Applied Mechanics and Materials Vol. 315

Abstract: The problem of machining titanium is one of ever-increasing magnitude due to its low thermal conductivity and work hardening characteristic of the titanium alloy. The efficient machining of titanium alloy with coated carbides involves a proper selection of process parameters to minimizing the surface roughness and cutting force. In the present work, experimental studies have been carried out to obtain the optimum conditions for machining titanium alloy. The effect of machining parameters such speed, feed and depth of cut on the cutting force, surface roughness were investigated. The significance of these parameters, on cutting force and surface roughness has been established using the analysis of variance. Mathematical models have also been developed for estimating the cutting force and surface roughness on the basis of experimental results.

Abstract: The present paper describes the effect of β solution treatment temperature on the sliding wear properties of near β titanium alloy (Ti-10V-4.5Fe-3Al) was examined under three different temperatures 800, 900 and 1000 °C, varying applied load 3, 6 and 9 kgf at a fixed rotational speed of 500 rpm for 16 minutes duration. The track diameter is varied 40, 80 and 120 mm in order to vary the sliding distance or sliding velocity. The sliding wear beahviour was studied using pin-on-disc apparatus against steel counter surface giving emphasis on the parameters such as weight loss as a function of sliding distance and applied load. It was observed from the results that the % weight loss is increases with increase in sliding distance and the load. It is also observed that the % weight loss increases with decreasing the β solution treatment temperature. Form the ANOVA analysis, it revealed that the β solution treatment temperature is not influencing that much on % weight loss as compared to that of load and sliding distance.

Abstract: Folding endurance is very important in terms of the indication for durability and performance of plastics and papers. The objective of this research is to study the performance of polypropylene hinges with the influence hot air in the fabricated chamber and high humidity condition. The performance of this sample was analysed by using folding endurance tester with hot air chamber, adopting the Design of Experiment L9 (3⁴) Taguchi Method for the selected factors which are temperature, relative humidity, breaking time and motor speed. All of these factors were selected with a constant force. Based on the findings, the best combination of parameters which signify the performance of folding endurance test in humidity environment is 70°C for temperature, 60 N for relative humidity, 2 days of breaking time and 850 rpm for motor speed. As for hot air environment, the best setting is 70°C for temperature, 55 N for relative humidity, 3 days of breaking time and 700 rpm for motor speed. For Signal to Noise ratio, the result showed that the temperature was the most influential factor for humidity effects and hot air environment, whereby the Signal to Noise ratio value obtained for the humidity and hot air environment are 129.5 dBi and 130.5 dBi respectively. The conclusion of this research is the polypropylene hinges have performed better with hot air environment as compared with higher humidity environment condition.

Abstract: Currently, one of the important topics in acoustic science is noise control. It is important to control the noise in order to minimize extraneous noise in rooms, buildings, and our environment. Noise control can be achieved by reducing the intensity of sound to the level that is not harmful to human ear. There are four basic principles employed to reduce noise which is absorption, isolation, vibration isolation, and vibration damping. In fact, the most recognized technique to reduce noise is sound absorption on the materials itself. Sound absorption on material such as wood and porous material have been developed and studied by few researchers. Materials that reduce the sound intensity as the sound wave passes through it by the phenomenon of absorption are called sound absorptive materials. There are lot of methods can be used on determining the sound absorption coefficient of materials. In this paper, a preliminary work has been carried out experimentally to determine the sound absorption coefficient of four types of Malaysian wood. They are Tapang (Koompassia excels), Pulai (Alstonai angustiloba), Selunsor merah (Tristianiopsis beccariana) and Jelutong (Dyera polyphylla). The test was performed using the ASTM E1050-98/ISO 10534-2 (American Society for Testing and Material) standards for the sound absorption coefficient testing. This method is known as impedance tube method (Two-Microphone Method). The absorption coefficient depends on the frequencies. In this study the values of the frequencies used was in the range from 350 Hz to 1000 Hz.

Abstract: This paper presents the development of a new polymer matrix composite (PMC) feedstock material by the injection molding machine. The material consists of iron powder filled in an acrylonitrile butadiene styrene (ABS) and surfactant powder (binder) material. In this study, the effect of powder loading and binder content on the mechanical properties was investigated experimentally. The detailed formulations of compounding ratio by Brabender Mixer and injection molding machine of the sample specimen was used with various combinations of the new PMC material. Based on the result obtained, it was found that, higher powder loading of iron filler affected the hardness, tensile and flexural strength of PMC material. With 32% iron powder loading in ABS composites increase the flexural force, maximum stress and force of PMC material through an injection molding process.

