فهرس المقالات Tool wear

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  1 - Optimization The High Speed Machining of Hardened AISI 4140 Steel Using Vapor Deposited Cutting Tools (Wear and Roughness)
  Mehdi Jalali Azizpour Ata Fardaghaie
  In this study, the main cutting parameters of high speed machining (HSM) including cutting speed, feed rate, depth of cut as well as deposition method were optimized using genetic algorithm considering the average surface roughness (Ra) of work piece and flank wear (Vb) أکثر

  In this study, the main cutting parameters of high speed machining (HSM) including cutting speed, feed rate, depth of cut as well as deposition method were optimized using genetic algorithm considering the average surface roughness (Ra) of work piece and flank wear (Vb) of CVD and PVD coated tool criteria in high speed turning of hardened AISI 4140 Steel. Standard L18 orthogonal array has been used for the design of experiment (DOE) applying Taguchi approach. Multiple linear regression model applying Minitab, was used to determine the relationship and interaction between machining parameters and outputs. For genetic algorithm(GA) optimization, the average was applied as a functional output of design of experiments. The results of GA for smaller- the better quality characterization shows the optimum roughness of 1.107 mm and optimum flank wear of 0.461mm. The confirmation tests were carried out in order to validate the response of predicted optimum condition. The results of validation test show a good agreement between obtained optimum condition and the results of genetic algorithm. The analysis of variance was used in order to obtain the contribution of each factor on the output statistically. ANOVA results indicated that the cutting speed and cut depth are the most effective factors on the flank wear by 37.02 and 27.80 percent contribution respectively. The most effective factors on surface roughness were feed rate and cutting speed by 82.49 and 10.50 percent contribution respectively. Stereoscopy and Scanning electron microscopy was used to evaluate the wear mechanism and topography of worn surface. تفاصيل المقالة
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  2 - Tool Wear Modeling in Drilling Process of AISI1020 and AISI8620 Using Genetic Programming
  Vahid Zakeri Mehrabad Vahid Pourmostaghimi
  In manufacturing industry, it has been acknowledged that tool wear prediction has an important role in higher quality of products and acceptable efficiency. Being an emerging area of research in recent years, drilling tool wear is an important factor which directly affe أکثر

  In manufacturing industry, it has been acknowledged that tool wear prediction has an important role in higher quality of products and acceptable efficiency. Being an emerging area of research in recent years, drilling tool wear is an important factor which directly affects quality parameters of machined hole such as hole centring, roundness, burr formation and finished surface. In this paper, the genetic equation for prediction of drilling tool flank wear was developed using the experimentally measured wear values and genetic programming for two different materials, AISI1020 and AISI8620 steels. These equations could be used to compare the behaviour of wear in both mentioned materials and analyse the effect of materials characteristics on wear rate and wear pattern. The suggested equations have been shown to correspond well with experimental data obtained for flank wear when machining in various cutting conditions.The results of experiments and equations showed that properties of work material can affect drill bit flank wear drastically. It was concluded that greater toughness and strength of AISI8620, compared to AISI1020, lead to higher cutting stresses and temperatures, resulting more flank wear. تفاصيل المقالة
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  3 - Vibration based Assessment of Tool Wear in Hard Turning using Wavelet Packet Transform and Neural Networks
  vahid pourmostaghimi Mohammad Zadshakoyan Morteza Homayon Sadeghi
  Demanding high dimensional accuracy of finished work pieces and reducing the scrap and production cost, call for devising reliable tool condition monitoring system in machining processes. In this paper, a tool wear monitoring system for tool state evaluation during hard أکثر

