Search results for: Hidden Markov chain with a bi-dimensional observed process

Authors: John Kabuba, Antoine Mulaba-Bafubiandi, Kim Battle

Abstract:

This paper presents a critical study about the application of Neural Networks to ion-exchange process. Ionexchange is a complex non-linear process involving many factors influencing the ions uptake mechanisms from the pregnant solution. The following step includes the elution. Published data presents empirical isotherm equations with definite shortcomings resulting in unreliable predictions. Although Neural Network simulation technique encounters a number of disadvantages including its “black box", and a limited ability to explicitly identify possible causal relationships, it has the advantage to implicitly handle complex nonlinear relationships between dependent and independent variables. In the present paper, the Neural Network model based on the back-propagation algorithm Levenberg-Marquardt was developed using a three layer approach with a tangent sigmoid transfer function (tansig) at hidden layer with 11 neurons and linear transfer function (purelin) at out layer. The above mentioned approach has been used to test the effectiveness in simulating ion exchange processes. The modeling results showed that there is an excellent agreement between the experimental data and the predicted values of copper ions removed from aqueous solutions.

Keywords: Copper, ion-exchange process, neural networks, simulation

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Authors: Reyna Singh, David Lokhat, Milan Carsky

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The world crude oil demand is projected to rise to 108.5 million bbl/d by the year 2035. With reserves estimated at 869 billion tonnes worldwide, coal remains an abundant resource. The aim of this work was to produce a high value hydrocarbon liquid product using a Direct Coal Liquefaction (DCL) process at, relatively mild operating conditions. Via hydrogenation, the temperature-staged approach was investigated in a dual reactor lab-scale pilot plant facility. The objectives included maximising thermal dissolution of the coal in the presence of tetralin as the hydrogen donor solvent in the first stage with 2:1 and 3:1 solvent: coal ratios. Subsequently, in the second stage, hydrogen saturation, in particular, hydrodesulphurization (HDS) performance was assessed. Two commercial hydrotreating catalysts were investigated viz. NickelMolybdenum (Ni-Mo) and Cobalt-Molybdenum (Co-Mo). GC-MS results identified 77 compounds and various functional groups present in the first and second stage liquid product. In the first stage 3:1 ratios and liquid product yields catalysed by magnetite were favoured. The second stage product distribution showed an increase in the BTX (Benzene, Toluene, Xylene) quality of the liquid product, branched chain alkanes and a reduction in the sulphur concentration. As an HDS performer and selectivity to the production of long and branched chain alkanes, Ni-Mo had an improved performance over Co-Mo. Co-Mo is selective to a higher concentration of cyclohexane. For 16 days on stream each, Ni-Mo had a higher activity than Co-Mo. The potential to cover the demand for low–sulphur, crude diesel and solvents from the production of high value hydrocarbon liquid in the said process, is thus demonstrated. 

Keywords: Catalyst, coal, liquefaction, temperature-staged.

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Authors: Andrus Pedai, Igor Astrov

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In modern telecommunications industry, demand & supply chain management (DSCM) needs reliable design and versatile tools to control the material flow. The objective for efficient DSCM is reducing inventory, lead times and related costs in order to assure reliable and on-time deliveries from manufacturing units towards customers. In this paper the multi-rate expert system based methodology for developing simulation tools that would enable optimal DSCM for multi region, high volume and high complexity manufacturing environment was proposed.

Keywords: Demand & supply chain management, expert systems, inventory control, multi-rate control, performance metrics.

