The Dodge-Romig Sampling Inspection Tables, developed with Harry G. Romig in the early 1930s and published in 1940, are renown of Dodge’s pioneering work. Harold was a prominent member in the quality assurance department at Bell Laboratories from 1917 to 1958. This provided him the opportunity to work with Walter Shewhart, George Edwards, Harry G. Romig, R.L. Jones, Paul Olmstead, E.G.D. Paterson, and Mary N. Torrey. Their work resulted in the development of basic concepts of acceptance sampling, such as consumer’s risk, producer’s risk, double sampling, lot tolerance percent defective (LTPD), and average outgoing quality limit (AOQL). Harold also originated several types of acceptance sampling schemes, CSP type continuous sampling plans, chain sampling plans, and skip-lot sampling plans.

It is an acceptance sampling system used to inspect incoming, in-process, and final products to determine compliance with established acceptance criteria through the selection of random samples of items. Acceptance sampling uses switching rules on a continuing stream of lots for a specific predetermined Acceptable Quality Limit (AQL). The acceptance sampling system provides tightened, normal, and reduced plans to be applied depending upon actual product quality performance, more specifically percent nonconforming or nonconformities per 100 units.

The sampling Inspection Tables and procedures for sampling inspection theories and mathematical formulas resulted in Mil-STD-205. Military standards came from a need for a sampling system that did not require 100% inspection for use in testing munitions and other destructive tests. The result was the Army Service Forces inspection tables, which came out in 1942 and 1943. Improvement led to MIL-STD-105A, B, C, D, and E (1950, 1958, 1961, 1963, 1989) in subsequent years. Although widely adopted outside of military procurement applications, MIL-STD-105 was cancelled in 1995. The last revision was MIL-STD-105E; which was carried over in ASTM E2234. ASTM E2234 – Standard Practice for Sampling a Stream of Product by Attributes Indexed by AQL. This practice establishes lot or batch sampling plans and procedures for inspection by attributes using MIL-STD-105E as a basis for sampling a steady stream of lots indexed by acceptance quality limit (AQL).

The current Notice of Cancellation (Notice 3) in 2008 recommends that future acquisitions refer to: MIL-STD-1916, “DoD Preferred Methods for Acceptance of Product”, or ANSI/ASQ Z1.4, “Sampling Procedures and Tables for Inspection by Attributes”. Originally the ANSI/ASQC Z1.4 and ISO 2859-1 were created as commercial equivalents to the MIL-STD-105E. The 1999 revision of the ISO 2859-1 standard changed some of the Accept-reject number pairs. Thus, ISO 2859-1 is close but not quite the same as the ANSI/ASQ Z1.4 and MIL-STD-105E standards.

The ANSI/ASQ Z1.4 standard is similar in format to both MIL-STD-105E and ASTM E2234-09. However, it differs in its definition of a rejectable item. ANSI/ASQ Z1.4 employs definitions and terminology in accordance with ANSI/ISO/ASQ 3534-2:2006 Statistics-Vocabulary and Symbols = Part 2 Applied Statistics.

The following two definitions are particularly important in applying the standard:

  • Defect: A departure of a quality characteristic from its intended level or state that occurs with a severity sufficient to cause an associated product or service not to satisfy intended normal or foreseeable usage requirements.
  • Nonconformity: A departure of a quality characteristic from its intended level or state that occurs with severity sufficient to cause an associated product or service not to meet a specification requirement.

ANSI/ASQ Z1.4 presents acceptance sampling plans for attributes in terms of the percentage or proportion of product in a lot or batch that departs from some defined requirement. Several benefits for quality control and product inspection have been documented for its implementation.

  1. Improvement in Quality Control: The guidance provided in applying statistical methods to monitor and control process variables provides ensuring for stable and predictable processes.
  2. Lower Sampling Costs: The tightened, normal, and reduced plans are well defined and allow for an organization to select the most efficient approach.
  3. Time Efficient: The plans quickly reject bad lots and acceptance of good lots.
  4. Increase Accuracy of Data: Proper application of the sampling plans ensures the process results in accurate data with regards to product quality.
  5. Addresses Limited Resources: The standard provides a systematic approach to sampling while making informed decisions without overtaxing resources.