Search results for "Operation"

Manufacturing Strategy: Production Problem Analysis for Assessing Focused Flexibility

2008

The objective of this chapter is to define an operationalization pattern which supports decision makers and managers in determining the level of manufacturing flexibility competences, given the business strategy and the manufacturing structure of the firm. This should drive the production system design and configuration activity. Specifically, this chapter presents an innovative approach to develop a manufacturing strategy, which is based on the idea that information on potential production problems that the manufacturing system could face throughout a given long-term planning horizon should be used as a starting point to determine the level of flexibility that the system should possess.

Flow-Injection Solid Phase Partial Least-Squares Spectrophotometric Simultaneous Determination of Iron, Nickel and Zinc

2002

A PLS-2 multivariate calibration method has been developed for the simultaneous determination of iron, nickel and zinc in ternary mixtures by solid phase spectrophotometry associated with flow injection analysis. Fe(II), Ni(II) and Zn(II) form color complexes with 1-(2-thiazolylazo)-2-naphthol (TAN), immobilized on a C18 bonded silica support, at pH 6.4. The proposed procedure is based on the different reaction/retention ratios of the studied ions on the solid support. Bilinear spectrophotometric data of the analytes, fixed in the solid support, were recorded in the 400-800 nm wavelength range as a function of time and a partial least squares (PLS-2) algorithm was used to predict results of…

Stochastic multicriteria evaluation of district heating systems considering the uncertainties

2018

It is of great importance to choose a suitable district heating (DH) system for a specific DH area from the economics, environment and energy (3E) points of view. This is a multicriteria decision making problem, in which the criteria performance values (PVs) and weighting are characterized by uncertain or imprecise information. In this study, seven candidate DH systems are evaluated from the viewpoints of 3E by the stochastic multicriteria acceptability analysis (SMAA) method. SMAA is able to handle the uncertainties of the criteria PVs and the weighting at the same time. These uncertainties are very common and typical in real-life, but in most cases are not treated judiciously or just negl…

WITHDRAWN: Measurement of beam focus quality in biomedical nuclear microscopy.

2009

This article has been withdrawn at the request of the author(s) and/or editor. The Publisher apologizes for any inconvenience this may cause. The full Elsevier Policy on Article Withdrawal can be found at http://www.elsevier.com/locate/withdrawalpolicy.

Using SMAA-2 method with dependent uncertainties for strategic forest planning

2006

Abstract Uncertainty included in forest variables is normally ignored in forest management planning. When the uncertainty is accounted for, it is typically assumed to be independently distributed for the criteria measurements of different alternatives. In forest management planning, the factors introducing the uncertainty can be classified into three main sources: the errors in the basic forestry data, the uncertainty of the (relative) future prices of timber, and the uncertainty in predicting the forest development. Due to the nature of these error sources, most of the involved uncertainties can be assumed to be positively correlated across the alternative management plans and/or criteria.…

A functional approach to monitor and recognize patterns of daily traffic profiles

2014

Functional Data Analysis (FDA) is a collection of statistical techniques for the analysis of information on curves or functions. This paper presents a new methodology for analyzing the daily traffic flow profiles based on the employment of FDA. A daily traffic profile corresponds to a single datum rather than a large set of traffic counts. This insight provides ideal information for strategic decision-making regarding road expansion, control, and other long-term decisions. Using Functional Principal Component Analysis the data are projected into a low dimensional space: the space of the first functional principal components. Each curve is represented by their vector of scores on this basis.…

MLOG: a strongly typed confluent functional language with logical variables

1994

Poirriez, V., MLOG: a strongly typed confluent functional language with logical variables, Theoretical Computer Science 122 (1994) 201-223. A new programming language called MLOG is introduced. MLOG is a conservative extension of ML with logical variables. To validate our concepts, a compiler named CAML Light FLU0 was implemented. Numerous examples are presented to illustrate the possibilities of MLOG. The pattern matching of ML is kept for X-calculus bindings and an unification primitive is introduced for the logical variables bindings. A suspension mechanism allows cohabitation of pattern-matching and logical variables, Although the evaluation strategy for the application is fixed, the or…

Representation of knowledge using Fuzzy set theory

1989

Fuzzy methods for analysing fuzzy production environment

1998

Abstract Very recently, in production management research literature, the necessity to extend production systems analysis techniques, such as queue theory, Mean Value Analysis (MVA) and discrete simulation, to Fuzzy Production Environments, i.e. to those production situations in which data are vague, has emerged. Fuzzy set theory is a powerful tool to model vagueness and, therefore, fuzzy mathematics can be used to extend classical production system analysis techniques. This paper proposes a methodology based on fuzzy relation algebra to extend classical MVA and discrete event simulation.

A genetic integrated fuzzy classifier

2005

This paper introduces a new classifier, that is based on fuzzy-integration schemes controlled by a genetic optimisation procedure. Two different types of integration are proposed here, and are validated by experiments on real data sets of biological cells. The performance of our classifier is tested against a feed-forward neural network and a Support Vector Machine. Results show the good performance and robustness of the integrated classifier strategies.