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Authors: Alaa Al Hawari, Mohammad Khader, Wael El Hasan, Mahmoud Alijla, Ammar Manawi, Abdelbaki Benamour

Abstract:

The production of aluminum alloys and ingots – starting from the processing of alumina to aluminum, and the final cast product – was studied using a Life Cycle Assessment (LCA) approach. The studied aluminum supply chain consisted of a carbon plant, a reduction plant, a casting plant, and a power plant. In the LCA model, the environmental loads of the different plants for the production of 1 ton of aluminum metal were investigated. The impact of the aluminum production was assessed in eight impact categories. The results showed that for all of the impact categories the power plant had the highest impact only in the cases of Human Toxicity Potential (HTP) the reduction plant had the highest impact and in the Marine Aquatic Eco-Toxicity Potential (MAETP) the carbon plant had the highest impact. Furthermore, the impact of the carbon plant and the reduction plant combined was almost the same as the impact of the power plant in the case of the Acidification Potential (AP). The carbon plant had a positive impact on the environment when it come to the Eutrophication Potential (EP) due to the production of clean water in the process. The natural gas based power plant used in the case study had 8.4 times less negative impact on the environment when compared to the heavy fuel based power plant and 10.7 times less negative impact when compared to the hard coal based power plant.

Keywords: Life cycle assessment, aluminum production, Supply chain.

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Authors: Azman, K., Sahar, M.R., Rohani, M.S.

Abstract:

Series of tellurite glass of the system 78TeO2-10PbO- 10Li2O-(2-x)Nd2O3-xEr2O3, where x = 0.5, 1.0, 1.5 and 2.0 was successfully been made. A study of upconversion luminescence of the Nd3+/Er3+ co-doped tellurite glass has been carried out. From Judd-Ofelt analysis, the experimental lifetime, exp. τ of the glass serie are found higher in the visible region as they varies from 65.17ms to 114.63ms, whereas in the near infrared region (NIR) the lifetime are varies from 2.133ms to 2.270ms. Meanwhile, the emission cross section,σ results are found varies from 0.004 x 1020 cm2 to 1.007 x 1020 cm2 with respect to composition. The emission spectra of the glass are found been contributed from Nd3+ and Er3+ ions by which nine significant transition peaks are observed. The upconversion mechanism of the co-doped tellurite glass has been shown in the schematic energy diagrams. In this works, it is found that the excited state-absorption (ESA) is still dominant in the upconversion excitation process as the upconversion excitation mechanism of the Nd3+ excited-state levels is accomplished through a stepwise multiphonon process. An efficient excitation energy transfer (ET) has been observed between Nd3+ as a donor and Er3+ as the acceptor. As a result, respective emission spectra had been observed.

Keywords: Tellurite glass, co-dopant, upconvertionluminescence spectra.

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Authors: G. Kehl, P. Wagner

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A novel simulation method to determine the displacements of machine tools due to thermal factors is presented. The specific characteristic of this method is the employment of original CAD data from the design process chain, which is interpreted by an algorithm in terms of geometry-based allocation of convection and radiation parameters. Furthermore analogous models relating to the thermal behaviour of machine elements are automatically implemented, which were gained by extensive experimental testing with thermography imaging. With this a transient simulation of the thermal field and in series of the displacement of the machine tool is possible simultaneously during the design phase. This method was implemented and is already used industrially in the design of machining centres in order to improve the quality of herewith manufactured workpieces.

Keywords: Accuracy, design process, finite element analysis, machine tools, thermal simulation.

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Authors: Nasibeh Nasiri, Dawood Talebi Khanmiri

Abstract:

Performance of any continuous speech recognition system is highly dependent on performance of the acoustic models. Generally, development of the robust spoken language technology relies on the availability of large amounts of data. Common way to cope with little data for training each state of Markov models is treebased state tying. This tying method applies contextual questions to tie states. Manual procedure for question generation suffers from human errors and is time consuming. Various automatically generated questions are used to construct decision tree. There are three approaches to generate questions to construct HMMs based on decision tree. One approach is based on misrecognized phonemes, another approach basically uses feature table and the other is based on state distributions corresponding to context-independent subword units. In this paper, all these methods of automatic question generation are applied to the decision tree on FARSDAT corpus in Persian language and their results are compared with those of manually generated questions. The results show that automatically generated questions yield much better results and can replace manually generated questions in Persian language.

Keywords: Decision Tree, Markov Models, Speech Recognition, State Tying.

