ENBIS: European Network for Business and Industrial Statistics
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ENBIS14 in Linz
21 – 25 September 2014; Johannes Kepler University, Linz, Austria Abstract submission: 23 January – 22 June 2014The following abstracts have been accepted for this event:

A Model for \Delta T Approximation in Power Semiconductor Devices with Different DMOS Areas based on Energy Ramp Up Tests
Authors: Olivia Bluder (KAI  Kompetenzzentrum für Automobil und Industrieelektronik GmbH), Christoph Schreiber (Infineon Technologies Austria), Michael Ebner (Infineon Technologies Austria), Michael Glavanovics (KAI  Kompetenzzentrum für Automobil und Industrieelektronik GmbH)
Primary area of focus / application: Modelling
Secondary area of focus / application: Mining
Keywords: Semiconductors, Reliability, Modelling, SOA definition, \Delta T approximation
At semiconductor lifetime testing temperature is one of the driving forces leading to device failure. In literature various lifetime models exist, most of them depend either on the temperature rise (\Delta T) or the peak temperature (Tpeak), e.g. Arrhenius, Coffin Manson [1]. This implies that the knowledge about the temperature in the device is substantial to derive a reliable model. If measuring the exact temperature on a device during operation is not possible, commonly, electrothermal FEM simulations are carried out instead [2]. These FEM simulations are time consuming. To reduce the effort we investigated mathematical approaches to approximate the temperature by physics based relationships.
Data
The data set for this investigation contains results from energy ramp up (ERU) [3] tests of one power semiconductor device type. ERU tests are carried out at constant ambient temperature, pulse width and voltage. Via predefined current steps the energy is increased until the device fails. Results are available for 4 different DMOS areas, tested at 3 different ambient temperatures and 5 different pulse widths.
Model
Previous publications [3] show that with these measurement data \Delta T of a device can be approximated. For this purpose, the nonlinear relationship given by Glavanovics and Zitta [4] that links \Delta T to the maximum power, the pulse width and a thermal constant, is used. The thermal constant is a device specific value that accounts for structural and material properties. Commonly, it is assumed that for equal device types with different DMOS areas, the constant scales with the DMOS area, which means that the model is applicable for changes in DMOS area. The given data show that a simple scaling is not sufficient, because not only the thermal constant shows a nonlinear dependency on the area, but also the exponent of the pulse width. Based on these observations on the measured data and on physical assumptions we extended the current \Delta T model to include the DMOS area. With the added parameters we are able to model \Delta T for different DMOS areas of one device type and varying pulse length.
Bibliography
[1] L.A. Escobar and W.Q. Meeker, A review of accelerated test models, Statistical Science, 21, pp.552577, 2006.
[2] M. Bernadoni, “Thermal and electrothermal modeling of electronic devices and systems for highpower and highfrequency applications”, PhD thesis, Università degli Studi di Parma, 2012.
[3] A. Waukmann and M. Glavanovics, “EnergyRampUp Test Method for SOA Definition of Smart Power Switches with Application Relevant Stress Pulses”, in Austrochip, Villach, 2010
[4] M. Glavanovics and H. Zitta, "Thermal Destruction Testing: an Indirect Approach to a Simple Dynamic Thermal Model of Smart Power Switches", in ESSCIRC, Villach, 2001. 
Optimal Designs Subject to Cost Constraints in Simultaneous Equations Models
Authors: Jesus LopezFidalgo (University of CastillaLa Mancha), Victor Casero Alonso (University of CastillaLa Mancha)
Primary area of focus / application: Design and analysis of experiments
Secondary area of focus / application: Business
Keywords: Approximate design, Exact design, Loptimal design, Cost constraints, Multiplicative algorithm, Simultaneous equations, Structural equations

Official Statistics Data Integration to Enhance Information Quality
Authors: Luciana Dalla Valle (Plymouth University), Ron Kenett (KPA Ltd., University of Turin and NYU Poly)
Primary area of focus / application: Quality
Secondary area of focus / application: Economics
Keywords: Information quality (InfoQ), Data integration, Vines, Copulas, Bayesian networks, Administrative data, Official statistics
Submitted at 15May2014 19:37 by Luciana Dalla Valle
Accepted
This paper illustrates, with different case studies, a novel strategy to increase InfoQ based on the integration of official statistics data using copulas and Bayesian Networks. The ability to conduct such an integration is becoming a key requirement in combining official statistics such as census or survey based data with administrative data being routinely aggregated in operational systems.
Official statistics are extraordinary sources of information about many aspects of the citizens’ life, like health, education, public and private services, as well as the economic climate, the financial situation and the environment. However, many studies fail to consider the importance of these fundamental sources of information, leading to a poor level of InfoQ, implying low valued statistical analyses and poor informative results.
