ENBIS: European Network for Business and Industrial Statistics
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ENBIS17 in Naples
9 – 14 September 2017; Naples (Italy) Abstract submission: 21 November 2016 – 10 May 2017The following abstracts have been accepted for this event:

A Note on the Minimum Sample Size and Critical Acceptance Value for Variables Sampling Inspection Scheme Based on Process Capability Indices Cpk and Cpmk
Authors: Antonio Lepore (University of Naples Federico II), Biagio Palumbo (University of Naples Federico II), Guido Cesaro (University of Naples Federico II)
Primary area of focus / application: Quality
Secondary area of focus / application: Six Sigma
Keywords: Quality control, Acceptance sampling, Process capability indices, Fuel consumption monitoring, Decisionmaking
Submitted at 10May2017 09:11 by Biagio Palumbo
Accepted
REFERENCES
[1] Lepore, A., & Palumbo, B. (2015). New Insights into the Decisional Use of Process Capability Indices via Hypothesis Testing. Quality and Reliability Engineering International, 31(8), 1725–1741. https://doi.org/10.1002/qre.1713
[2] Wu, C. W., Aslam, M., & Jun, C. H. (2012). Variables sampling inspection scheme for resubmitted lots based on the process capability index Cpk. European Journal of Operational Research, 217(3), 560–566. https://doi.org/10.1016/j.ejor.2011.09.042
[3] Pearn, W. L., & Wu, C. W. (2007). An effective decision making method for product acceptance. Omega, 35(1), 12–21. https://doi.org/10.1016/j.omega.2005.01.018
[4] Wu, C. W., & Pearn, W. L. (2008). A variables sampling plan based on Cpmk for product acceptance determination. European Journal of Operational Research, 184(2), 549–560. https://doi.org/10.1016/j.ejor.2006.11.032 
Misdiagnosis in Emergency Department and Its Impact on Hospital Load
Authors: Yariv Marmor (ORT Braude College of Engineering)
Primary area of focus / application: Other: Process improvement in healthcare
Keywords: Emergency department, Diagnosis, Misclassification, Tree structured data, Performance

Knowledge Improvement of an Additive Manufacturing Process via Stochastic Approach: Applicative Examples
Authors: Biagio Palumbo (University of Naples Federico II), Francesco Del Re (University of Naples Federico II), Pasquale Corrado (MBDA ITALIA), Giuseppe La Sala (MBDA ITALIA)
Primary area of focus / application: Design and analysis of experiments
Secondary area of focus / application: Quality
Keywords: Additive manufacturing, Direct metal laser sintering, Knowledge improvement, Stochastic approach, Design of Experiments
Submitted at 10May2017 12:08 by Francesco Del Re
Accepted
The aim of this work is to highlight, through three applicative examples, the strategic role that a systematic stochastic approach can play in the knowledge improvement of an Additive Manufacturing process based on the Direct Metal Laser Sintering technology, where threedimensional components are produced from metal powder.
In particular, the following key technological issues have been investigated: the effects of metal powder reusing and of topological printing strategies (i.e. component position and orientation within the printing volume) on the mechanical properties as well as the optimal settings of laser exposure parameters in terms of process productivity.
The experimental activities have been carried out after an accurate predesign phase in order to reduce efforts, costs and time required to investigate the process.
The applicative examples have been developed in partnership with MBDA ITALIA company and represent a positive example of synergic integration between statistical and technological competences. 
Distributions for the Maximum of a Random Number of Observations
Authors: Marta PerezCasany (Universitat Politècnica de Catalunya)
Primary area of focus / application: Reliability
Secondary area of focus / application: Modelling
Keywords: Extreme value theory, Generalized extreme value distribution, Generalized Pareto distribution, Positive Poisson distribution
Submitted at 10May2017 12:56 by Marta PerezCasany
Accepted
In many practical cases, one is interested in the maximum (minimum) value of a given measure during a given period of time or space, without knowing in advance how many observations there will be. In that case one needs to consider maximums (minimums) of a random number of independent copies of a given random variable, which is denoted as random stopped extreme distributions (RSED). The RSED depends on the distribution of the phenomena and on the distribution of the number of events. The main advantage of using RSED is that it does not require to have a large number of observations. The classical theory of Extreme values may be seen as a particular case. Emphasis will be given to the particular case where the number of observations follows a Positive Poisson distribution. 
A Stochastic Approach for Aerospace Industry Innovation via Engineering and Statistical Knowledge Integration
Authors: Gaetano De Chiara (Avio Aero), Roberto Marrone (Avio Aero), Biagio Palumbo (University of Naples, Federico II)
Primary area of focus / application: Other: Quality engineering applied to advanced manufacturing
Keywords: SixSigma, Laser drilling, Preexperimental planning phase, Design of Experiment
Submitted at 10May2017 13:09 by Roberto Marrone
Accepted
In this paper, the effectiveness of such approaches is demonstrated through several examples of laser drilling of combustion chambers for aerospace industry. In this technological field, many thousands of high quality small and shaped effusion holes need to be realized. The proposed examples have been developed within the Avio Aero industry, which is an aerospace company at the leading edge of propulsion technology. They show the continuous technological innovation of laser process in Avio Aero from conventional to fiber laser sources.
All experimental activities have been executed adopting a systematic approach in the preexperimental planning phase where predesign sheets have been conceived and implemented ad hoc. The remarkable results obtained in the last years make the Avio Aero plant in Pomigliano d’Arco the only European alternative for the production of advanced combustion chambers to GE Aviation American sites. 
Prediction of Coating Properties with Generalized Linear Models in an HVOF Spraying Process
Authors: EvaChristina BeckerEmden (FH Dortmund), Sonja Kuhnt (FH Dortmund)
Primary area of focus / application: Modelling
Keywords: HVOF spraying process, Generalized linear models, Model selection, Prediction of coating properties, Different spraying powders
Submitted at 10May2017 14:01 by EvaChristina BeckerEmden
Accepted
We use generalized linear models with different link functions and gamma distributed responses to describe the coating properties in dependence of particle properties, like particle temperature or velocity, and process parameters, like the feeder disc velocity. Previously only a WC12Co powder of type WOKA 3102 from Sulzer Metco was analysed. In this contribution, we run experiments on two further powders, namely WCFeCrAl and WCCo100nm. We analyse to which extend the models for WC12Co are transferable to other powders. Additionally, individual model selection for the new powders is conducted and results are compared. We base our model building on an allsubset selection with the BIC as selection criterion, and a maximal model containing main, twoway interaction and quadratic effects.
We find that the class of generalized linear models provides adequate prediction models for the individual coating properties. Possible extensions of the individual generalized linear models to a multivariate model are discussed.