable quality limit (AQL)<\/b>\u2014also called the <\/span>acceptance quality limit<\/b>\u2014is the risk-based quality limit you use to decide, from a sample, whether a production batch meets your quality requirements.\u00a0<\/span><\/p>\n

AQL plays a central role in today\u2019s product inspection cycle:: from <\/span>incoming<\/b> to <\/span>in-process<\/b> to <\/span>final<\/b> inspections, it gives buyers, suppliers, and <\/span>inspectors<\/b> a common language for <\/span>quality control<\/b>. Practically, AQL is best executed by experienced third-party teams as part of full <\/span>product inspection services<\/b>\u2014they bring calibrated tools, documented <\/span>sampling inspections<\/b>, and unbiased decision making that protects your <\/span>brand<\/b> and the <\/span>end user<\/b> while controlling <\/span>inspection costs<\/b>.<\/span><\/p>\n

In this article, you\u2019ll see exactly how AQL works in practice: the sampling standards behind it (ISO 2859-1 \/ ANSI\/ASQ Z1.4), how inspection levels (General I\/II\/III and Special S-1\u2013S-4) set sample size, and how critical defects, major defects, and minor defects map to an acceptance number and rejection number.<\/span><\/p>\n

You\u2019ll also learn how AQL tables translate lot size into a sample size code letter, how OC curves quantify producer\u2019s\/consumer\u2019s risks, when to apply switching rules, and which industries adapt AQL for their products.<\/span><\/p>\n

What is the acceptable quality limit (AQL)?<\/span><\/h2>\n

AQL, per <\/span>ISO 2859-1<\/b>, is the <\/span>worst tolerable process average<\/b> used in <\/span>attributes acceptance sampling<\/b> to control lot disposition via a defined <\/span>sampling plan<\/b>.\u00a0<\/span><\/p>\n

Under the plan\u2019s <\/span>operating characteristic (OC) curve<\/b>, lots at the AQL have ~95% probability of acceptance (<\/span>\u03b1\u22480.05<\/b>).\u00a0<\/span><\/p>\n

You specify separate AQL values by defect class\u2014e.g., 0% critical, 2.5% major, 4.0% minor in consumer goods; regulated goods may use \u22640.65% major and 0.1% or 0.065% critical.\u00a0<\/span><\/p>\n

AQL is a planning parameter, not \u201cthe percentage you allow in the sample.\u201d The acceptance numbers in AQL tables come from binomial\/Poisson mathematics selected to hit target \u03b1\/\u03b2 risks across many production runs. You then compare the number of observed defects in your sample size with the Ac\/Re values to decide whether to accept or reject the batch<\/span><\/p>\n

When was AQL first developed?<\/span><\/h3>\n

AQL\u2019s roots trace to <\/span>Bell Labs in the 1930s<\/b>, when <\/span>Harold F. Dodge<\/b> and <\/span>H. G. Romig<\/b> developed <\/span>acceptance sampling<\/b> for mass production.\u00a0<\/span><\/p>\n

During <\/span>World War II<\/b>, method was adopted for large-scale U.S. military procurement and eventually formalized as <\/span>MIL-STD-105<\/b>, which harmonized with <\/span>ANSI\/ASQ Z1.4<\/b> and ultimately informed today\u2019s <\/span>ISO 2859-1<\/b>.\u00a0<\/span><\/p>\n

Gradually, the terminology changed from\u201cacceptable quality level\u201d to \u201cacceptance quality limit\u201d to emphasize that AQL is a limit, not a target. Many sectors kept lineage variants\u2014e.g., food programs referencing Codex STAN 233.\u00a0<\/span><\/p>\n

The modern ecosystem includes OC curves, switching rules (normal\/tightened\/reduced), and consistent sample size logic that buyers, suppliers, and quality assurance teams can apply to global supply chain decisions.<\/span><\/p>\n

\"Aql

Aql History<\/p><\/div>\n

What are the benefits of using AQL?\u00a0<\/span><\/h3>\n

AQL improves objectivity, reduces cost versus 100% inspection, aligns expectations, and strengthens supplier governance. Six key advantages include:<\/span><\/p>\n

