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Performance Prediction in EDM Process for Al 6061 Alloy Using Response Surface Methodology and Genetic Algorithm
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The Electric Discharge (EDM) method is a novel thermoelectric manufacturing technique in which materials are removed by a controlled spark erosion process between two electrodes immersed in a dielectric medium. Because of the difficulties of EDM, determining the optimum cutting parameters to improve cutting performance is extremely tough. As a result, optimizing operating parameters is a critical processing step, particularly for non-traditional machining process like EDM. Adequate selection of processing parameters for the EDM process does not provide ideal conditions, due to the unpredictable processing time required for a given function. Models of Multiple Regression and Genetic Algorithm are considered as effective methods for determining the optimal processing variables of Electrical Discharge Machining.

The material removal rate (MRR) and tool wear (Tw) were investigated using the process variables of pulse on time (Ton), pulse off time (Toff), and current intensity (Ip). The established empirical models were used to perform Genetic Algorithm (GA) to maximize (MRR) and minimize (Tw). The optimization results were utilized to establish machining conditions, validate empirical models, and obtain optimization outcomes. The optimal result that appears in this work was the pulse on (176.261 μs), pulse off (39.42 μs), and current intensity (23.62 Amp.) to maximize the MRR to (0.78391 g/min) and reduce tool wear to (0.0451 g/min).

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Publication Date
Fri May 16 2025
Journal Name
Asian Journal Of Advanced Research And Reports
Conversion of Vegetable Oils into Glycidyl Ethers: The Key Process Moving Towards Sustainability and Improved Performance in Epoxy Resins
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It is through a review of conversion of vegetable oils into glycidyl ethers focusing on their roles in achieving sustainability and improved epoxy resin performance. It involves functionalization of triglycerides in the form of epoxidation followed by glycidylation and yields bio-based monomers having improved mechanical as well as thermal properties. The review covers the underlying chemistry, production drivers, industrial applications, and future issues, supported by quantitative data and comparative studies. In addition, it integrates recent data on catalyst choice, feedstock flexibility, and environmental performance factors of bio-based resins, indicating their suitability for replacing traditional petroleum-based components.<

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Publication Date
Wed Dec 01 2010
Journal Name
Al-khwarizmi Engineering Journal
Improvement of Surface Roughness Quality for Stainless Steel 420 Plate Using Magnetic Abrasive Finishing Method
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     An experimental study was carried out to improve the surface roughness quality of the stainless steel 420 using magnetic abrasive finishing method (MAF). Four independent operation parameters were studied (working gap, coil current, feed rate, and table stroke), and their effects on the MAF process were introduced. A rotating coil electromagnet was designed and implemented to use with plane surfaces. The magnetic abrasive powder used was formed from 33%Fe and 67% Quartz of (250µm mesh size). The lubricant type SAE 20W was used as a binder for the powder contents. Taguchi method was used for designing the experiments and the optimal values of the selected parameters were found. An empirical equation representing the r

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Publication Date
Sun Jan 01 2017
Journal Name
Pertanika Journal Of Science & Technology
Modified Kohonen network algorithm for selection of the initial centres of Gustafson-Kessel algorithm in credit scoring
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Credit risk assessment has become an important topic in financial risk administration. Fuzzy clustering analysis has been applied in credit scoring. Gustafson-Kessel (GK) algorithm has been utilised to cluster creditworthy customers as against non-creditworthy ones. A good clustering analysis implemented by good Initial Centres of clusters should be selected. To overcome this problem of Gustafson-Kessel (GK) algorithm, we proposed a modified version of Kohonen Network (KN) algorithm to select the initial centres. Utilising similar degree between points to get similarity density, and then by means of maximum density points selecting; the modified Kohonen Network method generate clustering initial centres to get more reasonable clustering res

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Publication Date
Sat Apr 23 2016
Journal Name
Iraqi Journal Of Agricultural Sciences
MEASURRING COW FARMS EFFICIENCY BY USING THE QUALITY RESPONSE
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In despite of the expansion of using the dummy variables as a explanatory variables, but their using as a dependent variables is still limited, and the reason of that may be return to may problems when using dummy variables as a dependent variables. the study aimed to using the quality Response Models to Measuring Efficiency of cows farms by random sample including (19) farm from (Abi gherak district). The study estimating the transcendental logarithmic production function by using stochastic frontier Analysis (SFA) to interpret the relation between the return achieved from the cows farms as a dependent variables and each of labor and capital as an independent variables. the function indicates that increasing in labor by (100%) will

