ENBIS: European Network for Business and Industrial Statistics

My abstracts

The following abstracts have been accepted for this event:

• A Two-Sided Multivariate p Control Chart
  
  Authors: Paolo Cozzucoli
  Primary area of focus / application:
  

  Submitted at 10-Sep-2007 11:29 by
  Accepted
  
  We assume that the operator is interested in monitoring a multinomial process, that is the items are classified into (k+1) ordered distinct and mutually exclusive categories; specifically, the first category is used to classify the conforming items, while the remaining k categories are used to classify the nonconforming items in k defect grades, with increasing degrees of nonconformity. Usually the process is said to be capable if the proportion of nonconforming items is very small and remains low, or declines, over time. In this case, because we have chosen to classify the nonconforming items into k defect grades, the overall proportion of nonconforming items depends on the k categories, which are not necessary independent, and we are interested in evaluating over time the proportion of nonconforming items in each category as well as the overall (across the k categories) proportion of nonconforming items. To achieve this goal, in this paper we propose i) a normalized index that can be used to evaluate the capability of the process and ii) a two sided Shewhart-type multivariate control chart with probabilistic limits to monitor the overall proportion of nonconforming items. In addition, we suggest a solution to the identification problem when an out control signal takes occurs. The same sample statistic is used to define the normalized index and the multivariate p control chart.
• A practical experience with Corrugation height production process improvement using an SPC
  
  Authors: Erik Mønness, Hedmark University College. Matt Linsley, ISRU University of Newcastle.
  Primary area of focus / application:
  

  Submitted at 10-Sep-2007 12:29 by
  Accepted
  
  A product is corrugated into a zigzag. The corrugated profile height is considered to be a critical to quality factor.
  
  The monitoring regime in place was to record corrugation profile height (always in groups of four) at morning startup, and then after any break or after any maintenance. Thus there is always at least one recording a day but typically two to three but could be more. The plan was called “First article inspection”. Originally the plotting unit in the SPC was “day”, thus the control limits would vary with observation number. Also, the control limits were updated each month.
  
  We first advised using each recording (with four measurements) as plotting unit thus avoiding varying control limits. However, we experienced that 1) With this regime the process appeared to be out of control more often, and 2) The variation (estimated sigma) within day was twice the variation within a group-of-four. We fancied that the monitoring regime may not fully monitor the process; perhaps it was monitoring the effect of the interventions more than the running production.
  
  We therefore advised a one month experiment where recordings where taken each hour in addition to the current regime.
  
  The experiment revealed that the current regime had a much smaller variation than the variation of experimental data.
  
  We concluded that we still lack insight into the variation of the process, this should be further investigated. We recommended taking three daily recordings at stated hours in addition to the current regime. We recommended monitoring monthly variation to search for any significant changes of the process.
  
• A practical guide to design conjoint experiments
  
  Authors: Roselinde Kessels*, Bradley Jones°, Marissa Langford* and Tim Clapp*
  Primary area of focus / application:
  

  Submitted at 10-Sep-2007 12:53 by
  Accepted
  
  * North Carolina State University, College of Textiles, Box 8301, 2401 Research Drive, Raleigh, NC 27695-8301. roselinde_kessels@ncsu.edu; marissa_langford@ncsu.edu; tclapp@ncsu.edu ° SAS Institute Inc., SAS Campus Drive, Cary, NC 27513. bradley.jones@jmp.com
  
  Understanding the Voice of the Customer (VOC) is a critical first step in developing a successful product or service. If a company can precisely predict customer preferences and needs, it has a competitive advantage to launch innovative products or services that lead to an increase in customer base. A popular way to predict people's choices for prospective goods is the use of conjoint experiments. In a conjoint experiment, respondents usually rate a set of goods on a scale. These goods are presented as profiles or alternatives of combinations of different component attributes. The usefulness of the predictions resulting from the analysis of the experimental data depends on the profiles and the number of test persons used. Also, the assignment of the profiles to the subjects plays a key role. To maximize the information gained you need an efficient experimental design. In this talk, we will show how to properly design conjoint surveys for both main-effects and interaction-effects models.
• Standards in control of variability
  
  Authors: Jan M. Myszewski, Leon Kozminski Academy of Entrepreneurship, Warsaw, Poland
  Primary area of focus / application:
  

  Submitted at 10-Sep-2007 13:15 by
  Accepted
  
  The text deals with basic schemes of controlling variability
  
  We show that the main method of controlling variability in man driven systems consists in a use of standards – patterns of systems and processes. Imitation of a pattern is a way to achieve more repeatable course of operation and therefore more repeatable effect thereof.
  
