A simulation study of despatch bay performance in the steel processing industry

2007 ◽  
Vol 179 (2) ◽  
pp. 567-578 ◽  
Author(s):  
Andrew Potter ◽  
Biao Yang ◽  
Chandra Lalwani
Keyword(s):  
Simulation Study ◽  
Processing Industry ◽  
Steel Processing

scholarly journals Consistent Identification and Traceability of Objects as an Enabler for Automation in the Steel Processing Industry

2020 ◽  
pp. 163-192
Author(s):  
Helmut Zsifkovits ◽  
Johannes Kapeller ◽  
Hermann Reiter ◽  
Christian Weichbold ◽  
Manuel Woschank
Keyword(s):  
Processing Industry ◽  
Steel Processing

PROCESS OPTIMIZATION IN CONTINUOUS CORRUGATION LINE AT STEEL PROCESSING INDUSTRY

2018 ◽  
Vol 10 (7) ◽  
Author(s):  
Rohit B. Ganorkar ◽  
K.N. Agrawal
Keyword(s):  
Process Optimization ◽  
Processing Industry ◽  
Steel Processing

Performance management within the Dutch steel processing industry

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ralf Jan Benjamin Van der Meij ◽  
David John Edwards ◽  
Chris Roberts ◽  
Hatem El-Gohary ◽  
John Posillico
Keyword(s):  
Performance Management ◽  
Inductive Reasoning ◽  
Chief Executive ◽  
Past Research ◽  
Research Problem ◽  
Mitigation Strategies ◽  
Processing Industry ◽  
Content Type ◽  
Extant Literature ◽  
Steel Processing

Purpose A comprehensive literature review of performance management within the Dutch steel processing industry is presented. The purpose of this paper is to analyse the motives for companies to become excellent performers in their field of expertise. These internal and external motives (refined by quantitative analysis of bibliographic data) sought to reveal the common factors that impact company performance. Design/methodology/approach Inductive reasoning was adopted using an interpretivist philosophical stance to generate new theoretical insight. A mixed-methods analysis of pertinent extant literature afforded greater synthesis of the research problem domain and generated more valid and reliable findings. The software visualisation of similarities viewer was used to conduct a qualitative bibliographic analysis of extant literature to yield greater clarification on the phenomena under investigation. Findings Four thematic groups of past research endeavours emerged from the analysis and were assigned appropriate nomenclature, namely: industry internal motives; industry external motives; excellent performer and incremental working method. To further expand upon the continuous improvement process (CIP – embodied within performance management), the paper describes the virtuous cycle of improvement, which consists of the consecutive steps of “planning”, “doing”, “checking” and ultimately of “acting” accordingly to the previous steps. It can be concluded that a high-performing company acts according to its mission, plans in line with the vision do as defined in the strategy and checks by reflection. Originality/value This unique study provides invaluable insight into the performance management of Dutch steel processing companies. Although the research context was narrowly defined, the findings presented are equally applicable to clients, contractors and sub-contractors active in other sectors of the construction industry. The research concludes by prescribing factors of mitigation strategies to support chief executive officers to focus on the optimum distribution of their scarce resources.

A Monte Carlo simulation study of associated liquid crystals

1999 ◽  
Vol 97 (11) ◽  
pp. 1173-1184 ◽  
Author(s):  
R. Berardi, M. Fehervari, C. Zannoni
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Liquid Crystals ◽  
Simulation Study ◽  
Monte Carlo Simulation Study

An Alternative to Cohen's κ

2006 ◽  
Vol 11 (1) ◽  
pp. 12-24 ◽  
Author(s):  
Alexander von Eye
Keyword(s):  
Simulation Study ◽  
Null Hypothesis ◽  
Categorical Variables ◽  
Alternative Measure ◽  
Rater Agreement ◽  
Verbal Processing ◽  
Heavy Tailed ◽  
Applicant Selection

At the level of manifest categorical variables, a large number of coefficients and models for the examination of rater agreement has been proposed and used. The most popular of these is Cohen's κ. In this article, a new coefficient, κ s , is proposed as an alternative measure of rater agreement. Both κ and κ s allow researchers to determine whether agreement in groups of two or more raters is significantly beyond chance. Stouffer's z is used to test the null hypothesis that κ s = 0. The coefficient κ s allows one, in addition to evaluating rater agreement in a fashion parallel to κ, to (1) examine subsets of cells in agreement tables, (2) examine cells that indicate disagreement, (3) consider alternative chance models, (4) take covariates into account, and (5) compare independent samples. Results from a simulation study are reported, which suggest that (a) the four measures of rater agreement, Cohen's κ, Brennan and Prediger's κ n , raw agreement, and κ s are sensitive to the same data characteristics when evaluating rater agreement and (b) both the z-statistic for Cohen's κ and Stouffer's z for κ s are unimodally and symmetrically distributed, but slightly heavy-tailed. Examples use data from verbal processing and applicant selection.

Comparison of Principal Component Solutions in Two Populations

Methodology ◽  
2016 ◽  
Vol 12 (1) ◽  
pp. 11-20 ◽  
Author(s):  
Gregor Sočan
Keyword(s):  
Simulation Study ◽  
Principal Components ◽  
Common Factor ◽  
Principal Component ◽  
Component Model ◽  
Bootstrap Procedure ◽  
Factor Loadings ◽  
Component Loadings ◽  
Principal Component Model ◽  
Two Populations

Abstract. When principal component solutions are compared across two groups, a question arises whether the extracted components have the same interpretation in both populations. The problem can be approached by testing null hypotheses stating that the congruence coefficients between pairs of vectors of component loadings are equal to 1. Chan, Leung, Chan, Ho, and Yung (1999) proposed a bootstrap procedure for testing the hypothesis of perfect congruence between vectors of common factor loadings. We demonstrate that the procedure by Chan et al. is both theoretically and empirically inadequate for the application on principal components. We propose a modification of their procedure, which constructs the resampling space according to the characteristics of the principal component model. The results of a simulation study show satisfactory empirical properties of the modified procedure.

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