ENBIS: European Network for Business and Industrial Statistics
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ENBIS-12 in Ljubljana
9 – 13 September 2012 Abstract submission: 15 January – 10 May 2012The following abstracts have been accepted for this event:
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How to Design Experiments when Categoric Mixture Components Go to Zero
Authors: Pat Whitcomb (Stat-Ease, Inc.)
Primary area of focus / application: Design and analysis of experiments
Keywords: design of experiments (DOE), mixtures, mixture experiments, categoric factors
A preservative blend (used to maximize shelf life of a food product) with a categoric factor whose proportion goes to zero is used to illustrate the method. -
Applications of Bayesian Networks
Authors: Ron S. Kenett (KPA / University of Turin)
Primary area of focus / application: Modelling
Keywords: Cause and Effect, Bayesian Networks, Bayesian Analysis, Conditional Distributions
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The Significance of Measurement Systems Analysis within the Lean Philosophy
Authors: Phil Lewis (Coventry University), Gillain Cooke (Coventry University)
Primary area of focus / application: Quality
Keywords: Measurement Systems Analysis, Lean, Waste/Muda reduction, Cost Down, SME
Submitted at 5-Mar-2012 13:33 by Phillip Lewis
Accepted
Within these business sectors the availability of statisticians and expert practitioners is freely available. However the associated supply chains of these business sectors exhibit the practices created by the lean operations drive which has promoted all forms of verification and measurement as “non value added” (NVA). Thus the concept that a NVA process is underpinned by a series of “complicated” statistics has arguably provided an excuse for it to be ignored.
An investigation into the current accepted practice within the SME activity would unveil many instances of disagreements between entities of the supply chain where contrasting measurements have been obtained. The resolution over which measurement is correct potentially erodes reduced profit margins further.
The ongoing demand for waste/NVA reduction and “cost down” activity could be achieved through the dissemination of MSA into various organisational interfaces. Linking the process improvement activity to the MSA arena to statistically evaluate confidence levels within organisation interacting measurement systems and thus align the process capability of measurement systems to ultimately enable Muda reductions.
This paper evaluates the theoretical problems arising from measurement systems misalignments and shows a need for a generic MSA framework which supports the relevant lean philosophy. -
Detection of Abrupt Changes in Count Data Time Series: Cumulative Sum Derivations for INARCH(1) Models
Authors: Christian H. Weiß (Darmstadt University of Technology), Murat Caner Testik (Hacettepe University)
Primary area of focus / application: Process
Keywords: Count data time series, CUSUM control chart, INARCH(1) model, INAR(1) model, overdispersion
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Water Quality Function Deployment
Authors: Shuki Dror (ORT Braude College), Natalia Zaitsev (ORT Braude College)
Primary area of focus / application: Quality
Keywords: water, quality, technology, QFD
Submitted at 16-Mar-2012 06:01 by Shuki Dror
Accepted
The Quality Function Deployment (QFD) is utilized as an instrument for ranking the relevant technologies. The QFD is designed to reveal where the quality of water characteristics requires improvement and to translate the deficiencies into demands on technical water characteristics and ultimately into relative importance of relevant technologies.
First, we range the wishes and the conceived preferences of the final customers (“voice of the customer” – VOC) for tap water quality. Customers’ requirements for tap water quality are obtained by a survey, which includes two groups of questions, aimed to assess the desirability of six separate characteristics of water quality, and to estimate the gap between the desired water quality and its perceived present state. The six characteristics are: odor, turbidity, color, calcification (scaling), taste, and absence of biological pollutants. In order to assess the required improvement level of each characteristic to the customer, we define the importance level of a characteristic as the mean of the importance of the characteristic multiplied by the mean gap between the desired level and the perceived present situation for the same characteristic.
In the next stage, we conduct an expert survey, which consists of two groups of questions.
In the first group, the expert is asked to estimate the influence of technical parameters of the water on the perceived characteristics of the water quality as provided by the customers. The relative importance of the following 10 parameters were calculated using QFD method: hardness, acidity, chlorine/chloramines, fluoride, nitrate, chloride (salinity), solid colloids, total organic carbon, iron, and dissolved oxygen.
The second group of questions in the expert survey comprises relevant water treatment technologies and their effect on the technical parameters. Again the experts estimated the contribution of each one of the relevant technologies to the improvement of the technical water parameters and the relative importance were calculated.
The list of technologies includes more than a dozen principal technologies, such as: desalination, microfiltration, granular filtration (sand/coal bedding), UV sterilization, reduction of acidity, chlorination, etc.
To construct the water QFD two matrices representing the questionnaire results have to be analyzed. Normalized improvement scores are calculated at each of the three hierarchical levels: customer requirements, technical parameters and technologies. The components to be improved at each of the above levels are selected by means of the MSE (Mean Square Error). We find that the desalination is the vital technology for improving water quality. -
Restricted Kernel Canonical Correlation Analysis
Authors: Nina Otopal (IMFM)
Primary area of focus / application: Mining
Keywords: kernel, canonical correlation, nonnegativity, restrictited