Abstract: Rapid Prototyping (RP) technology has proven its capability to produce complex parts with shorter lead time. This advantage could benefit tremendously in application such as the Investment Casting (IC) process. The focus of the study is the production of sacrificial IC patterns produced using Multijet Modeling (MJM) RP technology. It includes the evaluation of dimensional accuracy and the surface roughness of part with a hollow and quasi hollow inner support patterns. Different internal structure's pattern were developed using CAD software, and the part were fabricated using MJM technique in two different build orientations. Analyses were done using Coordinate Measuring Machine (CMM) and the surface roughness tester. Results show that part built with 90º orientation is better than part built with 0º orientation both in terms of accuracies and roughness. Different internal structure similarly affects the final part quality, though the post processing steps also have their influence, thus making it no clear different among the parts. However, it demonstrated parts with square structure produced the best dimensional accuracy and the part with hatch structure produced the best surface roughness.

Abstract: Chemical vapor deposition (CVD) diamond coatings are being developed to be applied on carbide cutting tools to enhance wear resistance and increase tool life. As a prerequisite, for ensuring adhesion of CVD diamond on tungsten carbide substrate, it is necessary to prepare high surface roughness and to remove the cobalt on tungsten carbide surface during the pretreatment. In this study, a two step acid pretreatment was examined for those purposes. Etching using modified Murakamis reagent was initially performed to roughen the surface. Subsequently, the carbide was immersed in nitric acid to remove cobalt. Concentration of the acid solutions and reaction time were varied. Results showed that the initial step by modified Murakamis reagent etching resulted in a surface roughness of Ry = 6.95 µm, which is a 15% increase from the average initial surface roughness. The second step by nitric acid immersion on modified Murakamis reagent etched carbide samples resulted in carbide surfaces with zero cobalt content, confirming the effectiveness of the pretreatment.

Abstract: The performance of a thermoelectric power generator for powering wireless sensor node has been studied and evaluated. This study covers the results obtained from two configurations of thermoelectric cell with heat source temperatures range from 40 to 230 °C. It was found that the highest output voltage is 9.08 V belong to configuration B with two parallel thermoelectric cells. This configuration was capable to power up sensor node compared to configuration A with the lowest heat source temperature at about 200 °C. To enhance the capability of the configurations, DC boost converter circuit has been developed and tested. By connecting to the DC boost converter, configuration A can power up the wireless sensor node with heat source temperature at about 220 °C while the minimum heat source temperature for configuration B was reduced from 200 to 170 °C. This study identified the optimum operation condition to power up wireless sensor node by thermoelectric power generator for remote application and make conclusion as to how to increase the performance of thermoelectric power generator by introducing DC boost converter.

Abstract: Support Vector Machine (SVM) is a new tool from Artificial Intelligence (AI) field has been successfully applied for a wide variety of problem especially in river stream flow forecasting. In this paper, SVM is proposed for river stream flow forecasting. To assess the effectiveness SVM, we used monthly mean river stream flow record data from Pahang River at Lubok Paku, Pahang. The performance of the SVM model is compared with the statistical Autoregressive Integrated Moving Average (ARIMA) and the result showed that the SVM model performs better than the ARIMA models to forecast river stream flow Pahang River.

Abstract: In manufacturing industries, monitoring and diagnosis of multivariate process out-of-control condition become more challenging. Process monitoring refers to the identification of process status either it is running within a statistically in-control or out-of-control condition, whereas process diagnosis refers to the identification of the source variables of out-of-control process. In order to achieve these requirements, the application of an appropriate statistical process control framework is necessary for rapidly and accurately identifying the signs and source out-of-contol condition with minimum false alarm. In this research, a framework namely, an Integrated Multivariate Exponentially Weighted Moving Average with Artificial Neural Network was investigated in monitoring-diagnosis of multivariate process mean shifts in manufacturing audio video device component. Based on two-stages monitoring-diagnosis technique, the proposed framework has resulted in efficient performance.