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of The Mechanical Behavior Of Materials
Transient response and performance of prestressed concrete deep T-beams with large web openings under impact loading
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Abstract<p>This study reports testing results of the transient response of T-shape concrete deep beams with large openings due to impact loading. Seven concrete deep beams with openings including two ordinary reinforced, four partially prestressed, and one solid ordinary reinforced as a reference beam were fabricated and tested. The effects of prestressing strand position and the intensity of the impact force were investigated. Two values for the opening’s depth relative to the beam cross-section dimensions were inspected under the effect of an impacting mass repeatedly dropped from different heights. The study revealed that the beam’s transient deflection was increased by about 50% with gre</p> ... Show More
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Publication Date
Sat Oct 01 2011
Journal Name
Journal Of Engineering
AGENT BASED MONITORING FOR INVESTIGATION PROCESS AND MAINTENANCE IMPROVEMENT
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Agent technology has a widespread usage in most of computerized systems. In this paper agent technology has been applied to monitor wear test for an aluminium silicon alloy which is used in automotive parts and gears of light loads. In addition to wear test monitoring، porosity effect on
wear resistance has been investigated. To get a controlled amount of porosity, the specimens have
been made by powder metallurgy process with various pressures (100, 200 and 600) MPa. The aim of
this investigation is a proactive step to avoid the failure occurrence by the porosity.
A dry wear tests have been achieved by subjecting three reciprocated loads (1000, 1500 and 2000)g
for three periods (10, 45 and 90)min. The weight difference a

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Publication Date
Tue Jan 01 2013
Journal Name
Innovative Systems Design And Engineering
Automated Surface Defect Detection using Area Scan Camera
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Publication Date
Sat Aug 04 2012
Journal Name
University Of Thi-qar Journal
Prediction of Ultimate Soil Bearing Capacity for Shallow Strip Foundation on Sandy Soils by Using (ANN) Techniqu
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Bearing capacity of soil is an important factor in designing shallow foundations. It is directly related to foundation dimensions and consequently its performance. The calculations for obtaining the bearing capacity of a soil needs many varying parameters, for example soil type, depth of foundation, unit weight of soil, etc. which makes these calculation very variable–parameter dependent. This paper presents the results of comparison between the theoretical equation stated by Terzaghi and the Artificial Neural Networks (ANN) technique to estimate the ultimate bearing capacity of the strip shallow footing on sandy soils. The results show a very good agreement between the theoretical solution and the ANN technique. Results revealed that us

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
Artificial Neural Network (ANN) for Prediction of Viscosity Reduction of Heavy Crude Oil using Different Organic Solvents
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The increase globally fossil fuel consumption as it represents the main source of energy around the world, and the sources of heavy oil more than light, different techniques were used to reduce the viscosity and increase mobility of heavy crude oil. this study focusing on the experimental tests  and modeling with Back Feed Forward Artificial Neural Network (BFF-ANN) of the dilution technique to reduce a  heavy oil viscosity that was collected from the south- Iraq oil fields using organic solvents, organic diluents with different weight percentage  (5, 10 and  20 wt.% )  of  (n-heptane, toluene, and a mixture of  different ratio

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Publication Date
Tue Aug 01 2017
Journal Name
Journal Of Engineering
Rigid trunk sewer deterioration prediction models using multiple discriminant and neural network models in Baghdad city, Iraq
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The deterioration of buried sewers during their lifetime can be affected by several factors leading to bad performance and can damage the infrastructure similar to other engineering structures. The Hydraulic deterioration of the buried sewers caused by sewer blockages while the structural deterioration caused by sewer collapses due to sewer specifications and the surrounding soil characteristics and the groundwater level. The main objective of this research is to develop deterioration models, which are used to predict changes in sewer condition that can provide assessment tools for determining the serviceability of sewer networks in Baghdad city. Two deterioration models were developed and tested using statistical software SPSS, the

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