A rolling horizon simulation approach for managing demand with lead time variability

This paper proposes a rolling horizon (RH) approach to deal with management problems under dynamic demand in planning horizons with variable lead times using system dynamics (SD) simulation. Thus, the nature of dynamic RH solutions entails no inconveniences to contemplate planning horizons with unpredictable demands. This is mainly because information is periodically updated and replanning is done in time. Therefore, inventory and logistic costs may be lower. For the first time, an RH is applied for demand management with variable lead times along with SD simulation models, which allowed the use of lot-sizing techniques to be evaluated (Wagner-Whitin and Silver-Meal). The basic scenario is based on a real-world example from an automotive single-level SC composed of a first-tier supplier and a car assembler that contemplates uncertain demands while planning the RH and 216 subscenarios by modifying constant and variable lead times, holding costs and order costs, combined with lot-sizing techniques. Twenty-eight more replications comprising 504 new subscenarios with variable lead times are generated to represent a relative variation coefficient of the initial demand. We conclude that our RH simulation approach, along with lot-sizing techniques, can generate more sustainable planning results in total costs, fill rates and bullwhip effect terms.     

Inverse material identification in coupled acoustic-structure interaction using a modified error in constitutive equation functional

This work focuses on the identification of heterogeneous linear elastic moduli in the context of frequency-domain, coupled acoustic-structure interaction (ASI), using either solid displacement or fluid pressure measurement data. The approach postulates the inverse problem as an optimization problem where the solution is obtained by minimizing a modified error in constitutive equation (MECE) functional. The latter measures the discrepancy in the constitutive equations that connect kinematically admissible strains and dynamically admissible stresses, while incorporating the measurement data as additional quadratic error terms. We demonstrate two strategies for selecting the MECE weighting coefficient to produce regularized solutions to the ill-posed identification problem: 1) the discrepancy principle of Morozov, and 2) an error-balance approach that selects the weight parameter as the minimizer of another functional involving the ECE and the data misfit. Numerical results demonstrate that the proposed methodology can successfully recover elastic parameters in 2D and 3D ASI systems from response measurements taken in either the solid or fluid subdomains. Furthermore, both regularization strategies are shown to produce accurate reconstructions when the measurement data is polluted with noise. The discrepancy principle is shown to produce nearly optimal solutions, while the error-balance approach, although not optimal, remains effective and does not need a priori information on the noise level.     

Synthesis and electrochemical properties of polyaniline nanofibers by interfacial polymerization

Polyaniline nanofibers were prepared by interfacial polymerization with different organic solvents such as chloroform and carbon tetrachloride. Field emission scanning electron microscopy and transmission electron microscopy were used to study the morphological properties of polyaniline nanofibers. Chemical characterization was carried out using Fourier transform infrared spectroscopy, UV-Vis spectroscopy, and X-ray diffraction spectroscopy and surface area was measured using BET isotherm. Polyaniline nanofibers doped with lithium hexafluorophosphate were prepared and their electrochemical properties were evaluated.     

Data‐driven bounded‐error fault detection

In this paper, a new data‐driven fault‐detection method is proposed. This method is based on a new nonparametric system identification approach, which constitutes the principal contribution to this work. The fault‐detection method is a parametric model‐free approach that can be applied to nonlinear systems that work at various operating points. Not only can the fault‐detection process be applied to the steady state of each operating point, but it can also be applied to the transient state resulting from a change in the operating point. In order to detect faults, the proposed method uses an interval predictor based on bounded‐error techniques. The utilization of techniques based on bounded error enables system uncertainties to be included in an explicit way. This in turn leads to the possibility of obtaining interval predictions of the behaviour of the system, which include information on the reliability of the prediction itself. In order to show the effectiveness of the fault‐detection method, two examples are presented: in the form of a simulated process (counter‐flow shell‐and‐tube heat‐exchanger system) and an example of a real application (two‐tanks system). A comparison with two fault‐detection methods has also been included. Copyright © 2013 John Wiley & Sons, Ltd.     

Infostations for highway cigar-shaped cells

An infostation is an isolated pocket area, with small coverage of high bandwidth connectivity, which collects information requests of mobile users and delivers data while users are going through the coverage area. In this paper, the performance of infostations networks with single, double and triple frequencies is studied. The two-slope propagation loss model is used to calculate the signal-to-interference plus noise ratio. The effect of the propagation parameters on the infostation performance is studied.     

Medical knowledge management for specific hospital departments

Medical knowledge representation and management is concerned with how to organise the often vague clinical experience of medical staff required for computable models. However, few knowledge management and acquisition tools have entered routine use, since such tools are not perceived by physicians as part of the clinical information process. An attempt to partially solve this problem, we identify two key aspects of knowledge representation and management tasks. The first is to adopt a medical knowledge standardisation to provide a consistent terminology control and to simplify the integration between knowledge management tools and the health information system. The second is to establish an effective knowledge acquisition process in specific medical fields by adapting knowledge acquisition tools. Therefore, the main goal of this work is to define computational models and to design mechanisms for the effective acquisition and management of medical knowledge in real-life hospital departments. To this end, we analyse the representation of medical knowledge (based on deep-causal models) and the development of knowledge management tools (based on ontologies), integrated within the information processing activities of the clinical user. Finally, we illustrate its applicability in the Intensive Care Unit and Pediatry scenarios.     

Burial grounds’ impact on groundwater and public health: an overview

The most common practice for disposal of dead bodies is inhumation in soil, which favours interactions with the surrounding environment and returns nutrients to the life cycle. However, when the burial ground is located where hydrogeological, geological and climatic conditions are not favourable to the process, contamination of soils and groundwater may occur, and decomposition may be inhibited, leading to social, economic and political problems. The most critical parameters when assessing the pollution potential of a burial ground are inhumation depth, geological formation, depth of the water table, density of inhumations, soil type and climate. Considering that, this paper presents an overview of the potential threat that cemeteries can pose, analysing and discussing the influence of the main variables causing environmental impacts and public health risks.     

Numerical model of a planar jet wiping system for continuous strip lines

Journal of Mechanical Science and Technology - The present study focuses on the numerical modelling of gas-jet wiping process. Many processes involving liquids are necessary during steel...     

The nature of choice in mass customized house building

There is a need to explore the actual uptake of specification options by clients in the context of the self-build housing industry. In so doing all the components in a house that can be customized were categorized so as to highlight the features that must be customizable and those that can be standardized. Through a longitudinal study of a German house builder, data from 16 projects over a 35-year time horizon have been collected. The extent of choice made in these projects has been determined by comparing the original standard building specification with the actual finalized fit-out specification of the project. In scrutinizing the collected data it became apparent that the number of changes made by the clients increased considerably over the timespan studied. More importantly, clients appreciated the freedom of choice as they were prepared to spend increasing amounts on customization. In particular specification options were made in the sanitary, internal design and façade categories. Moreover the results revealed that offering a high degree of choice is appropriate for most, but not all, components for the case house builder. Key areas for choice include those relating to sanitary ware and the façade.