Search results for: Galal H. Senussi

Authors: Galal H. Senussi, Muamar Benisa, Sanja Vasin

Abstract:

In our business field today, one of the most important issues for any enterprises is cost minimization and profit maximization. Second issue is how to develop a strong and capable model that is able to give us desired forecasting of these two issues. Many researches deal with these issues using different methods. In this study, we developed a model for multi-criteria production program optimization, integrated with Artificial Neural Network.

The prediction of the production cost and profit per unit of a product, dealing with two obverse functions at same time can be extremely difficult, especially if there is a great amount of conflict information about production parameters.

Feed-Forward Neural Networks are suitable for generalization, which means that the network will generate a proper output as a result to input it has never seen. Therefore, with small set of examples the network will adjust its weight coefficients so the input will generate a proper output.

This essential characteristic is of the most important abilities enabling this network to be used in variety of problems spreading from engineering to finance etc.

From our results as we will see later, Feed-Forward Neural Networks has a strong ability and capability to map inputs into desired outputs.

Keywords: Project profitability, multi-objective optimization, genetic algorithm, Pareto set, Neural Networks.

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Authors: Galal Elkobrosy, Amr M. Abdelrazek, Bassuny M. Elsouhily, Mohamed E. Khidr

Abstract:

Crank shaft length, connecting rod length, crank angle, engine rpm, cylinder bore, mass of piston and compression ratio are the inputs that can control the performance of the slider crank mechanism and then its efficiency. Several combinations of these seven inputs are used and compared. The throughput engine torque predicted by the simulation is analyzed through two different regression models, with and without interaction terms, developed according to multi-linear regression using LU decomposition to solve system of algebraic equations. These models are validated. A regression model in seven inputs including their interaction terms lowered the polynomial degree from 3^rd degree to 1^st degree and suggested valid predictions and stable explanations.

Keywords: Design of experiments, regression analysis, SI Engine, statistical modeling.

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Authors: Yassir M. Abbas, Mohammad Iqbal Khan, Galal Fares

Abstract:

In the present work, the structural responses of 12 ultra-high-performance concrete (UHPC) beams to four-point loading conditions were experimentally and analytically studied. The inclusion of a fibrous system in the UHPC material increased its compressive and flexural strengths by 31.5% and 237.8%, respectively. Based on the analysis of the load-deflection curves of UHPC beams, it was found that UHPC beams with a low reinforcement ratio are prone to sudden brittle failure. This failure behavior was changed, however, to a ductile one in beams with medium to high ratios. The implication is that improving UHPC beam tensile reinforcement could result in a higher level of safety. More reinforcement bars also enabled the load-deflection behavior to be improved, particularly after yielding.

Keywords: Ultra-high-performance concrete, moment capacity, RC beams, hybrid fiber, ductility.

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Authors: G. H. Senussi

Abstract:

The present work is concerned with the effect of turning process parameters (cutting speed, feed rate, and depth of cut) and distance from the center of work piece as input variables on the chip micro-hardness as response or output. Three experiments were conducted; they were used to investigate the chip micro-hardness behavior at diameter of work piece for 30[mm], 40[mm], and 50[mm]. Response surface methodology (R.S.M) is used to determine and present the cause and effect of the relationship between true mean response and input control variables influencing the response as a two or three dimensional hyper surface. R.S.M has been used for designing a three factor with five level central composite rotatable factors design in order to construct statistical models capable of accurate prediction of responses. The results obtained showed that the application of R.S.M can predict the effect of machining parameters on chip micro-hardness. The five level factorial designs can be employed easily for developing statistical models to predict chip micro-hardness by controllable machining parameters. Results obtained showed that the combined effect of cutting speed at it?s lower level, feed rate and depth of cut at their higher values, and larger work piece diameter can result increasing chi micro-hardness.

Keywords: Machining Parameters, Chip Micro-Hardness, CNCMachining, 304-Austenic Stainless Steel.

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Authors: Sherine Beshara, Khaled S. El-Kilany, Noha M. Galal

Abstract:

Supply chain management has become more challenging with the emerging trend of globalization and sustainability. Lately, research related to perishable products supply chains, in particular agricultural food products, has emerged. This is attributed to the additional complexity of managing this type of supply chains with the recently increased concern of public health, food quality, food safety, demand and price variability, and the limited lifetime of these products. Inventory management for agrifood supply chains is of vital importance due to the product perishability and customers- strive for quality. This paper concentrates on developing a simulation model of a real life case study of a two echelon production-distribution system for agri-food products. The objective is to improve a set of performance measures by developing a simulation model that helps in evaluating and analysing the performance of these supply chains. Simulation results showed that it can help in improving overall system performance.

Keywords: Agri-food supply chains, inventory model, modelling and Simulation, supply chain.

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Authors: Muhammad Nouman Haral, Abdulaziz I. Al-Negheimesh, Galal Fares, Mohammad Iqbal Khan, Abdulrahman M. Alhozaimy

Abstract:

Natural pozzolan (NP) is one of the potential prehistoric alternative binders in the construction industry. It has been investigated as cement replacement in ordinary concrete by several researchers for many purposes. Various supplementary cementitious materials (SCMs) such as fly ash, limestone dust and silica fume are widely used in the production of SCC; however, limited studies to address the effect of NP on the properties of SCC are documented. The current research is composed of different SCC paste and concrete mixtures containing different replacement levels of local NP as an alternative SCM. The effect of volume of paste containing different amounts of local NP related to W/B ratio and cement content on SCC fresh properties was assessed. The variations in the fresh properties of SCC paste and concrete represented by slump flow (flowability) and the flow rate were determined and discussed. The results indicated that the flow properties of SCC paste and concrete mixtures, at their optimized superplasticizer dosages, were affected by the binder content of local NP and the total volume fraction of SCC paste.

Keywords: Binder, fresh properties, natural pozzolan, paste, SCC.

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Authors: Eman M. Wahba, Noha M. Galal, Khaled S. El-Kilany

Abstract:

Spare parts inventory management is one of the major areas of inventory research. Analysis of recent literature showed that an approach integrating spare parts classification, demand forecasting, and stock control policies is essential; however, adapting this integrated approach is limited. This work presents an integrated framework for spare part inventory management and an Excel based application developed for the implementation of the proposed framework. A multi-criteria analysis has been used for spare classification. Forecasting of spare parts- intermittent demand has been incorporated into the application using three different forecasting models; namely, normal distribution, exponential smoothing, and Croston method. The application is also capable of running with different inventory control policies. To illustrate the performance of the proposed framework and the developed application; the framework is applied to different items at a service organization. The results achieved are presented and possible areas for future work are highlighted.

Keywords: Demand forecasting, intermittent demand, inventory management, integrated approach, spare parts, spare part classification

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