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Authors: A.Qaderi, A. Heydarinasab, M. Ardjmand

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Poly-β-hydroxybutyrate (PHB) is one of the most famous biopolymers that has various applications in production of biodegradable carriers. The most important strategy for enhancing efficiency in production process and reducing the price of PHB, is the accurate expression of kinetic model of products formation and parameters that are effective on it, such as Dry Cell Weight (DCW) and substrate consumption. Considering the high capabilities of artificial neural networks in modeling and simulation of non-linear systems such as biological and chemical industries that mainly are multivariable systems, kinetic modeling of microbial production of PHB that is a complex and non-linear biological process, the three layers perceptron neural network model was used in this study. Artificial neural network educates itself and finds the hidden laws behind the data with mapping based on experimental data, of dry cell weight, substrate concentration as input and PHB concentration as output. For training the network, a series of experimental data for PHB production from Hydrogenophaga Pseudoflava by glucose carbon source was used. After training the network, two other experimental data sets that have not intervened in the network education, including dry cell concentration and substrate concentration were applied as inputs to the network, and PHB concentration was predicted by the network. Comparison of predicted data by network and experimental data, indicated a high precision predicted for both fructose and whey carbon sources. Also in present study for better understanding of the ability of neural network in modeling of biological processes, microbial production kinetic of PHB by Leudeking-Piret experimental equation was modeled. The Observed result indicated an accurate prediction of PHB concentration by artificial neural network higher than Leudeking- Piret model.

Keywords: Kinetic Modeling, Poly-β-Hydroxybutyrate (PHB), Hydrogenophaga Pseudoflava, Artificial Neural Network, Leudeking-Piret

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Authors: Wijittra Srisorn

Abstract:

This research studied about green logistics and the expected benefit that organization gotten when adapted to green logistics also the organization concerned about the important activity in green logistics to apply in implementation from study was found that the benefit of green logistics that organization was gotten by logistics management which was the increased efficiency process of management the product from producer to customer all of reduce production cost, increased value added save energy and prevented environment together From study was found that the organization had green logistics to apply in logistics activities in supply chain since downstream till upstream to prevent environment as follow 1). Purchasing process, trade facilitation enhance such as linking of information technology during business to business (B2B business). 2). Productions process improved by business logistics improvement 3). Warehouse management process such as recycled packaging, moving goods in to warehouse, transportation goods and inside receiving and delivery products plan.

Keywords: Green Logistics, Trade Facilitation, Business Logistics Improvement, Double handling.

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Authors: A. Schirru, A. Irimescu, S. Merola, A. d’Adamo, S. Fontanesi

Abstract:

One of the aspects that are usually neglected during the design phase of an engine is the effect of the spark plug on the flow field inside the combustion chamber. Because of the difficulties in the experimental investigation of the mutual interaction between flow alteration and early flame kernel convection effect inside the engine combustion chamber, CFD-3D simulation is usually exploited in such cases. Experimentally speaking, a particular type of engine has to be used in order to directly observe the flame propagation process. In this study, a double electrode spark plug was fitted into an optically accessible engine and a high-speed camera was used to capture the initial stages of the combustion process. Both the arc and the kernel phases were observed. Then, a morphologic analysis was carried out and the position of the center of mass of the flame, relative to the spark plug position, was calculated. The crossflow orientation was chosen for the spark plug and the kernel growth process was observed for different air-fuel ratios. It was observed that during a normal cycle the flow field between the electrodes tends to transport the arc deforming it. Because of that, the kernel growth phase takes place away from the electrodes and the flame propagates with a preferential direction dictated by the flow field.

Keywords: Combustion, Kernel growth, optically accessible engine, spark-ignition engine, spark plug orientation.

