June 7, 2017

Statistical Quality Control – Industrial Engineering

SQC is an Efficiency Improvement Technique

SQC is brought into industrial engineering practice as an efficiency improvement technique.

In a narrow sense, some companies refer to their product inspection activity as quality control. In such companies inspection is the sole quality assurance activity. In many companies, now, a more elaborate quality assurance process is installed. In these organizations, quality control encompasses not only inspection but also quality planning, process controls, incoming material control, analysis and correction action in respect of defects, and quality reporting. An appropriate definition for quality control is “quality control is a system for verification and maintenance of a desired level of quality in a product or process by careful planning, the use of proper equipment, continuing inspection, and corrective action where required.”

Is industrial engineering department responsible for quality control? Some scholars in the IE discipline think so. But according to me, IE curriculums had only “Statistical quality control (SQC)” as a subject. Statistical quality control alone does not cover the entire scope of quality engineering and quality management.

Why only SQC? Because Statistical quality control is an efficient improvement innovation for quality engineering. Statistical quality control text books generally provide the explanation on the following lines (Halpern[1]).

Inspection of finished production on a 100% basis is a technique, which, with proper controls, theoretically should be one of the surest ways to eliminate defective products from being supplied to the next stage in production or ultimately to the customer. In practice, the 100% inspection is not as fool proof as may be expected. Experience has shown that the monotony and repetition inherent in 100% inspection tends to create boredom and fatigue with the result that not all defective units are eliminated. Thus in inspection activity, a behavioral dimension is brought in.

Statistical quality control technique of acceptance sampling, is relatively inexpensive as it inspects only a small percentage of items from a production lot or shipping lot, less time consuming, not fatiguing for inspectors, and it is based on well-established principles of probability theory.

The underlying idea is that SQC provides as good a quality assurance as 100% inspection provides and the cost involved in very low compared to 100% inspection.

Industrial engineers as efficiency designers understood the productivity potential of SQC, accepted SQC and promoted its use in practice. For introducing SQC, industrial engineers need not become functional quality system designers. The functional quality specialists still decide what characteristics of the product or item is to be inspected and how it is to be inspected. Industrial engineers design acceptance plans and install the SQC systems and demonstrate its utility and maintain the system. Thus industrial engineers collaborate with the quality specialists and play their role in the design of quality control system. But as the SQC evolved over 75 years period, quality engineers and managers now are capable of developing SQC systems and the role of IEs is now minimal. But productivity improvement of inspection and quality processes is still the task of IEs and this issue is covered in a separate note.

Poka Yoke is contributed by Industrial Engineer, Shigeo Shingo to quality engineering area.

Types of sampling plans



MIL-STD-105D is for inspection by attributes. This means the inspected item is classified as either acceptable or defective. It has the following features:

1. Plans

MIL-STD-105D provides two types of plans which protect lot quality.

i). AQL plans

ii). LTPD plans

2. Level of inspection

Three general inspection levels. I, II, and III.

For small sample sizes, four levels, S1, S2, S3, and S$.

3. Inspection severity

i) Normal

ii) Tightened inspection

iii) Reduced inspection

4. Sampling types

Three basic sampling methods: simple, double and multiple

MIL:-STD-414 is for inspection by variable.


Sigmund Halpern, The Assurance Sciences, Prentice Hall, 1978

Originally posted in

Industrial Engineering Knowledge Revision Plan - One Year Plan

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Updated 9 June 2017, 14 December 2011

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