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By John Carson and Stephen N. Luko
Sep 03, 2025
The subcommittee on statistical quality control (E11.30), part of the committee on quality and statistics (E11), focuses on developing standards for statistical process control (SPC) and related methods, including acceptance sampling, control charts, process capability, and significant digits and rounding.
The subcommittee’s standards are built in part on the foundations of the original ASTM Manual on Presentation of Data (now ASTM Manual 7, Manual on Presentation of Data and Control Chart Analysis) and on the military standard (MIL-STD) acceptance sampling procedures.1 These in turn had developed from foundational contributions from statisticians like Harold Dodge, Walter Shewhart, and others, before and during World War II. In the early years of E11, beginning in 1946, a number of notable applied statisticians served in E11 and contributed to the standards that E11.30 is currently responsible for. Among these were Dodge, A. E. R. Westman, O. P. Beckwith, Charles Bicking, S. Collier, J. H. Curtiss, W. E. Deming, E. G. Olds, L. E. Simon, Grant Wernimont, S. S. Wilks, and W. J. Youden. In the mid-1970s, the committee was opened up to all ASTM members, and it grew almost tenfold.2 Today, the subcommittee has 133 members with 123 official voters.
The committee’s most popular standard, by sales and by reference from other standards, is the standard practice for using significant digits in test data to determine conformance with specifications (E29). This standard was originally published in 1940 and has gone through many revisions over the years in order to keep up with changes in technology, as well as practice.
Several of the E11.30 standards address acceptance sampling, which is used by producers to qualify lots or production runs of product for sale and by customers for acceptance of products. The standard practice for use of process oriented AOQL and LTPD sampling plans (E1994) preserves, and is a guide to, the use of the original Dodge-Romig average outgoing quality limit (AOQL) and lot tolerance percent defective (LTPD) sampling plans.
Several of these sampling standards preserve military standard sampling procedures, recognizing the continuing usage of MIL-STD-105E, MIL-STD-414, MIL-STD-1916, and MIL-STD-1235B in industries supported by ASTM. These standards are no longer supported by the U.S. Department of Defense as of the mid-1990s and are out of print. In all of the MIL-STD preservation standards, the technical content is preserved exactly as originally published. The text was updated to reflect ASTM form and style for standards. Where appropriate, some tables were updated with additional significant digits, and corrections were made to table values where errors were detected in the original.
The standard practice for sampling a stream of product by attributes indexed by AQL (E2234) preserves the original MIL-STD-105E acceptable quality limit (AQL) attributes sampling plans. Attributes are quality indicators that are pass/fail rather than continuous quantities. The standard practice for sampling a stream of product by variables indexed by AQL (E2762) preserves the original MIL-STD-414 sampling plans by variables. Variables are measured quality indicators that take continuous values. The standard practice for single- and multi-level continuous sampling of a stream of product by attributes indexed by AQL (E2819) preserves the original MIL-STD-1235B. It provides a basis for sampling a steady stream of lots, versus intermittent batch production, using attributes indexed by AQL. It includes sequential sampling schemes, which are more complex to implement but are also much more efficient than single sample size designs.
The standard guide for preferred methods for acceptance of product (E2910) preserves MIL-STD-1916 “to support the movement away from an AQL-based inspection (detection) strategy to implementation of an effective prevention-based strategy including a comprehensive quality system, continuous improvement, and a partnership with the consumer.” This includes, as appropriate, control charts, traceability, corrective action, and all aspects of modern quality systems.
The standard practice for process capability and performance measurement (E2281) is a vital resource for assessing manufacturing or service process capability relative to specifications.3
The standard practice for setting an upper confidence bound for a fraction or number of non-conforming items, or a rate of occurrence for non-conformities, using attribute data, when there is a zero response in the sample (E2334) is an important standard for very low or “zero” defect processes or for using smaller sample sizes to monitor quality when special inspection levels are used. It allows bounding the “unknown fraction or quantity non-conforming, or a rate of occurrence for nonconformities” when zero defects are observed in the sample in three cases of sampling from a:
While “zero defects” is a popular idea in quality control, the implications of zero failures in the sample depends very much on the sample size and on the rate of possible misclassification errors. “Allowance is made for misclassification error in this standard but only when misclassification rates are well understood or known and can be approximated numerically.”
The standard practice for use of control charts in statistical process control (E2587) covers the use of control charting in SPC. It covers most types of control charts that are commonly used in industry. Although acceptance sampling has many essential uses, including receiving inspection for material and parts, final checks on finished products, and receiving inspection by the customer, in the opinion of the authors, control charting is the most powerful and effective SPC tool. In addition to its uses in manufacturing, it is a vital tool for quality control and improvement in laboratories.
The subcommittee on statistical quality control continues to improve these standards. Although E11 standards can be very technical, they are developed and improved to be viable tools for many types of practitioners, while meeting the needs expressed by the greater ASTM community of users. If you are a practitioner of SPC, we would welcome your participation. ●
References
1) Ullman, N. and Luko, S. (2010). “Statistical Standards and ASTM,” Quality Engineering, 22(4), p. 358–363. https://doi.org/10.1080/08982112.2010.500171.
2) Neubauer, D. V and, Luko, S. N. (2010). “Statistical Standards and ASTM, Part 2,” Quality Engineering, 23(1), p. 100–104. https://doi.org/10.1080/08982112.2011.529055.
3) Parendo, Carol. (2025). “Cpk vs. Ppk: Clearing Up the Confusion,” Standardization News, July/August. https://www.astm.org/news/cpk-vs-ppk-clearing-up-the-confusion.
John Carson, Ph.D., is senior statistician for Neptune and Co. and the Data Points column coordinator. Carson is the current chair of E11.30 and a member of the committees on quality and statistics (E11); petroleum products, liquid fuels, and lubricants (D02); air quality (D22); environmental assessment, risk management, and corrective action (E50); and personal protective clothing and equipment (F23).
Stephen N. Luko is a retired fellow and statistician at United Technologies Corp/Collins Aerospace. He is chair of the subcommittee on reliability (E11.40); a member of the quality and statistics committee (E11); an ASTM International fellow; Harold F. Dodge Award recipient; and a former E11 chair.
September / October 2025