    \n
  • Quantify risk<\/b>: Calibrate producer\u2019s risk near 5% at AQL and consumer\u2019s risk near 10% at RQL\/LTPD; decisions rely on defined probability, not guesswork.<\/span><\/li>\n
  • Reduce effort<\/b>: Typical sample size (e.g., code K n=125 or L n=200) inspects a fraction of the lot, cutting time versus 100% checks.<\/span><\/li>\n
  • Align stakeholders<\/b>: Common defaults (0\/2.5\/4.0) are widely understood across exporters and manufacturers, speeding decision making.<\/span><\/li>\n
  • Support clarity<\/b>: Clear acceptance criteria (e.g., n=125 at 2.5% \u2192 Ac7\/Re8) prevents disputes.<\/span><\/li>\n
  • Scale economically<\/b>: Sample size and acceptance increase sub-linearly with lot size, avoiding crude \u201cinspect 10%\u201d rules.<\/span>
    <\/span>Enable governance<\/b>: Works for incoming, in-process, and final quality inspections, and supports switching rules for stability or escalation.<\/span><\/li>\n<\/ul>\n

    How does acceptable quality limit (AQL) work?\u00a0<\/span><\/h2>\n

    You start by selecting your <\/span>lot size<\/b>, <\/span>inspection level<\/b> (I\/II\/III or S-levels), and AQL values by defect class; look up a <\/span>code letter<\/b>; read the <\/span>sample size<\/b> and <\/span>acceptance number<\/b>\/<\/span>rejection number<\/b>; then count <\/span>defects<\/b> and decide.\u00a0<\/span><\/p>\n

    Technically, the plan\u2019s OC curve defines <\/span>alpha (producer\u2019s risk)<\/b> and <\/span>beta (consumer\u2019s risk)<\/b> across many lots.<\/span><\/p>\n

    Examples anchor the mapping: <\/span>Lot 1,500 \u2192 code K \u2192 n=125<\/b>; <\/span>Lot 3,201\u201310,000 \u2192 code L \u2192 n=200<\/b>; <\/span>Lot ~15,000 \u2192 code M \u2192 n=315<\/b>. Typical acceptance limits under <\/span>normal inspection, Level II<\/b>:<\/span><\/p>\n

      \n
    • n=125 at <\/span>AQL 2.5% (major)<\/b> \u2192 <\/span>Ac7\/Re8<\/b><\/li>\n
    • AQL 4.0% (minor)<\/b> \u2192 <\/span>Ac10\/Re11<\/b><\/li>\n
    • n=200 at 2.5% \u2192 <\/span>Ac10\/Re11<\/b>; at 4.0% \u2192 <\/span>Ac14\/Re15<\/b>.<\/span><\/li>\n
    • n=315 at 2.5% \u2192 <\/span>Ac14\/Re15<\/b>; at 4.0% \u2192 <\/span>Ac21\/Re22<\/b>.<\/span><\/li>\n<\/ul>\n

      For a 50,000 lot at Level II and AQL 2.5%, n\u2248500 with roughly Ac21\/Re22 (single-sample attributes plan). In Table 2, arrow cells show when to adjust a plan up or down to keep target risks at boundaries. RQL\/LTPD sets the \u201cbad\u201d level; the IQL (indifference quality level) lies between AQL and RQL.<\/span><\/p>\n

      How do the AQL tables function, and what standards are they based on?<\/span><\/h2>\n

      AQL tables implement <\/span>ISO 2859-1 \/ ANSI\/ASQ Z1.4<\/b> single-sample plans<\/b> under <\/span>normal inspection<\/b>, mapping <\/span>lot size<\/b> and <\/span>inspection level<\/b> to a <\/span>sample size code letter<\/b>, then to <\/span>sample size<\/b> and <\/span>Ac\/Re<\/b> at chosen AQLs.\u00a0<\/span><\/p>\n

      Historically, they descend from <\/span>MIL-STD-105<\/b>; food programs may use <\/span>Codex STAN 233<\/b> variants.<\/span><\/p>\n

      Table 1<\/b> provides the sample size code letter (e.g., K, L, M).\u00a0<\/span><\/p>\n

