The influence of raw material characteristics on the industrial pelletizing process and pellet quality

Industrial pelletizing of sawdust was carried out as a designed experiment in the factors: sawdust moisture content, fractions of fresh pine, stored pine and spruce. The process parameters and response variables were energy consumption, pellet flow rate, pellet bulk density, durability and moisture content. The final data consisted of twelve industrial scale runs. Because of the many response variables, data evaluation was by principal component analysis of a 12 × 9 data matrix. The two principal component model showed a clustering of samples, with a good reproducibility of the center points. It also showed a positive correlation of energy consumption, bulk density and durability all negatively correlated to flow rate and moisture content. The stored pine was more related to high durability and bulk density. The role of the spruce fraction was unclear. The design matrix, augmented with the process parameters was a 12 × 6 matrix. Partial least squares regression showed excellent results for pellet moisture content and bulk density. The model for durability was promising. A 12 × 21 data matrix of fatty- and resin acid concentrations measured by GC–MS showed the differences between fresh and stored pine very clearly. The influence of the spruce fraction was less clear. However, the influence of the fatty- and resin acids on the pelletizing process could not be confirmed, indicating that other differences between fresh and stored pine sawdust have to be investigated. This work shows that it is possible to design the pelletizing process for moderate energy consumption and high pellet quality.     

Logistic Regression Analysis of Customer Satisfaction Data

Variation exists in all processes. Significant work has been done to identify and remove sources of variation in manufacturing processes resulting in large returns for companies. However, business process optimization is an area that has a large potential return for a company. Business processes can be difficult to optimize due to the nature of the output variables associated with them. Business processes tend to have output variables that are binary, nominal or ordinal. Examples of these types of output include whether a particular event occurred, a customer's color preference for a new product and survey questions that assess the extent of the survey respondent's agreement with a particular statement. Output variables that are binary, nominal or ordinal cannot be modeled using ordinary least‐squares regression. Logistic regression is a method used to model data where the output is binary, nominal or ordinal. This article provides a review of logistic regression and demonstrates its use in modeling data from a business process involving customer feedback. Copyright © 2006 John Wiley & Sons, Ltd.     

CO2 emissions in Greece for 1990–2002: A decomposition analysis and comparison of results using the Arithmetic Mean Divisia Index and Logarithmic Mean Divisia Index techniques

This paper deals with the decomposition analysis of energy-related CO₂ emissions in Greece from 1990 to 2002. The Arithmetic Mean Divisia Index (AMDI) and the Logarithmic Mean Divisia Index (LMDI) techniques are applied and changes in CO₂ emissions are decomposed into four factors: income effect, energy intensity effect, fuel share effect and population effect. The period-wise and time series analyses show that the biggest contributor to the rise in CO₂ emissions in Greece is the income effect; on the contrary, the energy intensity effect is mainly responsible for the decrease in CO₂ emissions. A comparison of the results of the two techniques gave an insight in the intricacies of energy decomposition. Finally, conclusions and future areas of research are presented.     

Automating application software generation

Many approaches have been proposed to enhance software productivity and reliability. These approaches typically fall into three categories: the engineering approach, the formal approach and the knowledge-based approach. But the optimal gain in software productivity cannot be obtained if one relies on only one of these approaches. This paper describes the work in knowledge-based software engineering conducted by the authors for the past 10 years. The final goal of the research is to develop a paradigm for software engineering which integrates the three approaches mentioned above. A knowledge-based tool which can support the whole process of software development is provided in this paper.     

Mining for trigger events with survival analysis

This paper discusses a new application of data mining, quantifying the importance of responding to trigger events with reactive contacts. Trigger events happen during a customer’s lifecycle and indicate some change in the relationship with the company. If detected early, the company can respond to the problem and retain the customer; otherwise the customer may switch to another company. It is usually easy to identify many potential trigger events. What is needed is a way of prioritizing which events demand interventions. We conceptualize the trigger event problem and show how survival analysis can be used to quantify the importance of addressing various trigger events. The method is illustrated on four real data sets from different industries and countries.     

An analysis of shielding against DC magnetic fields generated by electric railways. Evaluation of effective permeability of fine structure

This paper describes an effective analysis of magnetic shielding based on homogenization. The analyses become time‐consuming if the problems include the magnetic substances having fine structure. The homogenization of the structure makes it possible to analyze effectively the magnetic fields. The authors introduce a method to estimate the effective permeability of the homogenized substance. This method can be applied to any periodic structure made of magnetic substance. The magnetic shielding effects by the structures against direct‐current (DC) fields generated by electric railways are analyzed by using the present method. As a result, it is found that the overhead way and the protective fence near the railway work as a magnetic shield, whose effects can be improved by appropriate arrangement of those constructions. © 2007 Wiley Periodicals, Inc. Electr Eng Jpn, 160(4): 7–15, 2007; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20310     

Analysis of brushless three-phase synchronous generator without exciter

Recently, a demand for small-capacity generators has been increasing as electric sources in small ships and automobiles or as portable electric sources driven by engines. It is desired that the structure of small-capacity generators be simple and robust, and that the generators be highly reliable, easily maintained and controlled. This paper describes an analysis of the original brushless synchronous generator without exciter. The output voltage can be adjusted in the wide range by controlling the stator dc current. To analyze the characteristics of this generator, the finite element method is applied. It is found that the results of theoretical analysis agree well with the experimental results.     

电子表格EXCEL5.0在选煤线性规划问题中的应用

采用电子表格软件ＥＸＣＥＬ５．０可以方便地解决许多选煤生产中的线性规划问题。本文通过选煤过程线性规划实例介绍ＥＸＣＥＬ５．０在此领域的应用方法。