947 resultados para Quality Control Circles


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Issued Oct. 1977.

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Issued Oct. 1977.

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Mode of access: Internet.

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Federal Highway Administration, Washington, D.C.

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Bibliography: p. 467-548.

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Mode of access: Internet.

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Background and purpose Survey data quality is a combination of the representativeness of the sample, the accuracy and precision of measurements, data processing and management with several subcomponents in each. The purpose of this paper is to show how, in the final risk factor surveys of the WHO MONICA Project, information on data quality were obtained, quantified, and used in the analysis. Methods and results In the WHO MONICA (Multinational MONItoring of trends and determinants in CArdiovascular disease) Project, the information about the data quality components was documented in retrospective quality assessment reports. On the basis of the documented information and the survey data, the quality of each data component was assessed and summarized using quality scores. The quality scores were used in sensitivity testing of the results both by excluding populations with low quality scores and by weighting the data by its quality scores. Conclusions Detailed documentation of all survey procedures with standardized protocols, training, and quality control are steps towards optimizing data quality. Quantifying data quality is a further step. Methods used in the WHO MONICA Project could be adopted to improve quality in other health surveys.

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In order to survive in the increasingly customer-oriented marketplace, continuous quality improvement marks the fastest growing quality organization’s success. In recent years, attention has been focused on intelligent systems which have shown great promise in supporting quality control. However, only a small number of the currently used systems are reported to be operating effectively because they are designed to maintain a quality level within the specified process, rather than to focus on cooperation within the production workflow. This paper proposes an intelligent system with a newly designed algorithm and the universal process data exchange standard to overcome the challenges of demanding customers who seek high-quality and low-cost products. The intelligent quality management system is equipped with the ‘‘distributed process mining” feature to provide all levels of employees with the ability to understand the relationships between processes, especially when any aspect of the process is going to degrade or fail. An example of generalized fuzzy association rules are applied in manufacturing sector to demonstrate how the proposed iterative process mining algorithm finds the relationships between distributed process parameters and the presence of quality problems.

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This Thesis reports on the principles and usefulness of Performance Rating as developed by the writer over a number of years. In Part one a brief analysis is made of the Quality scene and its development up to the present. The need is exposed for Performance Rating as a tool for all areas of management*. At the same time a system of Quality Control is described which the writer has further developed under the title of 'Operator Control'. This system is based on the integration of all Quality control functions with the creative functions required for Quality achievement. The discussions are mainly focussed on the general philosophy of Quality, its creation and control and that part of Operator Control which affects Performance Rating. Whereas it is shown that the combination of Operator Control and Performance Rating is both economically and technically advantageous, Performance Rating can also usefully be applied under inspection control conditions. Part two describes the principles of Area Performance Rating. *The need for, and the advantages of, Performance Rating are particularly demonstrated in Case study No.1. From this a summation expression is derived which gives the key for grouping of areas with similar Performance Rating (P). A model is devised on which the theory is demonstrated. Relevant case studies, carried out in practice in factories are quoted in Part two, Chapter 4, one written by the Quality manager of that particular factory. Particular stress is laid in the final conclusions on management's function in the Quality field and how greatly this function is eased and improved through the introduction of Area Performance Rating.

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Previously, specifications for mechanical properties of casting alloys were based on separately cast test bars. This practice provided consistently reproducible results; thus, any change in conditions was reflected in changes in the mechanical properties of the test coupons. These test specimens, however, did not necessarily reflect the actual mechanical properties of the castings they were supposed to represent'. Factors such as section thickness and casting configuration affect the solidification rate and soundness of the casting thereby raising or lowering its mechanical properties in comparison with separately cast test specimens. In the work now reported, casting shapes were developed to investigate the variations of section thickness, chemical analysis and heat treatment on the mechanical properties of a high strength Aluminium alloy under varying chilling conditions. In addition, an insight was sought into the behaviour of chills under more practical conditions. Finally, it was demonstrated that additional information could be derived from the radiographs which form an essential part of the quality control of premium quality castings. As a result of the work, it is now possible to select analysis and chilling conditions to optimize the as cast and the heat treated mechanical properties of Aluminum 7% Silicon 0.3% Magnesium alloy.

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The service-producing industries have experienced problems in quality in the 1980s because of intense competition. The author discusses how these problems have been compounded in the fast food industry and how quality control can lead to success.