      Table 2<\/b> converts that code into n and lists AQL columns (0.0 \/ 0.65 \/ 1.0 \/ 2.5 \/ 4.0 \/ 6.5) with acceptance numbers.\u00a0<\/span><\/p>\n

        \n
      • General Inspection Levels<\/b> I\/II\/III scale n (II is the default; I is smaller; III is larger).\u00a0<\/span><\/li>\n
      • Special Inspection Levels<\/b> S-1..S-4 yield very small n for targeted or destructive tests.<\/span><\/li>\n<\/ul>\n

        Anchors<\/b>:\u00a0<\/span><\/p>\n

          \n
        1. Code L \u2192 n=200;\u00a0<\/span><\/li>\n
        2. at 2.5% major \u2192 Ac10\/Re11;\u00a0<\/span><\/li>\n
        3. at 4.0% minor \u2192 Ac14\/Re15. Code M \u2192 n=315;<\/span><\/li>\n
        4. at 2.5% \u2192 Ac14\/Re15<\/span><\/li>\n
        5. at 4.0% \u2192 Ac21\/Re22.\u00a0<\/span><\/li>\n<\/ol>\n

          ISO 2859-10 discourages ad-hoc \u201cinspect x%\u201d because risks are undefined. In Codex STAN 233, smaller n and net-weight\/content checks reflect destructive opening.\u00a0<\/span><\/p>\n

          All of this keeps quality control processes consistent across industries, companies, and manuals.<\/span><\/p>\n

          Once you understand how AQL tables link inspection levels and acceptance criteria to specific sample sizes, the next step is to see how lot or batch size directly influences those calculations.<\/span><\/p>\n

          What is the lot or batch size?<\/span><\/h3>\n

          The <\/span>lot (batch) size<\/b> is the count of homogeneous units presented for <\/span>sampling<\/b> and a single accept\/reject decision.\u00a0<\/span><\/p>\n

          In this context, <\/span>mixed SKUs<\/b> are separate lots.\u00a0<\/span><\/p>\n

          The lot size defines which sample size code applies in <\/span>Table 1<\/b> and thus <\/span>n<\/b> in <\/span>Table 2<\/b>.\u00a0<\/span><\/p>\n

          Examples (General Level II):\u00a0<\/span><\/p>\n

            \n
          • 1,201\u20133,200 \u2192 code K\u00a0<\/span><\/li>\n
          • 3,201\u201310,000 \u2192 code L\u00a0<\/span><\/li>\n
          • 10,001\u201335,000 \u2192 code M\u00a0<\/span><\/li>\n<\/ul>\n

            A <\/span>1,500-unit<\/b> lot (one SKU) yields <\/span>code K \u2192 n=125<\/b>; ~<\/span>8,000<\/b> units \u2192 <\/span>code L \u2192 n=200<\/b>; <\/span>15,000<\/b> units \u2192 <\/span>code M \u2192 n=315<\/b>.\u00a0<\/span><\/p>\n

            For <\/span>in-process<\/b> checks before completion, many practitioners size the lot as the <\/span>quantity ready<\/b> (e.g., <\/span>50,000 ready \u2192 n=500<\/b>).\u00a0<\/span><\/p>\n

            Proper carton dispersion (see <\/span>FAQ<\/b>) improves representativeness across <\/span>cartons<\/b> and <\/span>positions<\/b>.<\/span><\/p>\n

            What is the inspection level?\u00a0<\/span><\/h3>\n

            The <\/span>inspection level<\/b> specifies how intensively you sample under the standard. <\/span>General I\/II\/III<\/b> set broad effort:\u00a0<\/span><\/p>\n

              \n
            1. Level I<\/b> (smaller n) for lower risk or trusted suppliers;\u00a0<\/span><\/li>\n
            2. Level II<\/b> (default) balances cost and detection;<\/span><\/li>\n
            3. Level III<\/b> (larger n) for higher risk, new tooling, or complaint histories<\/span><\/li>\n
            4. Special S-1 to S-4<\/b> use small sample sizes for focused checks (e.g., packaging dimensions, label legibility, destructive tests).\u00a0<\/span><\/li>\n<\/ol>\n

