Mechanical Engineering

This study presents a new method to determine multi-objective optimal cutting conditions and mathematic models for surface roughness (Ra and Rz) on a CNC turning. Firstly, cutting parameters namely, cutting speed, depth of cut, and feed rate are designed using the Taguchi method. The AISI 304 austenitic stainless workpiece is machined by a coated carbide insert under dry conditions. The influence of cutting speed, feed rate and depth of cut on the surface roughness is examined. Secondly, the model for the surface roughness, as a function of cutting parameters, is obtained using the response surface methodology (RSM). Finally, the adequacy of the developed mathematical model is proved by ANOVA. The results indicate that the feed rate is the dominant factor affecting surface roughness, which is minimized when the feed rate and depth of cut are set to the lowest level, while the cutting speed is set to the highest level. The percentages of error all fall within 1%, between the predicte...

In this study, the average surface roughness values obtained when turning AISI 4140 grade tempered steel with a hardness of 51 HRC, were modeled using fuzzy logic, artificial neural networks (ANN) and multi-regression equations. Input variables consisted of cutting speed (V), feed ...

This article proposes for predicting the surface roughness of AISI 1040 steel material using the artificial intelligent. Cutting speed, feed rate, depth of cut, and nose radius have been taken into consideration as input factors and corresponding surface roughness values (R a , R t) as output. A series of experiments have been carried out in accordance with a full factorial design on the CNC lathe to obtain the data used for the training and testing of an artificial neural network (ANN). The developed MATLAB TM interface was used to predict surface roughness. Multilayer perceptron structure, which is a kind of feed forward ANNs, is applied to model and prediction of the surface roughness in turning operations. The number of iterations used was 20,000. MSE = 1E-4 and R 2 = 0.9991 were achieved using the developed ANN Model. The obtained results indicate that the ANN algorithm coupled with back propagation neural network is an efficient and accurate method in predicting of surface roughness in turning.

We applied combined response surface methodology (RSM) and Taguchi methodology (TM) to determine optimum parameters for minimum surface roughness () Ra and vibration () Vb in external cylindrical grinding. First, an experiment was conducted in a CNC cylindrical grinding machine. The TM using 27 L orthogonal array was applied to the design of the experiment. The three input parameters were workpiece revolution, feed rate and depth of cut; the outputs were vibrations and surface roughness. Second, to minimize wheel vibration and surface roughness, two optimized models were developed using computer-aided single-objective optimization. The experimental and statistical results revealed that the most significant grinding parameter for surface roughness and vibration is workpiece revolution followed by the depth of cut. The predicted values and measured values were fairly close, which indicates 2

This study presents a new method to determine multi-objective optimal cutting conditions and mathematic models for surface roughness (Ra and Rz) on a CNC turning. Firstly, cutting parameters namely, cutting speed, depth of cut, and feed rate are designed using the Taguchi method. The AISI 304 austenitic stainless workpiece is machined by a coated carbide insert under dry conditions. The influence of cutting speed, feed rate and depth of cut on the surface roughness is examined. Secondly, the model for the surface roughness, as a function of cutting parameters, is obtained using the response surface methodology (RSM). Finally, the adequacy of the developed mathematical model is proved by ANOVA. The results indicate that the feed rate is the dominant factor affecting surface roughness, which is minimized when the feed rate and depth of cut are set to the lowest level, while the cutting speed is set to the highest level. The percentages of error all fall within 1%, between the predicted values and the experimental values. This reveals that the prediction system established in this study produces satisfactory results, which are improved performance over other models in the literature. The enhanced method can be readily applied to different metal cutting processes with greater confidence.

In this work, a technique is proposed to predict surface roughness by using neural network. Surface roughness could be predicted within a reasonable degree of accuracy by taking feed rate, cutting speed, depth of cut and three orthogonal axis (x,y,z) signals of vibrations of tool holder as input parameters. 27 experiments were performed by using a CNC lathe with a carbide cutting tool. Experimental data obtained from turning process were used for training and testing of neural network architecture based prediction system. When experimental and prediction results were compared, it has been seen that a mean accuracy of 91,17% was achieved.

In bandsaw machines, it is desired to feed the bandsaw blade into the workpiece with an appropriate feeding force in order to perform an efficient cutting operation. This can be accomplished by controlling the feed rate and thrust force by accurately detecting the cutting resistance against the bandsaw blade during cutting operation. In this study, a neural-fuzzybased force model for controlling band sawing process was established. Cutting parameters were continuously updated by a secondary neural network, to compensate the effect of environmental disturbances. Required feed rate and cutting speed were adjusted by developed fuzzy logic controller. Results of cutting experiments using several steel specimens show that the developed neural-fuzzy system performs well in real time in controlling cutting speed and feed rate during band sawing. A material identification system was developed by using the measured cutting forces. Materials were identified at the beginning of the cutting operation and cutting force model was updated by using the detected material type. Consequently, cutting speed and feed rate were adjusted by using the updated model. The new methodology is found to be easily integrable to existing production systems.

