1,720,974 research outputs found
Ordered samples control charts for ordinal variables
Full text linkThe paper presents a new method for statistical process control when ordinal variables are involved. This is the case of a quality characteristic evaluated by an ordinal scale. The method allows a statistical analysis without exploiting an arbitrary numerical conversion of scale levels and without using the traditional sample synthesis operators (sample mean and variance). It consists of a different approach based on the use of a new sample scale obtained by ordering the original variable sample space according to some specific ‘dominance criteria' fixed on the basis of the monitored process haracteristics. Samples are directly reported on the chart and no distributional shape is assumed for the population (universe) of evaluations. Finally, a practical application of the method in the health sector is provided
Qualitative ordinal scales: the concept of ordinal range
Full text linkMany practical problems of quality control involve the use of ordinal scales. Questionnaires planned to collect judgments on qualitative or linguistic scales, whose levels are terms such as "good," "bad," "medium," etc., are extensively used both in evaluating service quality and in visual controls for manufacturing industry. In an ordinal environment, the concept of distance between two generic levels of the same scale is not defined. Therefore, a population (universe) of judgments cannot be described using "traditional" statistical distributions since they are based on the notion of distance. The concept of "distribution shape" cannot be defined as well. In this article, we introduce a new statistical entity, the so-called ordinal distribution, to describe a population of judgments expressed on an ordinal scale. We also discuss which of the traditional location and dispersion measures can be used in this context and we briefly analyze some of their properties. A new dispersion measure, the ordinal range, as an extension of the cardinal range to ordinal scales, is then proposed. A practical application in the field of quality is developed throughout the articl
A General Framework for Multiresponse Robust Design based on Combined Array
No full textAlthough multiple responses are quite common in practical applications, the robust design problem is frequently dealt with by considering only one response. In this paper we present a general framework for the multivariate problem when data are collected from a combined array. Within the framework, both parameter and tolerance design are handled in an integrated way. The optimization criterion is based on a single value in terms of the quadratic loss function, and it is selected in order to incorporate both statistical information (such as correlation structure among responses and prediction uncertainty) and economic information relevant to the product or process (such as priorities and trade-offs among responses from the user’s point of view). An illustrative application is presented on the design of the elastic element of a force transducer
Um modelo para a terceirização. Como uma empresa pode monitorar e administrar seu terceirizado em todas as etapas que requerem tomada de decisões
No full textOutsourcing: guidelines for a structured approach
Full text linkOutsourcing is a management approach by which an organization delegates some noncore functions to specialized and ef®cient service providers. In the era of ªglobal marketº and ªe-economyº, outsourcing is one of the main pillars of the new way to conceive the relationships among companies. Despite outsourcing large diffusion, huge business cases and big deals of documentation available on network or press, there is no structured procedure able to support the govern of the evolution of a generic outsourcing process. In accordance with the principles of total quality management, this paper describes a proposal of a new approach for managing outsourcing processes. The model, which can be easily adapted to different application ®elds, has been conceived with the main aim of managing strategic decisions, economic factors and human resources. The approach is supported by different decision and analysis tools, such as benchmarking techniques, multiple criteria decision aiding (MCDA) methods, cost analysis, and other process-planning methodologies. An application of the method to a real case is also provide
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