              Example with <\/span>lot 1,500<\/b>: Level I \u2192 <\/span>n=50<\/b>; Level II \u2192 <\/span>n=125<\/b>; Level III \u2192 <\/span>n=200<\/b>. You might run <\/span>S-1 (n=5)<\/b> on outer-carton measurements while keeping workmanship at <\/span>General Level II<\/b>. Choose levels by risk exposure and the cost-of-inspection vs cost-of-failure trade-off.<\/span><\/p>\n

              What are the AQL limits?\u00a0<\/span><\/h3>\n

              AQL limits<\/b> are the selected <\/span>quality level<\/b> parameters\u2014by defect severity\u2014that drive <\/span>acceptance numbers<\/b> in <\/span>Table 2<\/b>.\u00a0<\/span><\/p>\n

              Typical consumer defaults: <\/span>0% critical<\/b>, <\/span>2.5% major<\/b>, <\/span>4.0% minor<\/b>.\u00a0<\/span><\/p>\n

              Stricter programs may apply <\/span>1.0%<\/b> or <\/span>0.65%<\/b> for major in high-reliability <\/span>electronics<\/b>; <\/span>medical\/pharma<\/b> often set critical at <\/span>0.1%<\/b> or <\/span>0.065%<\/b>.\u00a0<\/span><\/p>\n

              Example mappings under Level II:\u00a0<\/span><\/p>\n

                \n
              • n=125<\/b> \u2192 2.5% <\/span>Ac7\/Re8<\/b><\/li>\n
              • 4.0% <\/span>Ac10\/Re11<\/b>. <\/span>n=200<\/b> \u2192 2.5% <\/span>Ac10\/Re11<\/b><\/li>\n
              • 4.0% <\/span>Ac14\/Re15<\/b>. <\/span>n=315<\/b> \u2192 2.5% <\/span>Ac14\/Re15<\/b><\/li>\n
              • 4.0% <\/span>Ac21\/Re22<\/b>.\u00a0<\/span><\/li>\n<\/ul>\n

                Remember, <\/span>acceptance numbers don\u2019t equal the AQL percentage of n<\/b>; the plan controls \u03b1 (producer\u2019s risk) and \u03b2 (consumer\u2019s risk) across multiple lots, rather than reflecting a single-sample proportion<\/span><\/p>\n

                How do you read AQL Table 1 (sample size code letters)?\u00a0<\/span><\/h2>\n

                You read <\/span>AQL Table 1<\/b> by locating your <\/span>lot size<\/b> row and chosen <\/span>inspection level<\/b> column to obtain the <\/span>sample size code letter<\/b>, which you\u2019ll carry to <\/span>Table 2<\/b> to find <\/span>sample size<\/b> and <\/span>acceptance criteria<\/b>.\u00a0<\/span><\/p>\n

                Here are the four main steps:\u00a0<\/span><\/p>\n

                  \n
                1. find the <\/span>lot<\/b> interval<\/span><\/li>\n
                2. select <\/span>General I\/II\/III<\/b> or <\/span>Special S-1..S-4<\/b><\/li>\n
                3. read the <\/span>code letter<\/b><\/li>\n
                4. go to <\/span>Table 2<\/b> to get <\/span>n<\/b> and <\/span>Ac\/Re<\/b>.\u00a0<\/span><\/li>\n<\/ol>\n

                  For example:\u00a0<\/span><\/p>\n

                    \n
                  • Lot 3,201\u201310,000 at Level II \u2192 code L \u2192 n=200.\u00a0<\/span><\/li>\n
                  • Lot 1,201\u20133,200 at Level II \u2192 code K \u2192 n=125<\/span><\/li>\n
                  • Lot 10,001\u201335,000 at Level II \u2192 code M \u2192 n=315\u00a0<\/span><\/li>\n<\/ul>\n

                    Special levels yield much smaller <\/span>n<\/b> (e.g., <\/span>S-1<\/b> can be <\/span>n=5<\/b> at 1,500 units).\u00a0<\/span><\/p>\n

                    Use <\/span>normal inspection<\/b> unless <\/span>switching rules<\/b> require a tightened or reduced level.<\/span><\/p>\n