In this paper response surface methodology (RSM) was used to study the transesterification reaction of safflower for biodiesel production. Biodiesel is alternative fuel, with catalyst and alcohols reaction production, from vegetable oils, animal oils and waste fried oils. But there are fuel problems to be solved before biodiesel. These are storage time, storage conditions and cloudy and flow points which have flow peculiarity in the low heats. In this research, physical and chemical properties as a fuel of Safflower Methyl Ester (SME) which are biodiesel fuels are determined. In this research, method of transesterification is employed. Attitudes in storage time and storage conditions of SME are investigated. As a result, SME viscosity figures, according to measured dates, are below 40 Redwood min. at 40°C. Also the effects of outer temperature and fuel temperature on viscosity were found significant (P<0.01) by the performed variance analysis.

In this study, Multiwall Carbon Nanotubes (MWCNT) reinforced High Density Polyethylene (HDPE) materials were used. Mechanical properties of the samples reinforced with Carbon Nanotubes at weight ratios of 1%, 3% and 5% were investigated. Reinforced samples were compared to samples produced with pure High density Polyethylene. Samples were produced by plastic injection method. The samples were then subjected to experiments and impact resistance values were measured in accordance with ASTM D6110 standards. Also Thermogravimetric Analyses (TGA) was performed for and Multi-Wall Carbon Nanotubes within the High Density Polyethylene. At the end of the study, it was observed that impact resistance decreased with increasing carbon nanotube reinforcement amount. Impact resistance of samples produced by means of plastic injection was decreased by 35% comparing with samples produced from pure HDPE. These results were explained with the fact that structures of composite materials were transformed to a tougher and fragile phase. In the TGA investigations, it was seen that mass loss breakdown temperature and melting point temperature increased by MCWNT ratio in the composite samples.

Статья посвящена анализу резолюции № 239, предложенной сенатором Ванденбергом и обеспечившей Соединѐнным Штатам возможность участия в региональных организациях безопасности за пределами американских континентов вопреки "Прощальной речи" Джорджа Вашингтона и "доктрине Монро". В статье отмечается, что авторитет Артура Ванденберга, сенатора от Республиканской партии, во многом сыграл решающую роль в принятии решения Сенатом США. Делается вывод о том, что без резолюции Ванденберга у Гарри Трумэна и его администрации было бы значительно больше сложностей в вопросе ратификации Сенатом Договора о создании НАТО.

The common exercise in investigations and industrial applications for tires and specifically tractor tires is experimenting. However, there are difficulties which will be detailed in the text. Similar issues are encountered in fluid mechanics, but fluid mechanics studies sometimes involve scaled models and uses similarity approaches to overcome some of the difficulties. However only one significant study has been encountered in the literature about tire scaling and no study is encountered about tractor tires. In this report, scaling, similarity and dimensionless analyses are introduced first. Then the work about tire scaling is viewed. Points for scaling tractor tires are proposed. Some concluding remarks and propositions are made for future work.

Bu çalışmanın amacı, karbon nano tüp (CNT) takviyeli plastik boruların deniz suyu içerisinde kullanılabilirliği ve bunun sonucunda mekanik özelliklerdeki değişimi incelemektir. Deneylerde kullanılan cam/epoksi borular, [±55]3 fiber oryantasyonuna sahip olup; filaman sarım metoduyla üretilmiştir. İkincil takviye malzemesi olarak ağırlıkça %1 oranında CNT kullanılmıştır. Deney numuneleri, kuru ortamın yanı sıra 2,3,4,6 ve 9 aylık reel sürelerle deniz suyu içerisinde bekletildikten sonra çekme ve sertlik testlerine tabi tutulmuşlardır. Testler, ASTM D 2290 standardına göre split disk metoduna uygun halka numuneler üzerinde gerçekleştirilmiştir. Sonuçlar, referans malzemesi cam takviyeli plastikten (CTP) elde edilen sonuçlar ile kıyaslama yapılmıştır. Elde edilen sonuçlara göre CNT'lerin kompozit yapı içerisine girmiş halde üretilmesinin delaminasyon hasarını azalttığı ve bunun sonucunda da kuru ortam şartlarında %21, uzun dönem kullanımlarda ise yaklaşık %18 mukavemet artışı sağladığı belirlenmiştir.

Today, image processing applications in agriculture seems to spread rapidly. Image processing in agriculture are used in many areas such as classification of products, the detection of weeds, crop yields and weight estimation. In this study weight estimation of bread wheat and durum wheat in different amounts was performed by using image processing techniques. Image processing techniques were applied by using Matlab software. The counting of wheat kernels in image and weight estimation was carried out. Success rates were determined by comparing estimated weights of wheat kernels and their actual weight.