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Authors: Aryanejad Mir Bahador Goli, Zahra Honarmand Shah Zileh

Abstract:

In most study fields, a phenomenon may not be studied directly but it will be examined indirectly by phenomenon model. Making an accurate model of system, there is attained new information from modeled phenomenon without any charge, danger, etc... there have been developed more solutions for describing and analyzing the recent complicated systems but few of them have analyzed the performance in the range of system description. Petri nets are of limited solutions which may make such union. Petri nets are being applied in problems related to modeling and designing the systems. Theory of Petri nets allow a system to model mathematically by a Petri net and analyzing the Petri net can then determine main information of modeled system-s structure and dynamic. This information can be used for assessing the performance of systems and suggesting corrections in the system. In this paper, beside the introduction of Petri nets, a real case study will be studied in order to show the application of generalized stochastic Petri nets in modeling a resource sharing production system and evaluating the efficiency of its machines and robots. The modeling tool used here is SHARP software which calculates specific indicators helping to make decision.

Keywords: Flexible manufacturing system, generalizedstochastic Petri nets, Markov chain, performance evaluation.

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Authors: H. F. A. Abdul Ghani, R. R. Porle

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Speech to text in Malay language is a system that converts Malay speech into text. The Malay language recognition system is still limited, thus, this paper aims to investigate the performance of ten Malay words obtained from the online Malay news. The methodology consists of three stages, which are preprocessing, feature extraction, and speech classification. In preprocessing stage, the speech samples are filtered using pre emphasis. After that, feature extraction method is applied to the samples using Mel Frequency Cepstrum Coefficient (MFCC). Lastly, speech classification is performed using Feedforward Neural Network (FFNN). The accuracy of the classification is further investigated based on the hidden layer size. From experimentation, the classifier with 40 hidden neurons shows the highest classification rate which is 94%.  

Keywords: Feed-Forward Neural Network, FFNN, Malay speech recognition, Mel Frequency Cepstrum Coefficient, MFCC, speech-to-text.

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Authors: Zeyneb Kurt, Oguzhan Yavuz

Abstract:

The feature of HIV genome is in a wide range because of it is highly heterogeneous. Hence, the infection ability of the virus changes related with different chemokine receptors. From this point, R5 and X4 HIV viruses use CCR5 and CXCR5 coreceptors respectively while R5X4 viruses can utilize both coreceptors. Recently, in Bioinformatics, R5X4 viruses have been studied to classify by using the coreceptors of HIV genome. The aim of this study is to develop the optimal Multilayer Perceptron (MLP) for high classification accuracy of HIV sub-type viruses. To accomplish this purpose, the unit number in hidden layer was incremented one by one, from one to a particular number. The statistical data of R5X4, R5 and X4 viruses was preprocessed by the signal processing methods. Accessible residues of these virus sequences were extracted and modeled by Auto-Regressive Model (AR) due to the dimension of residues is large and different from each other. Finally the pre-processed dataset was used to evolve MLP with various number of hidden units to determine R5X4 viruses. Furthermore, ROC analysis was used to figure out the optimal MLP structure.

Keywords: Multilayer Perceptron, Auto-Regressive Model, HIV, ROC Analysis

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Authors: H. El-Madbouly

Abstract:

For future Broad band ISDN, Asynchronous Transfer Mode (ATM) is designed not only to support a wide range of traffic classes with diverse flow characteristics, but also to guarantee the different quality of service QOS requirements. The QOS may be measured in terms of cell loss probability and maximum cell delay. In this paper, ATM networks in which the virtual path (VP) concept is implemented are considered. By applying the Markov Deterministic process method, an efficient algorithm to compute the minimum capacity required to satisfy the QOS requirements when multiple classes of on-off are multiplexed on to a single VP. Using the result, we then proposed a simple algorithm to determine different combinations of VP to achieve the optimum of the total capacity required for satisfying the individual QOS requirements (loss- delay).

Keywords: Bandwidth allocation, Quality of services, ATMNetwork, virtual path.

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Authors: Yun-Ho Ahn, Hyery Kang, Dong-Yeun Koh, Huen Lee

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In this study, we demonstrate the production of natural gas hydrates from permeable marine sediments with simultaneous mechanisms for methane recovery and methane-air or methane-air/carbon dioxide replacement. The simultaneous melting happens until the chemical potentials become equal in both phases as natural gas hydrate depletion continues and self-regulated methane-air replacement occurs over an arbitrary point. We observed certain point between dissociation and replacement mechanisms in the natural gas hydrate reservoir, and we call this boundary as critical methane concentration. By the way, when carbon dioxide was added, the process of chemical exchange of methane by air/carbon dioxide was observed in the natural gas hydrate. The suggested process will operate well for most global natural gas hydrate reservoirs, regardless of the operating conditions or geometrical constraints.