                    \"How

                    How To Read Aql Table 1<\/p><\/div>\n

                    Compact reference (excerpt):<\/b><\/p>\n

                      \n
                    • 281\u2013500 \u2192 G\/I=E, II=F, III=G<\/span><\/li>\n
                    • 501\u20131,200 \u2192 H\/I=G, II=H, III=J<\/span><\/li>\n
                    • 1,201\u20133,200 \u2192 <\/span>K<\/b> (Level II)<\/span><\/li>\n
                    • 3,201\u201310,000 \u2192 <\/span>L<\/b> (Level II)<\/span><\/li>\n
                    • 10,001\u201335,000 \u2192 <\/span>M<\/b> (Level II)<\/span><\/li>\n<\/ul>\n

                      With the code letter from Table 1 in hand, you can use Table 2 to find the exact sample size and acceptance numbers for making lot decisions<\/span><\/p>\n

                      How do you read AQL Table 2 (single-sample plans for normal inspection, Level II)?\u00a0<\/span><\/h2>\n

                      You read <\/span>AQL Table 2<\/b> by finding the <\/span>row<\/b> for your <\/span>code letter<\/b>, noting the <\/span>sample size (n)<\/b>, then using the <\/span>AQL column<\/b> (e.g., <\/span>0.0<\/b>, <\/span>1.0<\/b>, <\/span>2.5<\/b>, <\/span>4.0<\/b>, <\/span>6.5<\/b>) to get <\/span>Ac\/Re<\/b> and decide pass\/fail per defect class.\u00a0<\/span><\/p>\n

                        \n
                      • Code K (n=125)<\/b>: <\/span>AQL 2.5 \u2192 Ac7\/Re8 (major)<\/b>;\u00a0<\/span><\/li>\n
                      • AQL 4.0 \u2192 Ac10\/Re11 (minor)<\/b>;\u00a0<\/span><\/li>\n
                      • AQL 0.0 \u2192 Ac0\/Re1 (critical)<\/b>. <\/span>Code L (n=200)<\/b>: 2.5 \u2192 <\/span>Ac10\/Re11<\/b>;\u00a0<\/span><\/li>\n
                      • 4.0 \u2192 <\/span>Ac14\/Re15<\/b>. <\/span>Code M (n=315)<\/b>: 2.5 \u2192 <\/span>Ac14\/Re15<\/b>; 4.0 \u2192 <\/span>Ac21\/Re22<\/b>.\u00a0<\/span><\/li>\n<\/ul>\n

                        When a cell shows an <\/span>arrow<\/b>, follow it to the plan <\/span>above<\/b> (up arrow) or <\/span>below<\/b> (down arrow) to maintain \u03b1\/\u03b2 at boundary conditions.<\/span><\/p>\n

                        \"How

                        How To Read Aql Table 2<\/p><\/div>\n

                        What happens when you land on an arrow in Table 2?\u00a0<\/span><\/h3>\n

                        When you land on an arrow in Table 2 follow the arrow immediately: <\/span>up arrow \u2192 use the plan above; down arrow \u2192 use the plan below<\/b>.\u00a0<\/span><\/p>\n

                        The tables place arrows at discrete breakpoints so that <\/span>alpha\/beta risks<\/b> remain smooth as you cross <\/span>lot size<\/b> or <\/span>AQL<\/b> boundaries.\u00a0<\/span><\/p>\n

                        Example: a small-n boundary (e.g., a <\/span>code E<\/b> row near <\/span>AQL 2.5%<\/b>) with a <\/span>down arrow<\/b> directs you to inspect <\/span>n=20<\/b> with an appropriate <\/span>Ac\/Re<\/b> such as <\/span>Ac1\/Re2<\/b> in that region\u2014preventing step-changes that would distort decision risks.<\/span><\/p>\n

                        Which inspection levels should you choose and why?\u00a0<\/span><\/h2>\n

                        Start at <\/span>General Inspection Level II<\/b> for most <\/span>consumer goods<\/b> because it balances detection and throughput.<\/span><\/p>\n

                        Move to <\/span>Level III<\/b> for higher risk (new supplier, customer complaints, new tooling) and down to <\/span>Level I<\/b> for trusted suppliers and low-hazard items.\u00a0<\/span><\/p>\n

