ENBIS: European Network for Business and Industrial Statistics
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ENBIS11 in Coimbra
4 – 8 September 2011 Abstract submission: 1 January – 25 June 2011The following abstracts have been accepted for this event:

Identification of Adequate Reliability Verification Targets
Authors: Nikolaus Haselgruber Franz Langmayr Christopher Gray
Primary area of focus / application: Reliability
Keywords: Reliability , Reliability Target , Testing , Product Development
The classical way is to decompose a given reliability target defined for the complete product according to its hierarchic structure. This approach has several shortcomings, e.g. that in particular the test effort required to demonstrate the targets derived for components and subsystems is usually too high and does not fit to given development budgets.
The presentation shows an approach for the allocation of verification targets which considers a priori information from technical experts’ experience and, if available, field reliability observations of the forerunner product. 
Improving Shewharttype Control Charts for Monitoring Uni and Multivariate Process Variability
Authors: Emanuel Pimentel Barbosa , Mario Antonio Gneri and Ariane Meneguetti
Affiliation: Universidade Estadual de Campinas  UNICAMP
Primary area of focus / application: Process
Keywords: statistical process control , control charts , monitoring variability , Tukey studentized range , CornishFisher correction , Meijer Gfunction
In this paper we show that this sort of “adhoc” procedures inflates substantially the alpha risk (probability of false alarm) and therefore should be avoided. Improved versions of these control charts are presented in this paper based on exact or better approximations of the sample statistic distributions and their quantiles (chart limits).
For the R statistic we explore its relation with the Tukey’s maximum studentized range statistic distribution which provides simpler alternative background than the traditional Tippett`s integral formulae as well as it provides an easily way of implementation.
In this paper the sample S statistic is better approximated using CornishFisher quantile correction as well as it`s exact distribution is provided using the Mejer Gfunction, available in some recent mathematical software.
The advantages of the proposed improved charts are shown in terms of alpha risk and ARL(Average Run Length) , and a couple of examples with real data are provided. 
Likelihood Ratio Control Charts for Multivariate Process Variability Monitoring and Testing of Covariance Matrices
Authors: Emanuel Pimentel Barbosa , Mario Antonio Gneri and Ariane Meneguetti
Affiliation: Universidade Estadual de Campinas  UNICAMP
Primary area of focus / application: Process
Keywords: statistical process control , multivariate control charts , monitoring variability , likelihood ratio statistic
In this paper, five different methods for approximating the 2 lnLR statistic distribution (basic chisquare, SatterthwaiteBartlett, BoxKorin, Sugiura and Improved Sugiura) are compared in terms of false alarm risk for each method through simulation of ten million samples (based on Wishart random matrices, using Matlab). Also from this simulation study, one table of upper quantiles (alpha equal 0,0027) is produced for dimensions p = 2, 3 and 4 and sample sizes N from 3 to 10, 15, 20 and 30, which makes possible the practical implementation of the 2lnLR control chart. In order to illustrate the proposed mehod, a numerical example with real data is provided from a three dimensional quality characteristics of a production process. 
Measurement Uncertainty  A Process Improvement Tool
Authors: Phil Lewis
Affiliation: Coventry University  Faculty of Engineering and Computing
Primary area of focus / application: Metrology & measurement systems analysis
Keywords: MeasurementUncertainty , Design , Supplychain , Profitmargin
Submitted at 30Apr2011 17:15 by Phillip Lewis
Accepted
Within these business sectors the availability of statisticians and expert practitioners is freely available. Once the step is made into the various supply chains of any business sector the culture which has been created by the lean operations drive has promoted all forms of verification and measurement as “non value added”. Thus the concept that a NVA process also has an unknown has 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 and the resolution over which one is correct erodes reduced profit margins frantically.
The emerging trend of designing and managing processes “up stream” must be suitable for the introduction of “design for measurement uncertainty” which would introduce the process improvement concept into the measurement arena to statistically evaluate confidence levels within any organisation measurement systems and thus align the process capability of measurement systems and their alignment from interacting department right through to OEM’s partnerships with second tier suppliers and trade dealers. 
Incomplete jigsaw puzzle model of problem solving process
Authors: Jan M. Msyzewski
Affiliation: Kozminski University, Warsaw
Primary area of focus / application: Quality
Keywords: knowledge management, , problem solving , data transfer , jigsaw puzzle solving
Submitted at 1May2011 21:01 by Jan Myszewski
Accepted
A process of problem solving is represented by the metaphor of solving jigsaw puzzle, with some pieces missing. In particular, certain number are missing permanently.
Problem solving is a special case of process of the knowledge management in organization. Important part are processes of data transfer between participants. Model of incomplete jigsaw puzzle enables describing these transfers by use of some probabilistic distributions.
The model enables discussion of variants of strategies of problem solving and their association with organizations culture and knowledge management. 
A Comparison of Decision Procedures for Cpk when Data are Autocorrelated
Authors: Peder Lundkvist Kerstin Vännman Murat Kulahci
Primary area of focus / application: Quality
Keywords: process industry , continuous process , autocorrelation , capability index Cpk
The purpose of the presentation is to compare the performance of three different decision rules in process capability analysis using the process capability index when data are autocorrelated. This is done through a case study followed by a simulation study. In the case study the data is obtained for the weight percentage of the carbon content in pig iron from a blast furnace process, and can be described by an AR(1)model. In the simulation study the significance level and power of each method are investigated.