Keywords: Air injection, Carbon dioxide sequestration, Hydrate production, Natural gas hydrate.

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Authors: M. Bounechada, F. Benia, M. Aiouaz, S. Bouharati, N. Djirar, H. Benamrani

Abstract:

The cuticular hydrocarbons of Pamphagus elephas (Orthoptera: Pamphagidae) has been analysed by gas chromatography and by combined gas chromatograph-mass spectrometry. The following hydrocarbon classes have been identified in insect cuticular hydrocarbons are: n-alkanes and methylalkanes comprising Monomethyl-, dimethyl-and trimethylalkanes. Sexual dimorphism is observed in long chain alkanes (C24-C36) present on male and female. The cuticulars hydrocarbons of P.elephas ranged from 24 to 36 carbons and incluted n-alkanes, Dimethylalkanes and Trimethylalkanes. nalkanes represented by (C24-C36,72,7% on male and 79,2% on female), internally branched Monomethylalkanes identified were (C25, C30-C32,C35-C37;11% on male and 9,4% on female), Dimethylalkanes detected are (C31-C32, C36; 2,2% on male and 2,06% on female) and Trimethylalkanes detected are (C32, C36; 3,1% on male and 4, 97 on female). Larvae male and female (stage 7) showed the same quality of n-alkanes observed in adults. However a difference quantity is noted.

Keywords: Cuticular hydrocarbons, Gas chromatography, Mass spectrometry, Pamphagus elephas, , Sexual dimorphism

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Authors: Hacene Benkhoula, Mohamed Badreddine Benabdella, Hamid Bouzeboudja, Abderrahmane Asraoui

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The wind is a random variable difficult to master, for this, we developed a mathematical and statistical methods enable to modeling and forecast wind power. Gaussian Processes (GP) is one of the most widely used families of stochastic processes for modeling dependent data observed over time, or space or time and space. GP is an underlying process formed by unrecognized operator’s uses to solve a problem. The purpose of this paper is to present how to forecast wind power by using the GP. The Gaussian process method for forecasting are presented. To validate the presented approach, a simulation under the MATLAB environment has been given.

Keywords: Forecasting, Gaussian process, modeling, wind power.

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Authors: Vidyasagar Shilapuram, Nesrin Ozalp, Anam Waheed

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Carboneous catalytical methane decomposition is an attractive process because it produces two valuable products: hydrogen and carbon. Furthermore, this reaction does not emit any green house or hazardous gases. In the present study, experiments were conducted in a thermo gravimetric analyzer using Fluka 05120 as carboneous catalyst to analyze its effectiveness in methane decomposition. Various temperatures and methane partial pressures were chosen and carbon mass gain was observed as a function of time. Results are presented in terms of carbon formation rate, hydrogen production and catalytical activity. It is observed that there is linearity in carbon deposition amount by time at lower reaction temperature (780 °C). On the other hand, it is observed that carbon and hydrogen formation rates are increased with increasing temperature. Finally, we observed that the carbon formation rate is highest at 950 °C within the range of temperatures studied.

