Search results for "RCA"

showing 10 items of 3171 documents

Computer experiments combined with physical Experiments: two experiences in product development

2012

Physical experiments in industrial product development are often very expensive but also necessary sometimes even for safety reasons (think about the crash tests in the automotive industry conducted with new and completely equipped vehicles). Therefore there is a pressing need to reduce this cost as much as possible. Computer experiments may be a viable solution provided that their results are reliable as much as the physical ones. In most of the cases, computer experiments are opportunely combined with physical experiments and the recipe of such mix is interesting itself. In this presentation we will show two cases of combination of physical and computer experiments in product development.…

Settore SECS-S/02 - Statistica Per La Ricerca Sperimentale E TecnologicaDesign of ExperimentSettore SECS-S/01 - StatisticaComputer Experiments
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Indagine per la definizione di un modello statistico per lo studio della variabile "contenuto in proteine" nel frumento duro coltivato in Sicilia.

2011

A partire dal 2000 il Consorzio di Ricerca Gian Pietro Ballatore, nell'ambito del "Progetto Qualità e Tracciabilità del Grano Duro in Sicilia", ha attivato, in collaborazione con l'Assessorato delle Risorse Agricole e Alimentari della Regione Siciliana, un sistema di monitoraggio del grano duro, in modo tale da qualificarlo sulla base delle caratteristiche merceologiche, stoccarlo in maniera differenziata e rintracciarlo lungo la filiera. Nell'ambito della suddetta attività per ogni campagna granaria sono stati raccolti dati relativi alle partite di grano conferite presso i centri di stoccaggio che aderivano al progetto. In particolare sono state registrate informazioni sulla qualità merceo…

Settore SECS-S/02 - Statistica Per La Ricerca Sperimentale E TecnologicaModello statisticoproteineGrano duro
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The Use of Financial and Non-Financial Performance Measures: A Contingency Perspective

2013

Financial and non-financial index and indicators are applied in industry for measure firms’ business and operational performance. Different mix of measures are usually implemented in practice and we argue that, to a certain extent, this variability can be explained according to some contextual factors, as for instance environmental uncertainty, decentralization, type of strategic organizations and managerial practices.We develop hypothesis on the association between the usage of certain performance measures and this factors in a contingency perspective. Exploratory research based on large scale survey on manufacturing firms supports our investigation and test of the research hypothesis. R…

Settore SECS-S/02 - Statistica Per La Ricerca Sperimentale E TecnologicaPerformance Measurement System Metrics Contingency Theory Actual Performance Perceived Performance
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Rethinking the risk matrix

2011

So far risk has been mostly defined as the expected value of a loss, mathematically PL (being P the probability of an adverse event and L the loss incurred as a consequence of the adverse event). The so called risk matrix follows from such definition. This definition of risk is justified in a long term “managerial” perspective, in which it is conceivable to distribute the effects of an adverse event on a large number of subjects or a large number of recurrences. In other words, this definition is mostly justified on frequentist terms. Moreover, according to this definition, in two extreme situations (high-probability/low-consequence and low-probability/high-consequence), the estimated risk…

Settore SECS-S/02 - Statistica Per La Ricerca Sperimentale E TecnologicaRisk matrix Risk & sustainability Managerial perspective of risk Social perspective of risk
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Robust Product Development Using Variation Mode and Effect Analysis

2009

This is a book chapter. No abstract is present.

Settore SECS-S/02 - Statistica Per La Ricerca Sperimentale E TecnologicaRobust Design Variation Mode and Effect Analysis (VMEA)FMEA
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Enhanced TESF methodology for course excellence

2010

The need to achieve the excellence in services provided by a University has been object of study and research for several decades. Often, the focus is not only on the education service, but on several satellite services provided by a university. This article focuses on teaching, considered as a central service, believing (the authors) that the improvement actions of an academic institution should always start from this service. The work proposes the implementation of a tool able to measure student perceptions on certain selected aspects of the course. This tool is part of the Teaching Experiment and Student Feedback (TESF) methodology previously developed by the authors. Here, the steps to …

Settore SECS-S/02 - Statistica Per La Ricerca Sperimentale E TecnologicaSettore SECS-S/03 - Statistica EconomicaTeaching experimentSettore SECS-S/05 - Statistica SocialeCourse quality evaluationStudent satisfaction indexSERVQUALMeasuring improvement in education
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Statistical properties of a new student satisfaction index

2010

Quality of Higher Education is increasingly important in all developed countries. In fact quality and reputation are key elements to control the flow of students at national and international level. The authors have shown that quality of education can be improved through a process of self-assessment of the teaching services and a well studied analysis of the student feedback. In particular a new student satisfaction index was formulated which allows student feedback being summarised and interpreted for a continuous course improvement. In this paper some statistical properties of the student satisfaction index are illustrated, and comparisons with other measures based on Likert scales are ma…

Settore SECS-S/02 - Statistica Per La Ricerca Sperimentale E TecnologicaSettore SECS-S/03 - Statistica EconomicaTeaching experimentSettore SECS-S/05 - Statistica SocialeCourse quality evaluationStudent satisfaction indexSERVQUALMeasuring improvement in education
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La dimensione spaziale nella relazione tra cambiamento della popolazione e formazione di nuove imprese

2015

Questo contributo analizza la relazione tra cambiamento della popolazione e formazione di nuove imprese con particolare attenzione al ruolo dello spazio. Viene infatti, da un lato, analizzata l'influenza della concentrazione spaziale della popolazione rispetto la relazione di interesse, dall'altro, viene utilizzata una specificazione econometrica che tenga conto della correlazione spaziale presente nei dati. Lo studio condotto sulle province italiane per il periodo 2004/2007, mette in luce alcuni aspetti degni di nota. Tra questi, è di particolare interesse l'evidenza che nelle province con maggiore ritorno, in termini di natalità delle imprese, da un incremento della popolazione sono quell…

Settore SECS-S/02 - Statistica Per La Ricerca Sperimentale E TecnologicaSettore SECS-S/03 - Statistica Economicaformazione nuove imprese cambiamento popolazione statistica spaziale dati Italiani
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Implementation of Six Sigma in SMEs. A Case Study in Swedish Industry

2012

Many big companies today have already solid Six Sigma infrastructures. However, all over the world SMEs are only now approaching the methodology. In this presentation we expose an industrial application of a Six Sigma Black Belt project. It shows how Six Sigma was introduced and successfully implemented in a Swedish small-medium sized company. The project was carried out within the Six Sigma Black Belt course run at Chalmers University of Technology in Gothenburg. This case study is included in the book “Statistical and Managerial Techniques for Six Sigma Methodology, Theory and Application” (Wiley, 2012). The company is Structo Hydraulics AB, a manufacturing firm, located in Storfors, whic…

Settore SECS-S/02 - Statistica Per La Ricerca Sperimentale E TecnologicaSix SigmaIndustrial Statistics
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Statistical and managerial techniques for Six Sigma methodology. Theory and Application

2012

Settore SECS-S/02 - Statistica Per La Ricerca Sperimentale E TecnologicaSix SigmaSettore SECS-S/03 - Statistica EconomicaIndustrial StatisticsSettore SECS-S/05 - Statistica SocialeSettore SECS-S/01 - Statistica
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