ENBIS-12 in Ljubljana

9 – 13 September 2012 Abstract submission: 15 January – 10 May 2012

My abstracts


The following abstracts have been accepted for this event:

  • Replicates or Repeats

    Authors: Magnus Arnér (Tetra Pak Packaging Solutions)
    Primary area of focus / application: Design and analysis of experiments
    Keywords: Repeats, Replicates, Design of Experiments, Analysis
    Submitted at 10-May-2012 15:14 by Johan Olsson
    11-Sep-2012 10:40 Replicates or Repeats
    We all know that the best way to perform an experiment is to use replicates and not repeats. But how should we act if it is very easy to get repeats and it takes a lot of time to change the settings to get replicates. What implications does this have on the analysis?
  • Ask the Right Questions, or Apply Involved Statistics? Thoughts on the Analysis of Customer Satisfaction Data

    Authors: Dr. Thomas Hochkirchen (Ford Motor Company), Dr. Martin Blankenagel (divis GmbH)
    Primary area of focus / application: Business
    Keywords: customer survey data, customer satisfaction, Kansei Engineering, multicollinearity, communication and acceptance of statistical results
    Submitted at 10-May-2012 18:11 by Thomas Hochkirchen
    11-Sep-2012 11:50 Ask the Right Questions, or Apply Involved Statistics? Thoughts on the Analysis of Customer Satisfaction Data
    For years, there has been much talk about customer satisfaction – why companies should care, how we should measure and how we should analyse our customers’ satisfaction levels. Statisticians have published many papers on appropriate modelling methods to identify the “real” drivers of satisfaction.

    Our discussion’s focus is on the experience we made in the automotive industry, which has become incredibly competitive and thus spends much effort on understanding the voice of our customers. However, automobiles do not only carry passengers but as well lots of emotions, making separation of emotional and technical aspects of a product a challenging task. Statistically, this becomes visible in a high degree of multicollinearity between potential input variables, which makes “naïve regression modelling” a dangerous game to play.

    While we’ll provide a choice of tools suggested to overcome the technical difficulty of highly correlated inputs, we do as well want to trigger a discussion if we typically start from the right starting point: If we ask the right questions (in customer, not in engineering speak!), the multicollinearity issue will disappear – and with it, the need for unnecessarily complicated analysis methods. This in turn enables easier communication of findings and therefore increased acceptance of statistics as a tool with real business benefit.
  • Implementation of Six Sigma in SMEs. A Case Study in Swedish Industry

    Authors: Anna Errore (University of Palermo), Stefano Barone (University of Palermo), Alberto Lombardo (University of Palermo), Therese Doverholt (Structo Hydraulics AB)
    Primary area of focus / application: Six Sigma
    Keywords: Six Sigma,, Black Belt course, statistical methods, SMEs
    Submitted at 10-May-2012 18:31 by Anna Errore
    12-Sep-2012 09:45 Implementation of Six Sigma in SMEs. A Case Study in Swedish Industry
    Many big companies today have already solid Six Sigma infrastructures. However, all over the world SMEs are only now approaching the methodology.
    In this presentation we expose an industrial application of a Six Sigma Black Belt project. It shows how Six Sigma was introduced and successfully implemented in a Swedish small-medium sized company. The project was carried out within the Six Sigma Black Belt course run at Chalmers University of Technology in Gothenburg. This case study is included in the book “Statistical and Managerial Techniques for Six Sigma Methodology, Theory and Application” (Wiley, 2012).
    The company is Structo Hydraulics AB, a manufacturing firm, located in Storfors, which produces steel tubes, mainly for the hydraulic industry. The project focused on the improvement of the warehouse activities, specifically the cutting processes. A high yield is always desirable in an industrial process, maximizing the utilization of materials and reducing costs. This was the project main objective.
    The argumentations follow the DMAIC framework. The main finding was that the planning for cutting processes was mostly based on operators’ knowledge and it was not structured in the optimum way. Four main improvement recommendations were given concerning: maintenance, calibration, tolerance analysis, tools for short and long term planning.
    The case ends with the implementation of the recommendations and a control plan designed for the future activities.
    General considerations concerning the implementation of Six Sigma in SMEs will be also provided.
  • ENBIS Conference Participants Satisfaction Survey

    Authors: Irena Ograjenšek (University of Ljubljana, Faculty of Economics)
    Primary area of focus / application: Business
    Keywords: customer satisfaction, ENBIS, measurement, survey research
    Submitted at 10-May-2012 22:42 by Irena Ograjenšek
    11-Sep-2012 12:10 ENBIS Conference Participants Satisfaction Survey
    Like any other professional association ENBIS strives to determine satisfaction of those attending its annual conferences. In this paper we (1) critically evaluate the evolution of the measurement instrument used in ENBIS Conference Participants Satisfaction Surveys to date and (2) present the most interesting findings from some of the most recent surveys.
  • Distribution-free Prediction Intervals

    Authors: Rainer Göb (University of Wuerzburg), Kristina Lurz (University of Wuerzburg)
    Primary area of focus / application: Modelling
    Keywords: quantile, confidence interval, prediction interval, Cornish-Fisher expansion, inequality
    Submitted at 11-May-2012 01:06 by Rainer Göb
    10-Sep-2012 11:00 Distribution-free Prediction Intervals
    Prediction intervals are used in many industrial contexts, e. g., in reliability analysis, risk management, finance, or trading. Distribution-based prediction intervals have been studied for many distributions. In particular in the case of small sample sizes, the choice of a specific distribution can be fallacious. Relying on distribution-free prediction intervals helps to avoid model error. We study and compare approaches to distribution free prediction intervals, particularly based on the Cornish-Fisher expansion and on inequalities of probability theory. The methods are illustrated on data from finance, currency trade, and commodity trade.
  • A Bayesian Approach to the Analysis of Split-Plot Combined and Product Arrays and Optimization in Robust Parameter Design

    Authors: Tim Robinson (University of Wyoming)
    Primary area of focus / application: Design and analysis of experiments
    Keywords: split-plot design, robust parameter design, Bayesian statistics
    Submitted at 27-May-2012 23:14 by Tim Robinson
    10-Sep-2012 12:20 A Bayesian Approach to the Analysis of Split-Plot Combined and Product Arrays and Optimization in Robust Parameter Design
    Many robust parameter design (RPD) studies involve a split-plot randomization structure and to obtain valid inferences in the analysis, it is essential to account for the induced correlation structure. Bayesian methods are appealing for these studies since they naturally accommodate a general class of models, can account for parameter uncertainty in process optimization, and offer the necessary flexibility when one is interested in non-standard performance criteria, e.g., the probability that a new response exceeds some value. In this talk, a Bayesian approach to process optimization is presented for a general class of RPD models in the split-plot context using an empirical approximation to the posterior distribution of an objective function of interest. Two examples from the literature are used for illustration.