Keywords: Catalysis, Fluka 05120, Hydrogen production, Methane decomposition

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Authors: Shilan Li, Ivan Arokiam, Peter Jarvis, Wendy Garner, Gazelleh Moradi, Stuart Wakefield

Abstract:

Development of a Robust Supply Chain for Dynamic Operating Environment as we move further into the twenty first century, organisations are under increasing pressure to deliver a high product variation at a reasonable cost without compromise in quality. In a number of cases this will take the form of a customised or high variety low volume manufacturing system that requires prudent management of resources, among a number of functions, to achieve competitive advantage. Purchasing and Supply Chain management is one of such function and due to the substantial interaction with external elements needs to be strategically managed. This requires a number of primary and supporting tools that will enable the appropriate decisions to be made rapidly. This capability is especially vital in a dynamic environment as it provides a pivotal role in increasing the profit margin of the product. The management of this function can be challenging by itself and even more for Small and Medium Enterprises (SMEs) due to the limited resources and expertise available at their disposal. This paper discusses the development of tools and concepts towards effectively managing the purchasing and supply chain function. The developed tools and concepts will provide a cost effective way of managing this function within SMEs. The paper further shows the use of these tools within Contechs, a manufacturer of luxury boat interiors, and the associated benefits achieved as a result of this implementation. Finally a generic framework towards use in such environments is presented.

Keywords: Lean, Supply Chain, High variety Low volume, Small and Medium Enterprises.

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Authors: M. Veeresham

Abstract:

The microstructure and texture evolution of cryo rolled and annealed ductile TaHfNbZrTi refractory high entropy alloy was investigated. To obtain that, the alloy is severely cryo rolled and subsequently annealed for the recrystallization process. The cryo rolled – 90% shows the presence of very fine grains and microstructural heterogeneity. The cryo rolled samples are annealed at a temperature ranging from 800°C to 1400°C, the partial recrystallization is observed at 800°C annealed condition, and at higher annealing temperatures the complete recrystallization process is noticed. The development of ND fiber texture is observed after the annealing.

Keywords: refractory high entropy alloy, cryo-rolling, annealing, microstructure, texture

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Authors: Sara Najiazarpour, Mahsa Najiazarpour

Abstract:

There are many problems in contracting projects and their performance. At each project stage and due to different reasons, these problems affect cost, time, and quality. Hence, in order to increase the efficiency and performance in all levels of the chain and with supply chain management approach, there will be a coordination from the beginning of a project to the end of project (handover of project). Contractor selection is the foremost part of construction projects which in this multi-criteria decision-making, the best contractor is determined by expert judgment, different variables, and their priorities. In this paper for selecting the best contractor, numerous criteria were collected by asking from adept experts and then among them, 16 criteria with highest frequency were considered for questionnaire. This questionnaire was distributed between experts. Cronbach's alpha coefficient was used and then based on Borda function important criteria were selected which was categorized in four main criteria as follows: Environmental factors and physical equipment, past performance and technical expertise, affordability and standards. Then with PROMTHEE method, the criteria were normalized and monitored, finally the best alternative was selected. A case study had been done, and the best contractor was selected based on all criteria and their priorities.

Keywords: Evaluation and selecting contractors, project development, supply chain management, multi-criteria decision-making.

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Authors: M. G. Mattos, J. E. Pécora Jr, T. A. Briso

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Today's challenging business environment, with unpredictable demand and volatility, requires a supply chain strategy that handles uncertainty and risks in the right way. Even though inventory models have been previously explored, this paper seeks to apply these concepts on a practical situation. This study involves the inventory replenishment problem, applying techniques that are mainly based on mathematical assumptions and modeling. The primary goal is to improve the retailer’s supply chain processes taking store differences when setting the various target stock levels. Through inventory review policy, picking piece implementation and minimum exposure definition, we were able not only to promote the inventory reduction as well as improve sales results. The inventory management theory from literature review was then tested on a single case study regarding a particular department in one of the largest Latam retail chains.

Keywords: Inventory, distribution, retail, risk, safety stock, sales, uncertainty.

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Authors: Mohit Tyagi, Pradeep Kumar

Abstract:

The objective of this research work is to identify and analyze the significant corporate social responsibility (CSR) practices with an aim to improve the supply chain performance of automobile industry located at National Capital Region (NCR) of India. To achieve the objective, 6 CSR practices have been considered and analyzed using expert’s preference rating (EPR) approach. The considered CSR practices are namely, Top management and employee awareness about CSR (P₁), Employee involvement in social and environmental problems (P₂), Protection of human rights (P₃), Waste reduction, energy saving and water conservation (P₄), Proper visibility of CSR guidelines (P₅) and Broad perception towards CSR initiatives (P₆). The outcomes of this research may help mangers in decision making processes and framing polices for SCP implementation under CSR context.