                        Use <\/span>Special levels (S-1..S-4)<\/b> for targeted, <\/span>time-intensive<\/b>, or <\/span>destructive<\/b> checks while keeping workmanship at a General level.\u00a0<\/span><\/p>\n

                        With <\/span>lot 1,500<\/b>, the throughput trade-off is visible: Level I \u2192 <\/span>n=50<\/b>, Level II \u2192 <\/span>n=125<\/b>, Level III \u2192 <\/span>n=200<\/b>.\u00a0<\/span><\/p>\n

                        S-levels may reduce a packaging test to <\/span>n=5\u201332<\/b> while you still inspect workmanship at <\/span>General Level II<\/b>.\u00a0<\/span><\/p>\n

                        Align level choice with potential harm, <\/span>brand<\/b> impact, warranty exposure, and <\/span>inspection costs<\/b>. Products from high-end brands or those that are safety-critical require stricter sampling.<\/span><\/p>\n

                        What are the General Inspection Levels (I, II, III)?<\/span><\/h3>\n

                        General levels define the <\/span>sampling intensity<\/b> for overall workmanship and functional checks.\u00a0<\/span><\/p>\n

                          \n
                        • Level I<\/b> lowers <\/span>sample size<\/b> for cost control when processes are stable<\/span><\/li>\n
                        • Level II<\/b> is the <\/span>standard<\/b> (better <\/span>discrimination<\/b> at reasonable effort)<\/span><\/li>\n
                        • Level III<\/b> increases n for maximum detection. At the same <\/span>lot size<\/b> (e.g., <\/span>1,500<\/b> units), <\/span>n<\/b> might swing from <\/span>50 (I)<\/b> to <\/span>125 (II)<\/b> to <\/span>200 (III)<\/b>.\u00a0<\/span><\/li>\n<\/ul>\n

                          Choose <\/span>III<\/b> if recent failures or new tooling raise risk; choose <\/span>I<\/b> for cost savings after SPC shows stability and <\/span>customer expectations<\/b> are met.<\/span><\/p>\n

                          What are the Special Inspection Levels (S-1 to S-4)?\u00a0<\/span><\/h3>\n

                          Special levels provide <\/span>very small samples<\/b> to cover focused or limited-scope inspections\u2014useful when tests are <\/span>destructive<\/b>, slow, or peripheral.\u00a0<\/span><\/p>\n

                          Examples:<\/span><\/p>\n

                            \n
                          • S-1<\/b> for outer-carton <\/span>width<\/b>\/dimensions<\/span><\/li>\n
                          • S-2\/S-3<\/b> for slow function tests<\/span><\/li>\n
                          • S-4<\/b> for moderate effort\u00a0<\/span><\/li>\n<\/ul>\n

                            For a 1,500-unit lot, S-1 can be n=5. Keep General Level II for workmanship to protect product quality while applying S-levels for packaging, labeling, or power-cycle tests that would otherwise consume units.<\/span><\/p>\n

                            How do you calculate and apply AQL using the tables?<\/span><\/h2>\n

                            At a high level, you define the lot, select <\/span>inspection level<\/b>, pick <\/span>AQLs<\/b>, find the code letter in Table 1, then read <\/span>n\/Ac\/Re<\/b> in <\/span>Table 2<\/b> and inspect randomly.\u00a0<\/span><\/p>\n

                            There are six main steps:<\/span><\/p>\n

                            1) Define lot & defect classes (H3)<\/b><\/h3>\n

                            Fix <\/span>lot size<\/b> and defect taxonomy (<\/span>critical\/major\/minor<\/b>) for consistent <\/span>quality assessment<\/b>.<\/span><\/p>\n

                            2) Choose inspection severity & level (H3)<\/b><\/h3>\n

                            Default to <\/span>normal inspection<\/b>, <\/span>General Level II<\/b>; escalate or reduce via <\/span>switching rules<\/b>.<\/span><\/p>\n

                            3) Select AQLs by class (H3)<\/b><\/h3>\n

                            Typical defaults: <\/span>0\/2.5\/4.0<\/b>; tighten for high hazard or stricter <\/span>customers<\/b>.<\/span><\/p>\n