  Scope of standards with regard to their content and domain of application is very wide – some of them are generic, used by broad groups of users and some are personal – used by single persons who are their inventor. Use of some standards may be obligatory (law system) and use of some of them may be optional (science system).
  
  Standards used in organisation reflect a knowledge that belongs to organization. A set of corporate standards includes various know-hows and instructions how to control a variability. Some elements of the knowledge are documented and therefore can be controlled. The rest remains in brains of members of organisation. This knowledge is accessible as long as they are in organisation
  
  Organisation should take care that corporate standards are being continually improved – improvement of standards is a way to improve organisational performance
  
  There are several models of standards systems – like ISO 9000 or EFQM Business Excellence Model. There are also schemes used to improve standards used in organization such complex as Six Sigma or such simple as Problem Solving algorithm. The Shewhart-Deming PDCA Cycle is a general algorithm of monitoring standard’s improvement
  
  There is a natural relation between standards and variability:
  
  standards used in organization represent corporate knowledge how to operate against factors producing variability.
  
  Variability (a differentiation which has causes not known to observer) represents those phenomena in organisational processes that are not controlled and fall beyond the corporate knowledge.
  
• Efficient Conjoint Choice Designs in the Presence of Respondent Heterogeneity
  
  Authors: Jie Yu, Peter Goos, Martina Vandebroek
  Primary area of focus / application:
  

  Submitted at 10-Sep-2007 13:20 by
  Accepted
  
  The authors propose a fast and efficient algorithm for constructing
  $D$-optimal conjoint choice designs for mixed logit models in the
  presence of respondent heterogeneity. With this new algorithm, the
  construction of semi-Bayesian $D$-optimal mixed logit designs with
  large numbers of attributes and attribute levels becomes practically
  feasible. The results from the comparison of eight designs (ranging
  from the simple locally $D$-optimal design for the multinomial logit
  model and the nearly orthogonal design generated by Sawtooth (CBC)
  to the complex semi-Bayesian mixed logit design) across wide ranges
  of parameter values show that the semi-Bayesian mixed logit approach
  outperforms the competing designs not only in terms of estimation
  efficiency but also in terms of prediction accuracy. In particular,
  it was found that semi-Bayesian mixed logit designs constructed with
  large heterogeneity parameters are most robust against the
  misspecification of the values for the mean of the individual-level
  coefficients for making precise estimations
  and predictions.
• Fitting a Model for Predicting Leaks in Pipes for a Water Supplying Company
  
  Authors: Lluís Marco-Almagro (Technical University of Catalonia),Lourdes Rodero (Technical University of Catalonia),Xavier Tort-Martorell (Technical University of Catalonia),Lluís Jordan (Aigües de Barcelona),Jordi Molina (Aigües de Barcelona),Ramon Ariño (Ai
  Primary area of focus / application:
  

  Submitted at 10-Sep-2007 17:09 by
  Accepted
  
  Aigües de Barcelona is a company that supplies water to Barcelona and other
  surrounding districts. The company contacted UPC to get help in a project to identify
  and characterize variables affecting the distribution of leaks in water supply pipes.
  Although the company already had a model for predicting leaks in pipes, they were not
  sure about its validity.
  The first step was reviewing existing historical data using descriptive statistics and basic
  graphics. Information from this step was considered valuable by company technicians.
  The information gathered was used to decide the locations of a nondestructive test to
  know the current condition of the pipes. The remaining life years was deducted from
  this data. The information from this study, together with historical data from the leaks
  database, was used to develop a list of candidate variables for improving the model in
  the company.
  
  A loglinear model was then fitted. The new model was able to better explain the number
  of leaks than the previous one. A substantial collateral benefit of the project was
  revealing how materials and diameters affected the number of leaks in the tubes.
  