Keywords: Supply chain performance, corporate social responsibility, CSR practices, expert’s preference rating approach.

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Authors: E. Giovanis

Abstract:

In this paper we present a Feed-Foward Neural Networks Autoregressive (FFNN-AR) model with genetic algorithms training optimization in order to predict the gross domestic product growth of six countries. Specifically we propose a kind of weighted regression, which can be used for econometric purposes, where the initial inputs are multiplied by the neural networks final optimum weights from input-hidden layer of the training process. The forecasts are compared with those of the ordinary autoregressive model and we conclude that the proposed regression-s forecasting results outperform significant those of autoregressive model. Moreover this technique can be used in Autoregressive-Moving Average models, with and without exogenous inputs, as also the training process with genetics algorithms optimization can be replaced by the error back-propagation algorithm.

Keywords: Autoregressive model, Feed-Forward neuralnetworks, Genetic Algorithms, Gross Domestic Product

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Authors: Yuan-Jye Tseng, Yi-Shiuan Chen

Abstract:

In this paper, a new concept of closed-loop design for a product is presented. The closed-loop design model is developed by integrating forward design and reverse design. Based on this new concept, a closed-loop design model for sustainable manufacturing by integrated evaluation of forward design, reverse design, and green manufacturing using a fuzzy analytic network process is developed. In the design stage of a product, with a given product requirement and objective, there can be different ways to design the detailed components and specifications. Therefore, there can be different design cases to achieve the same product requirement and objective. Subsequently, in the design evaluation stage, it is required to analyze and evaluate the different design cases. The purpose of this research is to develop a model for evaluating the design cases by integrated evaluating the criteria in forward design, reverse design, and green manufacturing. A fuzzy analytic network process method is presented for integrated evaluation of the criteria in the three models. The comparison matrices for evaluating the criteria in the three groups are established. The total relational values among the three groups represent the total relational effects. In applications, a super matrix model is created and the total relational values can be used to evaluate the design cases for decision-making to select the final design case. An example product is demonstrated in this presentation. It shows that the model is useful for integrated evaluation of forward design, reverse design, and green manufacturing to achieve a closed-loop design for sustainable manufacturing objective.

Keywords: Design evaluation, forward design, reverse design, closed-loop design, supply chain management, closed-loop supply chain, fuzzy analytic network process.

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Authors: C. Ardil

Abstract:

Aircraft supplier selection process, which is considered as a fundamental supply chain problem, is a multi-criteria group decision problem that has a significant impact on the performance of the entire supply chain. In practical situations are frequently incomplete and uncertain information, making it difficult for decision-makers to communicate their opinions on candidates with precise and definite values. To solve the aircraft supplier selection problem in an environment of incomplete and uncertain information, proximity measure method is proposed. It uses determinate fuzzy numbers. The weights of each decision maker are equally predetermined and the entropic criteria weights are calculated using each decision maker's decision matrix. Additionally, determinate fuzzy numbers, it is proposed to use the weighted normalized Minkowski distance function and Hausdorff distance function to determine the ranking order patterns of alternatives. A numerical example for aircraft supplier selection is provided to further demonstrate the applicability, effectiveness, validity and rationality of the proposed method.

Keywords: Aircraft supplier selection, multiple criteria decision making, fuzzy sets, determinate fuzzy sets, intuitionistic fuzzy sets, proximity measure method, Minkowski distance function, Hausdorff distance function, PMM, MCDM

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Authors: Pradeep Kumar, Tjoon Tow Teng, Shri Chand, Kailas L. Wasewar

Abstract:

