APICS Operations Management Body of Knowledge Framework, Third Edition

4.4 Quality

In operations management, quality has two major components: quality of conformance, or the quality defined by the absence of defects; and quality of design, or the quality measured by the degree of customer satisfaction with a product's characteristics and features.

4.4.1 Cost of quality

Costs of quality reflect the overall costs associated with prevention activities and the improvement of quality throughout the firm in all phases of the production of a product. These costs fall into four recognized categories: internal failures, external failures, appraisal costs, and prevention costs.

4.4.2 Principal theorists

W. Edwards Deming. Deming developed theories and concepts applicable to quality management and statistical quality control, first in Japan and later in the United States. Deming is credited as one of the fathers of the philosophy widely referred as total quality management.

Kaoru Ishikawa. Ishikawa was a Japanese philosopher and professor. In 1950, he developed the cause-and-effect diagram (also called the fishbone diagram or Ishikawa diagram). This diagram starts with the end result (the effect) and attempts to trace the causes of quality problems back from that point.

Joseph M. Juran. Juran, along with Deming, introduced statistical quality control (SQC) techniques in Japan and subsequently the United States. SQC is the application of statistical techniques to control quality, and includes concepts associated with acceptance sampling.

4.4.3 Total quality management (TQM)

TQM is an approach to improving quality and ultimately customer satisfaction. The term was first used to describe Japanese-style management approaches to quality management. It relies on the participation of all members of the organization. The methods of implementing this approach are found in the works of Armand Feigenbaum, Philip Crosby, W. Edwards Deming, Joseph M. Juran, Kaoru Ishikawa, and others. The overall goals of TQM are lower costs, higher revenues, satisfied customers, and empowered employees.

4.4.4 Six sigma

Six sigma is a methodology that emphasizes reducing process variability and product deficiencies to improve product quality and customer satisfaction. In the theory, at a six sigma level of performance, only 3.4 defects occur for every one million opportunities, assuming the process is operating within 1.5 standard deviations of the center of the process specification.

.1 Quality improvement tools

Kaoru Ishikawa, a principal theorist in quality improvement, stated that as much as 95 percent of all quality issues in the factory can be solved with seven fundamental quality tools: (1) flowcharts, (2) Pareto charts, (3) cause-and-effect diagrams, (4) control charts, (5) check sheets, (6) scatter diagrams, and (7) histograms.

.2 Continuous improvement

Continuous improvement means an ongoing effort to expose and eliminate the root causes of problems, which leads to incremental improvements over time.

In six sigma, the improvement process has five stages. The stages are grouped collectively as the acronym DMAIC:

  • Define the nature of the problem.
  • Measure the existing performance and record data and facts that offer information to determine the root causes of the problem.
  • Analyze the information to determine the root causes of the problem.
  • Improve the process by implementing solutions to the problem.
  • Control the process until the solutions become ingrained.

4.4.5 Business process reengineering (BPR)

BPR is the fundamental rethinking and radical redesign of business processes to achieve dramatic organizational improvements in critical measures of performance, such as cost, quality, service, and speed. The goal of BPR is to eliminate non-value-added activities, sometimes achieving these results through automation.

4.4.6 Statistical techniques

Statistical techniques are used to study and understand variations in processes and populations, interactions among these variables, and operational definitions. The ultimate goal is reducing variation in a process or population.

.1 Normal distribution

In this statistical distribution, most observations fall within one standard deviation (a measure of dispersion) from the mean, the measure of central tendency. In a normal distribution, observations are equally likely to be greater or less than the mean, as the dispersion is symmetrical. When graphed, the normal distribution takes the form of a bell-shaped curve.

.2 Process capability

Process capability is the ability of a process to produce parts that conform to engineering specifications. Process capability deals with the inherent variability of a process in a state of statistical control and its relationship to design tolerances. Measures of process capability have the notations Cp and Cpk. Cp considers both sides of the mean. Cpk relates to either side of the mean, but not both.

.3 Statistical process control (SPC)

SPC is the application of statistical techniques to control quality. Sometimes the term is used interchangeably with statistical quality control (or is considered the main subset of statistical quality control).

Variable data. Variable, or quantitative, data take the form of numerical values and arise from measuring a characteristic of a product, service, or process; or from the computation of two or more measurements. There are no set categories or values that variable data can take. Heights and weights are examples of variable data.

Attribute data. Attribute data take form from the classification of items, such as products or services, into categories. Alternatively, they may be represented by counts or proportions of items in a given category or counts of occurrences per unit. Some examples of attribute data are found in binary categories, such as go/no-go information and the reporting of gender.

Chart types. Control charts are graphical comparisons of process performance data with predetermined control limits. The data usually consist of samples of a fixed size selected at regular intervals. Control charts are used primarily to detect assignable causes of variation in processes and rule out random variations. The most common control charts are the X-bar chart (used to track sample means) and the c chart (used to track attribute defects).

.4 Average outgoing quality (AOQ)

AOQ is the expected average quality level of outgoing product for a given value of incoming product quality.

.5 Acceptance sampling

Acceptance sampling typically is used for determining whether a batch of parts conform to a quality specification. This is executed through a sampling process in which the number of units in the sample and the maximum number of defective items are defined. If defects exceed the maximum acceptable amount, the entire batch is rejected.

4.4.7 Benchmarking and best practices

Benchmarking is the continuous process of measuring products, services, costs, and practices. The two types of benchmarking are competitive (a comparison against the industry best) and process (a comparison to the best in class). Best practices, through the benchmarking process, identify opportunities for improvement. The process of comparing a result to a best practice may be applied to resources, activities, and costs.

4.4.8 ISO registration

The standards issued by the Belgium-based organization ISO, whose English name is the International Organization of Standardization, have been adopted by more than 100 nations and are supported by most national standards organizations.

ISO 9000 is a set of five related international standards on quality management and assurance, developed to help companies document the elements needed to maintain an efficient quality system.