The use of copulas and Bayesian Networks, allows us to calibrate official statistics and organizational or administrative data, strengthening the quality of the information derived from a survey, and enhancing InfoQ. It also provides an ability to conduct studies with dynamic updates using structured and unstructured data thus enhancing several of the InfoQ dimensions. 
Megavariate and Multiscale Monitoring of the Process NETworked Structure: M2NET
Authors: Tiago Rato (University of Coimbra), Marco Reis (University of Coimbra)
Primary area of focus / application: Process
Keywords: Process monitoring of the correlation structure, Multiscale dynamical processes, Partial correlations, Sensitivity enhancing data transformations, Causal network, Wavelet transform
One approach for handling such type of systems was proposed by Bakshi (1998) [2]. The basic idea is to decompose the original observations into a set of scaledependent wavelet coefficients, which are then monitored simultaneously through parallel control charts. From the monitoring of the wavelet coefficients, the relevant scales can be selected and used to reconstruct the signal in the original domain, in what effectively corresponds to a feature extraction stage of the fault signature. Then, the reconstructed signal is subjected to a confirmatory assessment of the actual state of the process. Even though this methodology is conceptually simple, its implementation in the case of monitoring the correlation structure is not straightforward. For instance, the current online approaches tend to resort to EWMA like recursions [35], which cannot be applied at the data reconstruction level, since the scales included in the reconstructions are not always the same. Given these considerations, a new multiscale procedure involving monitoring statistics based on partial correlations and variables’ sensitivity enhancing transformations (SET) is proposed. This procedure allows for a finer description of the process, since the inner relationships between the variables are analyzed at each scale through partial correlations. The monitoring procedure is also more focused in the timefrequency scales related with the fault and therefore a better isolation of the fault’s signature is obtained and consequently the detection performance is improved.
The obtained results show that the proper modelling of the process network through the SET is a major factor in the detection of structural changes. In fact, it was observed that even singlescale monitoring statistics can achieve the same level of detection capability as their multiscale counterparts when a proper SET is employed. However, the multiscale approach still proved to be useful since it led to comparable results using a much simpler model. Therefore, the application of a wavelet decomposition is advantageous for systems that are difficult to model, providing a good compromise between modeling complexity and monitoring performance.
References:
1. Yen, et al., Quality and Reliability Engineering International, 2012. 28(4): p. 409426.
2. Bakshi, AIChE Journal, 1998. 44(7): p. 15961610.
3. Reynolds, et al., Journal of Quality Technology, 2006. 38(3): p. 230252.
4. Hawkins, et al., Technometrics, 2008. 50(2): p. 155166.
5. Bodnar, et al., Computational Statistics & Data Analysis, 2009. 53(9): p. 33723385. 
Exploiting Uncertainty Information for Empirical Model Building in Process Industries
Authors: Marco P. Seabra dos Reis (Department of Chemical Engineering, University of Coimbra), Ricardo Rendall (Department of Chemical Engineering, University of Coimbra), SweeTeng Chin (Analytical Tech Center, The Dow Chemical Company), Leo Chiang (Analytical Tech Center, The Dow Chemical Company)
Primary area of focus / application: Modelling
Secondary area of focus / application: Process
Keywords: Measurement uncertainty, Modelling heteroscedasticity, Principal Components Regression, Partial Least Squares, Weighted Least Squares, Ordinary Least Squares
Submitted at 18May2014 23:54 by Marco P. Seabra dos Reis
Accepted
In this talk, we will address the issue of deriving predictive models is situations closer to the ones found in CPIs, through a Monte Carlo study encompassing several models with high dimension, a variety of noise levels, and different levels of knowledge regarding the uncertainty structure of data. Different modelling frameworks are tested under these scenarios, such as those based on OLS, WLS, several versions of PCR and PLS.
In the end, useful guidelines can be extracted regarding the best methods to use and the added value of obtaining more information regarding the uncertainty affecting the responses. 
The Challenge of Testing Autonomous Vehicles
Authors: Luigi del Re (Johannes Kepler University Linz)
Primary area of focus / application: Reliability
Keywords: Reliability, Transportation
Submitted at 19May2014 08:58 by Kristina Krebs
Accepted
The impressive reliability of modern transportation systems is to a very large extent the effect of the systematic development of testing methods which allow testing a specific “deterministic” test object (the vehicle) in a large number of “stochastic” situations. This is done first at component level on specific test benches, but then by fleet tests.
In the case of autonomous or semiautonomous vehicles, the problem complexity is largely increased by the fact that a control algorithm takes over the place of the driver and the producer becomes responsible – if not legally, at least commercially  not only for the performance of the vehicle but also for the way it is driven. This increases enormously the number of situations to be considered, making standard methods, like fleet testing, unaffordable.
This keynote gives an overview on different approaches being analyzed by different groups to cope with this problem.