UNDERSTANDING QUALITY CONTROL
➢ Quality Control is a process by which entities review the quality of all factors involved in production. This approach places emphasis on three aspects: o Elements such as controls, job management, defined and well managed processes, performance and integrity criteria, and identification of records o Competence, such as knowledge, skills, experience, and qualifications o Soft elements, such as personnel integrity, confidence, organizational culture, motivation, team spirit, and quality relationships The quality of the outputs is at risk if any of these three aspects is deficient in any way. ➢ Quality control is a major component of total quality management; and the quality-control cycle consists of four steps: quality planning, data collection, data analysis, and implementation. o 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 o 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. o 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,...
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