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:

Examining Potential Reductions in Wind Tunnel Testing Data Requirements
Authors: Raymond Hill (Air Force Institute of Technology), Douglas A. Dillard (Air Force Institute of Technology), Darryl K. Ahner (Air Force Institute of Technology), Douglas C. Montgomery (Arizona State University)
Primary area of focus / application: Other: US Session and Tribute to Stephen Fienberg
Keywords: Experimentation, Regression, RSM, Modeling
Submitted at 25Apr2017 18:08 by Raymond Hill
Accepted

Control Charts on Dependent Streams
Authors: Moshe Pollak (The Hebrew University of Jerusalem and Israel Central Bureau of Statistics)
Primary area of focus / application: Process
Secondary area of focus / application: Quality
Keywords: Cusum, ShiryaevRoberts, Average run length to false alarm, Exponential distribution
We argue that despite the dependence structure, when the process is in control, for large ARL's to false alarm, run lengths of parallel Cusumtype control charts are asymptotically independent. Furthermore, often, incontrol run lengths are asymptotically exponentially distributed, enabling uncomplicated asymptotic expressions for the ARL2FA. We prove this assertion for certain Cusum and ShiryaevRobertstype control charts and illustrate it by simulations. 
MultiplicityCause Economic and Economic Statistical Design of T2Control Charts Under Proportional Hazards Shock Model
Authors: Mojtaba Aghajanpoor Pasha (Allameh Tabataba'i University), Mohammad Bameni Moghadam (Allameh Tabataba'i University), Nader Nematollahi (Allameh Tabataba'i University)
Primary area of focus / application: Quality
Secondary area of focus / application: Reliability
Keywords: Multiple assignable causes, Increasing failure rate, Proportional hazards shock model, Expected cost per unit time, Economic statistical design
Submitted at 1May2017 09:34 by Mojtaba Aghajanpoor Pasha
Accepted

Benchmarking Rater Agreement Indices: Statistical Properties and Power Analysis
Authors: Amalia Vanacore (University of Naples Federico II), Maria Sole Pellegrino (University of Naples Federico II)
Primary area of focus / application: Other:
Keywords: Interrater agreement, Intrarater agreement, Kappatype indices, Monte Carlo simulation
Submitted at 3May2017 11:50 by Amalia Vanacore
Accepted
The reviewed indices are Gwet’s AC1 and the linear weighted variants of Scott’s Pi coefficient, Cohen’s Kappa and BrennanPrediger statistic. In order to evaluate the statistical behavior of the reviewed indices and of a nonparametric benchmarking procedure, a Monte Carlo simulation study has been conducted for several scenarios differing from each other in sample size, rating scale dimension and agreement level. The estimate precision is evaluated in terms of relative bias, variance and coverage rate of the percentile bootstrap confidence interval, whereas the effectiveness of the benchmarking procedure is assessed in terms of statistical power.
Simulation results suggest that the analyzed indices have satisfactory estimate precision that improves as n, k and agreement level increase and a coverage rate close to its nominal level, only for n ≥ 30; the benchmarking procedure is generally adequately powered in testing null and nonnull cases of rater agreement and thus it can be suitably applied for the characterization of agreement over a small or moderate number of subjective ratings provided by one or more raters. 
Kriging Modelization in Predicting Metal Sheet Elongation
Authors: Valentina Calì (Università degli studi di Torino), Maria Teresa Giraudo (Università degli studi di Torino), Roberto Sofia (Amada Engineering Europe), Grazia Vicario (Politecnico di Torino)
Primary area of focus / application: Design and analysis of experiments
Keywords: LH designs, Kriging, Variogram, FEM, Bend deduction
Submitted at 4May2017 16:16 by Valentina Calì
Accepted
We resort to the most popular metamodel, the Kriging model, applied to an industrial instance: prediction of the Bend Deduction. Metal sheet bending is a manufacturing process in which a plastic deformation of the work pieces over an axis occurs. This is a metal forming process, and similar to the other processes, bending changes the shape of the work pieces.
The work focuses on the construction of an optimal initial design in order to achieve a good accuracy of the metamodel at an acceptable computational cost, on the theoretical study of this model and on understanding how it could be conformed to the bend deduction prediction.
The correlation structure, mandatory in a Kriging model, has been evaluated by means of the variogram, whose refinements of its specification naturally improve the Kriging predictions. The empirical variograms for each input variable brought to light unusual behaviors. This peculiarity suggested that the bending angle could be related with the bend deduction according to two different models with a discontinuity certain in their relationship but uncertain where it is.
Then the accuracy achieved has been evaluated using different indicators of the robustness and of the uncertainty of the leaveoneout methods. 
Electroluminescence Image Analysis and Suspicious Areas Detection
Authors: Evgenii Sovetkin (RWTHAachen), Ansgar Steland (RWTHAachen)
Primary area of focus / application: Metrology & measurement systems analysis
Secondary area of focus / application: Quality
Keywords: Image processing, Nonparametrics, Changepoint, Spatial statistics
Submitted at 6May2017 11:35 by Evgenii Sovetkin
Accepted
We first consider several practical issues that arise in field studies, i.e.\ when images are taken under outdoor conditions and not in a lab. We discuss a new problemspecific procedure for automatic correction of rotation and perspective distortions, which to some extent employs statistical approaches such as robust regression; and a procedure for automatic detection of the module and its cell areas (by means of a modified version of the Hough Transform). Those techniques provide us with images of the PV module cells, intensity light of which are of the main interest in quality study.
Secondly, we discuss a spatial test to screen large databases of EL image data aiming at the detection of malfunctioning cells. The spatial test statistics is based on comparing sample averages inside two regions indexed by a region location parameter. The asymptotics is established for a general class of random fields for several of regions sets.
Lastly, we discuss simulation studies and an application of the method to the real EL image data.