The aim of this research is to investigation the optimization of the machining parameters (spindle speed, feed rate, depth of cut, diameter of cutter and number of flutes of cutter) of surface roughness for free-form surface of composite material (Aluminum 6061 reinforced boron carbide) by using HSS uncoated flat end mill cutters which are rare use of the free-form surface. Side milling (profile) is the method used in this study by CNC vertical milling machine. The purpose of using ANFIS to obtain the better prediction of surface roughness values and decreased of the error prediction value and get optimum machining parameters by using Taguchi method for the best surface roughness at spindle speed 4500 r.p.m, 920mm/rev feed rate, 0.6mm de

Polymer matrix composites are suitable materials for medical applications, such as denture base resin polymethyl methacrylate (PMMA). This includes light weight and high strength. This paper describes the effect of selected weight fractions (1, 2, 3, 4 & 5) % wt of nano(Alumina AL2O3, Zirconia ZrO2, Hydroxyapatite HA and Halloysite nanoClay) reinforcements on the biopolymer matrix (PMMA). Some tribology tests were used to evaluate the prepared system (impact strength, hardness surface, and wear rate) tests. The samples were fabricated by (Hand Lay-Up) with different particle reinforcement percentages. All tests were accomplished at room temperature, and samples were developed according to the ASTM standard. The weight fraction o

This study investigated the structural behavior of a beam–slab member fabricated using a steel C-Purlins beam carrying a profile steel sheet slab covered by a dry board sheet filled with recycled aggregate concrete, called a CBPDS member. This concept was developed to reduce the cost and self-weight of the composite beam–slab system; it replaces the hot-rolled steel I-beam with a steel C-Purlins section, which is easier to fabricate and weighs less. For this purpose, six full-scale CBPDS specimens were tested under four-point static bending. This study investigated the effect of using double C-Purlins beams face-to-face as connected or separated sections and the effect of using concrete material that contains different recycled

Polymer matrix composites are suitable materials for medical applications, such as denture base resin polymethyl methacrylate (PMMA). This includes light weight and high strength. This paper describes the effect of selected weight fractions (1, 2, 3, 4 & 5) % wt of nano(Alumina AL2O3, Zirconia ZrO2, Hydroxyapatite HA and Halloysite nanoClay) reinforcements on the biopolymer matrix (PMMA). Some tribology tests were used to evaluate the prepared system (impact strength, hardness surface, and wear rate) tests. The samples were fabricated by (Hand Lay-Up) with different particle reinforcement percentages. All tests were accomplished at room temperature, and samples were developed according to the ASTM standard. The weight fraction of (4% for AL

This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

Background: To evaluate the ISO depth of cure of bulkfill composites and depth of cure which determined by Vickers microhardness test. Materials and Methods: Bulkfill resin composite specimens (n=150) were prepared of three bulkfill composite materials (TetricEvo Ceram, Quixfil and SDR) and light cured by Flash max p3 for 3, 10, 20 seconds and by wood pecker for 10, 20 seconds respectively, a mold was filled with one of the three bulkfill composites and light cured. The specimens removed from the mold and scraped by plastic spatula and the remaining length (absolute length) was measured which represent the ISO depth of cure. After that the specimens were returned into the mold and a microhardness indentation device applied on the specimen

This paper presents a robust algorithm for the assessment of risk priority for medical equipment based on the calculation of static and dynamic risk factors and Kohnen Self Organization Maps (SOM). Four risk parameters have been calculated for 345 medical devices in two general hospitals in Baghdad. Static risk factor components (equipment function and physical risk) and dynamics risk components (maintenance requirements and risk points) have been calculated. These risk components are used as an input to the unsupervised Kohonen self organization maps. The accuracy of the network was found to be equal to 98% for the proposed system. We conclude that the proposed model gives fast and accurate assessment for risk priority and it works as p