Tires are important parts of every vehicle including tractors and other off-road vehicles. Thus, structural and operational characteristics determination of the tires is too important. Tire deflection and tire contact area are functions of tractive performance. In this study an electronic system was designed in order to determine deflection of the tire. Deflection and contact area experiments were conducted by means of single wheel tester. As a result; the effects on deflection of dynamic axle load and inflation pressure were found significant (P<0.01) by utilizing variance analysis. There was a linear relationship between deflection and contact area of tire. The deflection of the tire increased with dynamic axle load for all inflation pressures tested. The deflection decreased with increasing inflation pressure. Additionally, increase in the tire load and decrease in the tire inflation pressure lead to bigger the tire contact area.

Utilization of shape memory alloys is rapidly spreading to many technological areas. From this point, alloys with shape memory are used in various fields such as temperature sensors in electronics, test valves in medicine, radiator fans in automotive and multi leg mobile robots. Application of nitinol fibers, which are actually shape memory alloys, as muscle fibers in industrial robots are increasing day by day. In this study, several tests were carried on aiming for the operational performance of nitinol fibers that are easy to control, economic, silent and harmless to environment and that have increasing utilization in recent motion technology. By using embedded systems, contraction (spasm) ratios and electrical current passing through the fibers were measured after 0.04 and 0.06 inch nitinol fibers were subjected to various voltages. Additionally, yielding limit value of nitinol fibers at split (breaking) point were detected. In the realized test system, ATmega 2560 microprocessor was took part as an embedded system in the Open Source Arduino Mega electronic card.

This paper proposes a Fuzzy Expert System design to determine the wearing properties of nitrided and non nitrided steel. The proposed Fuzzy Expert System approach helps the user and the manufacturer to forecast the wearing properties of nitrided and non nitrided steel under specified laboratory conditions. Surfaces of the engineering components are often nitrided for improving wear, corosion, fatigue specifications. A major property of nitriding process is reducing distortion and wearing of the metalic alloys. A Fuzzy Expert System was developed for determining the wearing and durability properties of nitrided and non nitrided steels that were tested under different loads and different sliding speeds in the laboratory conditions.

The work presents the metal injection molding (MIM) of carbon nanotubes reinforced aluminium matrix nanocomposite. The paraffin wax (PW), high density polyethylene (HDPE), stearic acid (SA) is used as a binder. Sintering of aluminium is a critical issue in injection molding. The new blind mold cavity sintering method is adopted to impart the strength in the MMC. The surface morphology is observed by the SEM. It is seen that aluminium particles uniformly welded and wide pores are visible in the MMC-Al product. Further the low temperature blind mold sintering helps to retain CNTs in the MMC-Al matrix. This imparts the higher hardness which is comparable with the aluminium alloy. The hardness tests carried out on sintered samples shows the results ranging from 42 to 73 BHN. The pores in these samples tested are in the ranges from 0.25µm to 1.0µm.

In this study, mechanical properties of multiwalled carbon nanotubes / high density polyethylene (MWCNT/HDPE) nanocomposite materials produced by method of injection molding have been investigated experimentally. Multi-walled carbon nanotubes (MWCNTs) have been incorporated into a high-density polyethylene (HDPE) matrix using twin screw extrusion and injection technique. High density polyethylene, which was reinforced with different percentages (1%, 3% and 5%) of carbon nanotubes, was produced in the form of tensile test bars and then tested. The tensile tests were performed according to ASTM D 638 test standards. The increase in tensile strength as a result of the added carbon nanotube was studied. After the experiments, changes of mechanism at fracture surfaces were examined. Experiments were repeated three times. As a result, it could be inferred that minimum percentage of carbon nanotubes reinforcement should be between 1% 3%.

Many studies on tractive performance of tractor tires have been carried out to solve soil-wheel interaction problems in the last decades. The purpose of this study is to experimentally determine effects on tractive performance of radial and bias-ply drive tires at three different tire lug heights, axle loads and inflation pressures. The experiments were carried out in stubble field conditions. To obtain sufficient performance data, a new single wheel tester was designed and manufactured. Travel reduction, net traction ratio and tractive efficiency varied from 3.3% to 34.1%, 0.24 to 0.93 and from 0.27 to 0.78 respectively depending on drawbar pull. The effects of tire type, lug height, dynamic axle load and inflation pressure on tractive efficiency were found significant (P<0.01) by the performed variance analysis and LSD tests. Radial tires provide better tractive performance compared with bias-ply tires. The tractive efficiency increased especially with increasing dynamic axle load and decreased with increasing tire inflation pressure. Tire dynamic axle load was the major contributory factor on tractive performance as compared with other independent variables. For a given drawbar pull, it was observed that tractive efficiency of radial tire can be maximized by selecting appropriate levels of lug height, dynamic axle load and inflation pressure.