                            4) Read code letter in Table 1 (H3)<\/b><\/h3>\n

                            Map <\/span>lot size<\/b> \u00d7 <\/span>inspection level<\/b> \u2192 <\/span>code letter<\/b> (e.g., <\/span>L<\/b> for 5,000 at Level II).<\/span><\/p>\n

                            5) Read n and Ac\/Re in Table 2 (H3)<\/b><\/h3>\n

                            Find <\/span>sample size<\/b> and <\/span>acceptance number<\/b>; note <\/span>arrows<\/b> and boundary rules.<\/span><\/p>\n

                            6) Inspect randomly and decide (H3)<\/b><\/h3>\n

                            Randomly select samples across <\/span>\u221acartons (often +1)<\/b>; tally <\/span>defect levels<\/b>; compare to <\/span>Ac\/Re<\/b>; document.<\/span><\/p>\n

                            Worked example 1 (consumer product, AQL 2.5 major\/4.0 minor)<\/b><\/h3>\n

                            Decision first: <\/span>Lot 1,500<\/b>, <\/span>Level II<\/b>, <\/span>code K \u2192 n=125<\/b>.\u00a0<\/span><\/p>\n

                            With <\/span>AQL 2.5\/4.0<\/b>, the plan is <\/span>Ac7\/Re8 (major)<\/b> and <\/span>Ac10\/Re11 (minor)<\/b>; <\/span>critical 0.0% \u2192 Ac0\/Re1<\/b>.\u00a0<\/span><\/p>\n

                            If you find <\/span>6 major + 9 minor<\/b>, the lot <\/span>passes<\/b>; <\/span>8 major<\/b> or <\/span>11 minor<\/b> means <\/span>fail<\/b>; any <\/span>critical defects<\/b> means <\/span>fail<\/b>.\u00a0<\/span><\/p>\n

                            Pull samples across <\/span>\u221acartons (+1)<\/b>\u2014e.g., 100 cartons \u2192 select <\/span>11<\/b> cartons to improve representativeness.<\/span><\/p>\n

                            Worked example 2 (regulated product, AQL 0.65 major\/0.1 critical)<\/b><\/h3>\n

                            Decision first: <\/span>Lot 5,000<\/b>, <\/span>Level II<\/b>, <\/span>code L \u2192 n=200<\/b>. With <\/span>critical 0.1%<\/b>, use <\/span>Ac0\/Re1<\/b>; with <\/span>major 0.65%<\/b>, typical <\/span>Ac2\/Re3\u2013Ac3\/Re4<\/b> depending on the exact cell; <\/span>minor<\/b> could be <\/span>1.5\u20132.5%<\/b>.\u00a0<\/span><\/p>\n

                            Such <\/span>aql inspection <\/b>choices account for stricter safety requirements; if failures cluster, switch to <\/span>tightened<\/b> severity per the standard\u2019s <\/span>switching rules<\/b> and document <\/span>containment<\/b> and <\/span>traceability<\/b> actions before shipment.<\/span><\/p>\n

                            What is an AQL calculator or sampling simulator, and when should you use one?\u00a0<\/span><\/h2>\n

                            An <\/span>AQL calculator<\/b> is a tool that automates <\/span>sample size<\/b> selection, <\/span>acceptance numbers<\/b>, and sometimes <\/span>OC curve<\/b> visualization from <\/span>ISO 2859-1<\/b>\/<\/span>ANSI Z1.4<\/b> inputs.<\/span><\/p>\n

                            Use it for large portfolios, training, and \u201cwhat-if\u201d cases when manual table lookup slows work. <\/span>.<\/p>\n

                            [\/et_pb_text][et_pb_code _builder_version=”4.27.5″ _module_preset=”default” global_colors_info=”{}” theme_builder_area=”post_content”]<\/p>\n

                            <\/p>\n

                            AQL Sample Size & Acceptance Calculator<\/h3>\n

                            Enter your lot size, inspection level, and AQLs by defect class. The sampling plan will appear below once the required fields are filled. <\/pee><\/p>\n

                            <\/p>\n