  Demanding high dimensional accuracy of finished work pieces and reducing the scrap and production cost, call for devising reliable tool condition monitoring system in machining processes. In this paper, a tool wear monitoring system for tool state evaluation during hard turning of AISI D2 is proposed. The method is based on the use of wavelet packet transform for extracting features from vibration signals, followed by neural network for associating the root mean square values of extracted features with tool flank wear values of the cutting tool. From the result of performed experiments, coefficient of determination and root mean square error for the proposed tool wear monitoring system were found to be 99% and 0.0104 respectively. The experimental results show that wavelet packet transform of vibration signals obtained from the cutting tool has high accuracy in tool wear monitoring. Furthermore, the proposed neural network has the acceptable ability in generalizing the system characteristics by predicting values close to the actual measured ones even for the cutting conditions not encountered in the training stage. تفاصيل المقالة
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  4 - Evaluation of the Cryogenic Effect on Friction Stir Processed AA7075/Si Matrix Nanocomposites
  Navid Molla Ramezani Behnam Davoodi
  Friction-stir processing is a green manufacturing process for surface composite fabrication and surface modification. To achieve this critical goal, the type of cooling and lubrication are of great importance. Therefore, in this paper, the cryogenic effects were investi أکثر

  Friction-stir processing is a green manufacturing process for surface composite fabrication and surface modification. To achieve this critical goal, the type of cooling and lubrication are of great importance. Therefore, in this paper, the cryogenic effects were investigated on friction-stir processing (FSP) tool wear and surface quality of an aluminum matrix nanocomposite. Silicon carbide (SiC) nanopowder was used as the reinforcing phase. The effects of cooling strategy and tool rotation speed on the tool wear, microhardness, surface roughness, and energy dispersive spectroscopy (EDS) analysis were studied. The cooling procedure was conducted under dry and cryogenic conditions. Additionally, the rotation speed was set at three levels, while other parameters were kept constant. The FSP tools were examined under a scanning electron microscope, and the wear mechanisms were investigated under different conditions. The results showed that tool wear, surface roughness, and microhardness were improved under cryogenic conditions compared to air conditions. Furthermore, in the presence of liquid nitrogen, the metal matrix composite did not exhibit any microstructural defects, such as micro-cracks. Energy dispersive spectroscopy analysis also demonstrated that SiC had better penetration into the base material under cryogenic conditions compared to dry conditions. تفاصيل المقالة
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  5 - Optimization of Spindle loading and Tool Wear for CNC Turning Machine by Using Intelligent System
  Morteza Sadegh Amalnik
  Intelligent knowledge based system (IKBS) is developed for optimizing dry CNC turning process using Taguchi method, CNC Machine, EN19 steel as the work piece material, andCutting Insert. Tool wear and spindle loading which are the machining parameters, spindle speed, fe أکثر

  Intelligent knowledge based system (IKBS) is developed for optimizing dry CNC turning process using Taguchi method, CNC Machine, EN19 steel as the work piece material, andCutting Insert. Tool wear and spindle loading which are the machining parameters, spindle speed, feed rate, and depth of cut, areoptimized through the intelligent knowledge based system (IKBS). The experimental CNC turning machine is used to evaluate IKBS. IKBS is developed to determine the effect of the machining parameters such as tool wear and spindle loading. The simultaneous optimization is done by IKBS. Fourlevels of each machining parameter are used inexperimental verification on Model PTC 600, CNC lathe machinetool of PRAGA. The experimental verification designed based on Taguchi’s method is used to evaluate the effect of the machining parameters on individual responses of IKBS. The simultaneous optimization is done by intelligent knowledge based system. Theoptimization of complicated multi-performancecharacteristics is simplified through this approach. Tool wear and spindle loading are twocharacteristics on the basis of which the machining parameters, spindle speed, feed rate, loading and depth of cut, areoptimized through IKBS. تفاصيل المقالة
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  6 - The Effectiveness of Ceramic Wiper Tool in Turning of Monel K500
  Mohammad Lotfi Saeid Amini Sayed Ali Sajjady Adil Hussein Juaifer
  In this study, turning operation of Monel K500 copper-nickel super-alloy was evaluated. Ceramic cutting tools with two different cutting noses (conventional and wiper) were utilized. At first, the experimental tests were designed by using central composite design method أکثر

