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quality control[′kwäl·əd·ē kən‚trōl]
The operational techniques and the activities that sustain the quality of a product or service in order to satisfy given requirements. Quality control is a major component of total quality management and is applicable to all phases of the product life cycle: design, development, manufacturing, delivery and installation, and operation and maintenance.
The quality-control cycle consists of four steps: quality planning, data collection, data analysis, and implementation. Quality planning consists of defining measurable quality objectives. Quality objectives are specific to the product or service and to the phase in their life cycle, and they should reflect the customer's requirements.
The collection of data about product characteristics that are relevant to the quality objectives is a key element of quality control. These data include quantitative measurements (measurement by variables), as well as determination of compliance with given standards, specifications, and required product features (measurement by attributes). Measurements may be objective, that is, of physical characteristics, which are often used in the control of the quality of services. Since quality control was originally developed for mass manufacturing, which relied on division of labor, measurements were often done by a separate department. However, in the culture of Total Quality Management, inspection is often done by the same individual or team producing the item.
The data are analyzed in order to identify situations that may have an adverse effect on quality and may require corrective or preventive action. The implementation of those actions as indicated by the analysis of the data is undertaken, including modifications of the product design or the production process, to achieve continuous and sustainable improvement in the product and in customer satisfaction.
The methods and techniques for data analysis in quality control are generic and can be applied to a variety of situations. The techniques are divided into three main categories: diagnostic techniques; process control, which includes process capability assessment and control charts; and acceptance sampling.
Diagnostic techniques serve to identify and pinpoint problems or potential problems that affect the quality of processes and products, and include the use of flowcharts, cause-and-effect diagrams, histograms, Pareto diagrams, location diagrams, scatter plots, and boxplots.
Process-control methods are applicable to systems that produce a stream of product units, either goods or services. They serve to control the processes that affect those product characteristics that are relevant to quality as defined in the quality objectives. For example, in a system that produces metal parts, some of the processes that might need to be controlled are cutting, machining, deburring, bending, and coating. The relevant product characteristics are typically spelled out in the specifications in terms of physical dimensions, position of features, surface smoothness, material hardness, paint thickness, and so on. In a system that produces a service, such as a telephone help line, the relevant processes could be answering the call, identifying the problem, and solving the problem. The characteristics that are relevant to quality as perceived by the customer might include response time, number of referrals, frequency of repeat calls for the same problem, and elapsed time to closure.
Process control focuses on keeping the process operating at a level that can meet quality objectives, while accounting for random variations over which there is no control. There are two main aspects to process control: control charts and capability analysis. Control charts are designed to ascertain the statistical stability of the process and to detect changes in its level or variability that are due to assignable causes and can be corrected. Capability analysis considers the ability of the process to meet quality objectives as implied by the product specifications.
Process-control techniques were originally developed for manufactured goods, but they can be applied to a variety of situations as long as the statistical distribution of the characteristics of interest can be approximated by the normal distribution. In other cases, the principles still apply, but the formula may need to be modified to reflect the specific mathematical expression of the probability distribution functions. See Process control
Acceptance sampling refers to the procedures used to decide whether or not to accept product lots or batches based on the results of the inspection of samples drawn from the lots. Acceptance sampling techniques were originally developed for use by customers of manufactured products while inspecting lots delivered by their suppliers. These techniques are particularly well suited to situations where a decision on the quality level of product lots and their subsequent disposition needs to be made, but it is not economic or feasible to inspect the entire production output.