The pulp and paper mill effluent is one of the high polluting effluent amongst the effluents obtained from polluting industries. All the available methods for treatment of pulp and paper mill effluent have certain drawbacks. The coagulation is one of the cheapest process for treatment of various organic effluents. Thus, the removal of chemical oxygen demand (COD) and colour of paper mill effluent is studied using coagulation process. The batch coagulation process was performed using various coagulants like: aluminium chloride, poly aluminium chloride and copper sulphate. The initial pH of the effluent (Coagulation pH) has tremendous effect on COD and colour removal. Poly aluminium chloride (PAC) as coagulant reduced COD to 84 % and 92 % of colour was removed at an optimum pH 5 and coagulant dose of 8 ml l-1. With aluminium chloride at an optimum pH = 4 and coagulant dose of 5 g l-1, 74 % COD and 86 % colour removal were observed. The results using copper sulphate as coagulant (a less commercial coagulant) were encouraging. At an optimum pH 6 and mass loading of 5 g l-1, 76 % COD reduction and 78 % colour reduction were obtained. It was also observed that after addition of coagulant, the pH of the effluent decreases. The decrease in pH was highest for AlCl3, which was followed by PAC and CuSO4. Significant amount of COD reductions was obtained by coagulation process. Since the coagulation process is the first stage for treatment of effluent and some of the coagulant cations usually remain in the treated effluents. Thus, cation like copper may be one of the good catalyst for second stage of treatment process like wet oxidation. The copper has been found to be good oxidation catalyst then iron and aluminum.

Keywords: Aluminium based coagulants, Coagulation, Copper, PAC, Pulp and paper mill effluent, Wastewater treatment

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Authors: Abdelouahab Errida, Bouchra Lotfi, Elalami Semma

Abstract:

In this paper, we try to address the topic of multiple change management by adopting an engineered research methodology, conducted within a Moroccan company during its implementation of several change projects that aim at improving its supply chain management performance. Firstly, we present the key concepts related to our research, namely change management, multiproject management and supply chain management. Then, we try to assess how the change management and multi-project management are applied in this company. Finally, we try to propose an approach that will help managers in dealing with multiple change projects. This approach proposes to integrate change management, project management and multi-project management for managing change projects according to three organizational levels: executive level, project portfolio level and change project level.

Keywords: Change management, multi-project management, project management, change portfolio, supply chain management.

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Authors: W. Koranuntachai, T. Chantrasmi, U. Nontakaew

Abstract:

Medical latex gloves are made from the latex compound in production lines. Latex dipping is considered one of the most important processes that directly affect the final product quality. In a continuous production line, a chain conveyor carries the formers through the process and partially submerges them into an open channel flow in a latex dipping tank. In general, the conveyor speed is determined by the desired production capacity, and the latex-dipping tank can then be designed accordingly. It is important to understand the flow behavior in the dipping tank in order to achieve high quality in the process. In this work, Computational Fluid Dynamics (CFD) was used to simulate the flow past an array of formers in a simplified latex dipping process. The computational results showed both the flow structure and the vortex generation between two formers. The maximum shear stress over the surface of the formers was used as the quality metric of the latex-dipping process when adjusting operation parameters.

Keywords: medical latex gloves, latex dipping, dipping tank, computational fluid dynamics

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Authors: Khaing Win Mar, Thinn Thu Naing

Abstract:

Nowadays, precipitation prediction is required for proper planning and management of water resources. Prediction with neural network models has received increasing interest in various research and application domains. However, it is difficult to determine the best neural network architecture for prediction since it is not immediately obvious how many input or hidden nodes are used in the model. In this paper, neural network model is used as a forecasting tool. The major aim is to evaluate a suitable neural network model for monthly precipitation mapping of Myanmar. Using 3-layerd neural network models, 100 cases are tested by changing the number of input and hidden nodes from 1 to 10 nodes, respectively, and only one outputnode used. The optimum model with the suitable number of nodes is selected in accordance with the minimum forecast error. In measuring network performance using Root Mean Square Error (RMSE), experimental results significantly show that 3 inputs-10 hiddens-1 output architecture model gives the best prediction result for monthly precipitation in Myanmar.

Keywords: Precipitation prediction, monthly precipitation, neural network models, Myanmar.

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