  In this study, turning operation of Monel K500 copper-nickel super-alloy was evaluated. Ceramic cutting tools with two different cutting noses (conventional and wiper) were utilized. At first, the experimental tests were designed by using central composite design method. After implementation of the tests, the statistical models for output data (surface roughness, cutting force, and flank wear) have been developed. Furthermore, the effect of cutting parameters on output data was taken into account with help of analysis of variance. In third step, the optimal cutting condition was introduced for both cutting tools by using response surface method. In total, it was revealed that low depth of cut and feed rate coupled with high cutting speed is an optimal condition for turning of Monel super-alloy when ceramic tools are selected. In particular, the positive effect of wiper tool on output data was more when depth of cut has been lower than the length of wiper edge. تفاصيل المقالة
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  7 - ﺑﺮرﺳﯽ ماشین‌کاری تخلیه‌الکتریکی ماده مرکب آلومینیوم تقویت شده با نانو ذرات اکسید تیتانیوم
  علی اکبر لطفی سعید دانشمند
  نانو ذرات مورد استفاده در مواد مرکب زمینه فلزی دارای انواع مختلف و خواص فیزیکی، شیمیایی و مکانیکی متفاوتی می باشند که باعث بهبود سختی، مقاومت مکانیکی، سایش و خواص دمایی می شوند و قابلیت های ماشینکاری مواد را تغییر می دهند. در این تحقیق به بررسی پارامترهای ماشینکاری تخلی أکثر

  نانو ذرات مورد استفاده در مواد مرکب زمینه فلزی دارای انواع مختلف و خواص فیزیکی، شیمیایی و مکانیکی متفاوتی می باشند که باعث بهبود سختی، مقاومت مکانیکی، سایش و خواص دمایی می شوند و قابلیت های ماشینکاری مواد را تغییر می دهند. در این تحقیق به بررسی پارامترهای ماشینکاری تخلیه الکتریکی ماده مرکب الومینیوم تقویت شده با نانوذرات اکسید تیتانیوم پرداخته می شود. هدف از این تحقیق بررسی تاثیر شدت جریان، ولتاژ، زمان روشنی و خاموشی پالس و نانو ذرات اکسید تیتانیوم بر نرخ براده برداری، سایش ابزار و زبری سطح می باشد. از نفت سفید به عنوان دی الکتریک و الکترود مسی به عنوان ابزار و تجزیه و تحلیل واریانس برای اعتبار سنجی آزمایشگاهی استفاده می شود. نتایج نشان داد نانو ذرات سرامیکی اکسید تیتانیوم با توجه به ایتکه غیر هادی هستند تاثیر زیادی بر پارامترهای ماشینکاری ندارند و حین فرایند ماشینکاری تخلیه الکتریکی ذوب نمی شوند و شدت جریان و زمان روشنی بیشترین تاثیر بر نرخ براده برداری، سایش ابزار و زبری سطح دارند. با افزایش شدت جریان و زمان روشنی پالس سایش ابزار و زبری سطح زیاد شده و با افزایش زمان خاموشی پالس سایش ابزار کم می شود. به طور متوسط نرخ سایش الکترود ابزار در آلومینیوم 2024 تقویت شده با نانو ذرات اکسید تیتانیوم 5 درصد به میزان 46/3 درصد معادل 346/0گرم بیشتر از نمونه آلومینیوم 2024 از نظر وزنی است. تفاصيل المقالة
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  8 - Indirect prediction of flank wear using ANNs in turning of CK45
  Hossein Sepehri
  This work aims to develop models to investigate the effects of flank wear on cutting forces during the turning of ck45 steel using carbide tools. Therefore, various turning experiments were performed with different cutting conditions. Flank wear and cutting forces were أکثر

  This work aims to develop models to investigate the effects of flank wear on cutting forces during the turning of ck45 steel using carbide tools. Therefore, various turning experiments were performed with different cutting conditions. Flank wear and cutting forces were recorded at different stages of each experiment. The data obtained from the experiments showed that the tangential component of the cutting force was not significantly correlated with the tool flank wear. Instead, there was a good correlation between the axial and radial components of the cutting forces against flank wear. Since the cutting forces depend on both the cutting conditions and the tool flank wear, different cutting forces and cutting condition ratios were used to find the cutting force models that are more sensitive to tool wear. These ratios were used to develop artificial neural network models. The statistical results showed that the tool wear obtained from the artificial neural network models was very close to the results obtained from the experiments. In addition, the accuracy of the models including the axial component of cutting force was higher than in other models. تفاصيل المقالة