Surfaces quality is one of the most specified customer requirements for machine parts. The major indication of surfaces quality on machined parts is surface roughness. The research aim is to study the cutting conditions and their effects on the surface roughness. This paper utilizes regression models to predict surface roughness over the machining time for variety of cutting conditions in turning. In the experimental part for turning, different types of materials (Aluminum alloy, Copper alloy, and Gray cast iron) were considered with different cutting speed ( ) and feed rate ( ). A mathematical Model depending on statistical-mathematical method between surface roughness (Rz ) and cutting condition ( , ) were derived, for the three materials. The matrix of test conditions included cutting speeds of the 16, 30, 45 and 60 m/min, feed rates of 0.17, 0.35 and 0.7 mm/rev while the depth of cut has been kept constant. The effect of cutting parameters on surface roughness is evaluated and the optimum cutting condition for minimizing the surface roughness is determined. Mathematical model has been established between the cutting conditions and surface roughness using regression. The predicted values and measured values are fairly close, which indicates that the developed model can be effectively used to predict the surface roughness in the turning machining. As the results of this work, the mathematical models were used in predicting surface roughness, can be used in CAD-CAM manufacturing systems, this mathematical model helps engineer to reduce the efforts. Mathematical models shows that the decreasing in the feed rate resulted in better surface roughness and increasing cutting speed resulted in better surface roughness. The goal of this work is to identify a relationship between experimental results and theoretical model, and study the proper process values for machining, to increasing the rates for raising the quality (better surface roughness).
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This work presents a novel technique for the detection of oil aging in electrical transformers using a single mode optical fiber sensor based on surface plasmon resonance (SPR). The aging of insulating oil is a critical issue in the maintenance and performance of electrical transformers, as it can lead to reduce insulation properties, increase risk of electrical breakdown, and decrease operational lifespan. Many parameters are calculated in this study in order to examine the efficiency of this sensor like sensitivity (S), signal to noise ratio (SNR), resolution (refractive index unit) and figure of merit (FOM) and the values are for figure of merit is 11.05, the signal to noise ratio is 20.3, the sensitivity is 6.63, and the resolution is 3
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This paper presents an investigation to the effect of the forming speed on healing voids that inhabit at various size in an ingot. The study was performed by using finite element method with bilinear isotropic material option, circular type voids were considered. The closure index was able to predict the minimum press force necessary to consolidate voids and the reduction. The simulation was carried out, on circular cross-section lead specials containing a central void of different size. At a time with a flat die, different ratio of inside to outside radius was taken with different speed to find the best result of void closure.
Folic acid and multivitamin tablets containing Aspergillus flavus Penicillia spp. and Cladosporia spores were prepared at a compression pressure of 148 MN/m2 and stored at 35°C under different relative humidifies (75,85, and 95)% within air tight containers, to study the effect of storage condition on them, as well as ,the estimation of the microbial level of the raw materials intended to be used in the two kinds of tablets . Result showed that some raw materials derived from natural origin were heavily contaminated with microorganism compared to that of synthetic origin ,the results also indicated the effect of relative humidity , types of fungal spore , and the hygroscopic nature of exicpient upon survival. Multivit
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In this study multi objective optimization is utilized to optimize a turning operation to reveal the appropriate level of process features. The goal of this work is to evaluate the optimal combination of cutting parameters like feed, spindle speed, inclination angle and workpiece material to have a best surface quality Taguchi technique L9 mixed orthogonal array, has been adopted to optimize the roughness of surface. Three rods of length around (200 mm) for the three metals are used for this work. Each rod is divided into three parts with 50 mm length. For brass the optimum parametric mix for minimum Ra is A1, B1 and C3, i.e., at tool inclination angle (5), feedrate of 0.01, spindle speed of 120
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Electrocoagulation process was employed for the treatment of river water flows in Iraq. In this study, a batch Electrocoagulation process was used to treat river water taken from Al - Qadisiyah water treatment plant. electrolysis time, voltage and inter-electrode spacing were the most important parameters to study . A statistical model was developed using the RSM model. The optimum condition after studying the parameter effect the process was 1 cm separating, 30 volts . The RSM model shows the ideal condition of removal for both the TSS and turbidity at 1 cm, 20 volts and 55 min.
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Background: to evaluate the effect of different dentifrices on the surface roughness of two composite resins (nanofilled-based and nanoceramic – based composite resins). Materials and methods: Forty specimens (diameter 12 mm and height of 2mm) prepared from different composite resin materials: Z350 (nanofilled composite, and Ceram-X (nanoceramic) .they were subjected to brushing simulation equivalent to the period of 1 year. The groups assessed were a control group brushed with distilled water (G1), Opalescence whitening toothpasteR (G2), Colgate sensitive pro-relief (G3) and Biomed Charcoal Toothpaste (G4). The initial and final roughness of each group was tested by surface roughness tester. The results were statistically analyzed using
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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 determ
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Objective: To enhance bonding strength between thermoplastic denture base and acrylic soft liner through ethyl acetate surface treatment. Materials and Methods: Modifications of thermoplastic acrylic denture base surface were investigated with SEM. FTIR was used to detect whether there was a chemical bond between thermoplastic acrylic and the organic solvent. A total of 80 samples were prepared and divided into 20 samples for the surface roughness test and 60 samples for the shear bond strength test. Failure type was assessed visually. Results: Shear bond strength and surface roughness values of un treated samples were lower in comparison to surface treated groups; the greatest post thermocycling bond strength value was recorded for the sam
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