فهرس المقالات Cutting Forces

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  1 - Estimation of Surface Roughness in Turning by Considering the Cutting Tool Vibration, Cutting Force and Tool Wear
  A. Salimi A. Ebrahimpour M. Shalvandi E. Seidi
  Surfacequality along with the low production cost, play significant role in today’s manufacturing market. Quality of a product can be described by various parameters. One of the most important parameters affecting the product quality is surface roughness of the ma أکثر

  Surfacequality along with the low production cost, play significant role in today’s manufacturing market. Quality of a product can be described by various parameters. One of the most important parameters affecting the product quality is surface roughness of the machined parts. Good surface finish not only assures quality, but also reduces the product cost. Before starting any machining process, surface finish is predictable using cutting parameters and estimation methods. Establishing a surface prediction system on a machine tool, avoids the need for secondary operation and leads to overall cost reduction. On the other hand, creating a surface estimation system in a machining plant, plays an important role in computer integrated manufacturing systems (CIMS). In this study, the effect of cutting parameters, cutting tool vibration, tool wear and cutting forces on surface roughness are analyzed by conducting experiments using different machining parameters, vibration and dynamometers sensors to register the amount of tool vibration amplitude and cutting force during the machining process. For this, a number of 63 tests are conducted using of different cutting parameters. To predict the surface quality for different parameters and sensor variables, an ANN model is designed and verified using the test results. The results confirm the model accuracy in which the R2 value of the tests was obtained as 0.99 comparing with each other. تفاصيل المقالة
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  2 - Designing an Artificial Neural Network Based Model for Online Prediction of Tool Life in Turning
  A. Salimiasl A. Özdemir I. Safarian
  Artificial neural network is one of the most robust and reliable methods in online prediction of nonlinear incidents in machining. Tool flank wear as a tool life criterion is an important task which is needed to be predicted during machining processes to establish an on أکثر

  Artificial neural network is one of the most robust and reliable methods in online prediction of nonlinear incidents in machining. Tool flank wear as a tool life criterion is an important task which is needed to be predicted during machining processes to establish an online tool life estimation system.In this study, an artificial neural network model was developed to predict the tool wear and tool life in turning process. Cutting parameters and cutting forces were used as input and tool flank wear rates were regarded as target data for creating the online prediction system. SIMULINK and neural network tool boxes in MATLAB software were used for establishing a reliable online monitoring model. For generalizing the model, full factorial method was used to design the experiments. Predicted results were compared with the test results and a full confirmation of the model was reached. تفاصيل المقالة
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  3 - شبیه‌سازی نیروها و ارتعاشات برشی استاتیک و دینامیک برای ابزارهای سرامیکی فرزکاری کارگذاری شده
  پرویز قزوینیان
  ابزار برشی با کارگذاری های سرامیکی به طور فزاینده ای در ماشین کاری الیاژهای سوپر که معمولا در صنعت هوافضا کاربرد دارد، استفاده می شود. کارگذاری های سرامیکی سرعتهای برش بالاتری را به دلیل مقاومت حرارتی بالاتر در مقایسه با کارگذاری های کاربیدی ایجاد می کنند. اما موفقیت ای أکثر

  ابزار برشی با کارگذاری های سرامیکی به طور فزاینده ای در ماشین کاری الیاژهای سوپر که معمولا در صنعت هوافضا کاربرد دارد، استفاده می شود. کارگذاری های سرامیکی سرعتهای برش بالاتری را به دلیل مقاومت حرارتی بالاتر در مقایسه با کارگذاری های کاربیدی ایجاد می کنند. اما موفقیت این پروسه خیلی به انتخاب درست پارامترهای پروسه حساس است. در این مطالعه، مدلهای پروسه آنالیتیکی برای ابزار فرزکاری قابل پیوست با کارگذاری های سرامیکی گرد ارائه می شود. این مدلها را می توان برای تعیین پارامترهای برشی برای کیفیت بهینه و بهره وری ماکزیمم بکار برد. ابتدا، هندسه حاشیه های برشی کارگذاری تحت اثر زوایا روی کار گذاری ها فرموله گردید. انگاه یک مدل نیروی برشی تحلیلی ایجاد گردید. این کار به تحلیل اثرات پارامترها روی نیروهای برشی امکان می دهد. یک مدل زمان حوزه نیز برای تحلیل نیروهای برشی دینامیک و حدود ایستایی برای پروسه فرزکاری ایجاد گردیده است. پس از آن، مدلها در متلب GUI اجرا گردید تا کاربردهای مدل را در صنعت اسان سازد. ضرایب همبستگی نیروی برشی که برای محاسبه نیروهای برشی نیاز است از تست های برش با ماده Inconel718 شناسایی گردید. آنگاه مدل نیروی برشی با تجربیات برشی روایی سازی گردید. بعد از کسب داده های مدل ابزار از طریق تست تپ، نیروها و ارتعاشات برشی دینامیک بوسیله مدل حوزه زمان شبیه سازی گردید. یک سری از شبیه سازی ها انجام گرفت تا حدود ایستایی را در برخی شرایط عملیاتی با استفاده از مدل حوزه زمان تعیین کند و لبهای ایستایی برای ابزار تحت مطالعه رسم گردید. تفاصيل المقالة
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  4 - 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
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  5 - Investigation of Cutting Forces Superalloy Inconel 718
  سید مسعود بدخشیان مجید کریمیان سید علی افتخاری
  Since the cutting tools used in machining process of super alloys are subjected to high cutting forces, accordingly tools life is reduced, therefore improvement in alloys machining and reducing cutting forces to achieve longer tools life is an essential necessity. In th أکثر

  Since the cutting tools used in machining process of super alloys are subjected to high cutting forces, accordingly tools life is reduced, therefore improvement in alloys machining and reducing cutting forces to achieve longer tools life is an essential necessity. In this research, the effect of changes in feed rate on cutting forces in machining process of nickel based super alloys is investigated. Cutting tools used in this experiment was a tungsten carbide material, model 890, geometry square shaped and specification of SNMG 120412. Also the tools has been coated using physical vapor deposition by chemical composition of TiN/TiCN/AlTiSiN in both micro and nano layer conditions. According to the results, as the feed rate is increased cutting forces mostly increases in both micro and nano layer coating conditions. . Generally in this research, application of micro layer coating results in less cutting forces compared to nano layer coating, so it can be said that micro layer coating has a better performance تفاصيل المقالة