  Many important lessons were derived from the project. Among others, the value of
  having an updated and consistent database for actualizing the model, the falling of some
  old myths in the company that weren't based on data, and the validation of some other
  perceptions from technicians.
  
  The presentation will focus not only in the results, but also in the methodology followed
  and in the relationship with technicians and managers in the company.
  
• MEASURING SERVICE QUALITY IN HIGHER EDUCATION SECTOR
  
  Authors: Ana Brochado and Rui Cunha Marques (Technical University of Lisbon, Lisbon, Portugal)
  Primary area of focus / application:
  

  Submitted at 12-Sep-2007 10:05 by Ana Brochado
  Accepted
  
  The purpose of this work is to examine the performance of five alternative measures of service quality in high education sector - SERVQUAL (Service Quality), Weighted SERVQUAL, SERVPERF (Service Preferences), Weighted SERVPERF and HedPERF (Higher Education performance). We aim at determining which instrument had the superior measurement capability. Data were collected by means of a structured questionnaire containing perceptions items enhanced from the SERVPERF and HEdPERF scales and expectation items from the SERVQUAL scale, both modified to fit into the higher education sector.
  The first draft of the questionnaire was subject to a pilot testing through a focus group and an expert evaluation. Data were gathered from a 300 student's sample of a Portuguese university in Lisbon. Scales were compared in terms of unidimensionality, reliability and validity (convergent, discriminant and predictive). Managerial conclusions were also drawn.
  
  Keywords: Service quality scales, higher education, reliability.
• FAULT DETECTION IN FEEDBACK (CLOSED-LOOP) CONTROLLED SYSTEMS
  
  Authors: Murat Caner Testik
  Primary area of focus / application:
  

  Submitted at 16-Sep-2007 16:13 by
  Accepted
  
  Feedback control systems do not remove assignable causes of variation but attempt to compensate variations in the output by adjustments to some controllable process variables. In contrast, statistical process control methods are used with an intention to eliminate assignable causes that are the sources of variation. In the following, characteristics of feedback control systems have been discussed for their integration with statistical process control methods. Optimal controllers, arbitrary controllers and different fault types are considered. Detection of different types of faults by monitoring the deviations from target, control actions, and some other statistics are discussed.
• Automating model selection for predictive modeling using SAS Enterprise Miner
  
  Authors: Stefan Ahrens, SAS Institute
  Primary area of focus / application:
  

  Submitted at 20-Sep-2007 10:07 by
  Accepted
  
  Predictive modeling, as used in the context of analytic customer relationship management or credit scoring requires building stable models that not only fit the training and validation data, but generalize well when presented with new data that were not using during the modeling stage. Statisticians usually employ techniques like cross-validation or jack-knifing to ensure that no over-fitting occurs. However, finding the best model by trial and error is still a time-consuming challenge, as many statistical methods and data mining algorithms require fine-tuning certain parameters.
  
  Using an example from database marketing, this presentation will demonstrate how SAS Enterprise Miner can be used to run various models with differing parameter settings and automatically select the best performing model for the final scoring task. Model selection can be based on statistical criteria such as misclassification, error or profit/loss (if a profit/loss function is supplied). SAS Enterprise Miner offers a convenient graphical user interface that supports the statistician with all necessary tasks during a data mining project, from sampling and initial data exploration via variable transformation and modeling to model assessment and scoring. Thus, using SAS Enterprise Miner can help statisticians save time during the model building process.
  
• Virtual Statistics: Exploiting new web-based tools on the company intranet to improve internal discussion and learning within the user community
  
  Authors: Ewan Polwart (Fujifilm Imaging Colorants Ltd)
  Primary area of focus / application:
  

  Submitted at 21-Sep-2007 15:46 by
  Accepted
  
  Within FFIC we have recently been developing intranet-based tools to
  facilitate and improve discussion and information sharing. Statistics has
  been one of the pioneering areas for the use our new Community Server
  interface. Both blogs and forums have been used to promote discussion,
  learning and dissemination of information. This poster will present a
  background to this approach, detail some examples and share learning from
  the experience.
  
  Specifics: poster presentation