Modeling and optimization of surface roughness and vibration amplitude in heat assisted end milling of SKD 11 tool steel using ball nose tool

Tool steel - SKD 11 is frequently used in industries for making dies and molds. This grade is chosen for its toughness, strength, and hardness maintained up to high temperature. However, the same properties make the steel extremely difficult and expensive to machine using conventional approaches. Heat assisted machining has been found wide spread application in recent years to improve machinability of difficult-to-cut materials. This research paper presents the outcome of an investigation on heat assisted end milling of SKD 11 conducted on a vertical machining center using ball nose coated carbide inserts. The Design of Experiments (DoE) was done using the Response Surface Methodology, in order to develop empirical mathematical models of surface roughness and vibration in terms of cutting speed, feed, axial depth of cut, and heating temperature. The models were checked for significance using Analysis of Variance (ANOVA). 3-D response surface graphs of the interactions of primary cutting parameters with the responses were plotted. Optimization was then performed by using the desirability function approach. From the graphs and optimized results it was concluded that the primary input parameters could be controlled in order to reduce vibration amplitude and produce semi-finished machined surfaces applying induction heat assisted technique

Prediction of surface roughness in hard milling of AISI D2 tool steel

This paper presents a study of the development of a surface roughness model in end milling of hardened steel AISI D2 using PVD TiAIN coated carbide cutting tool. The hardness of AISI D2 tool lies within the range of 56-58 HRe. The independent variables or the primary machining parameters selected for this experiment were the cutting speed, feed, and depth of cut. First and second order models were developed using Response Surface Methodology (RSM). Experiments were conducted within specified ranges of the parameters. Design-Expert 6.0 software was used to develop the surface roughness equations as the predictive models. Analysis of variance (ANOVA) with 95% confidence interval has indicated that the models are valid in predicting the surface roughness of the part machined under specified condition

Preheating in end milling of AISI D2 hardened steel with coated carbide inserts

This study was conducted to investigate the effect of preheating through inductive heating mechanism in end milling of AISI D2 hardened steel (60-62 HRC) by using coated carbide tool inserts. Apart from preheating, two other machining parameters such as cutting speed and feed were varied while the depth of cut constant was kept constant. Tool wear phenomenon and machined surface finish were found to be significantly affected by preheating temperature and other two variables. End milling operation was performed on a Vertical Machining Centre (VMC). Preheating of the work material to a higher temperature range resulted in a noticeable reduction in tool wear rate leading to a longer tool life. In addition, improved surface finish was obtained with surface roughness values lower than 0.4 um, leaving a possibility of skipping the grinding and polishing operations for certain applications

Prediction of tool life in end milling of hardened steel AISI D2

Most published research works on the development of tool life model in machining of hardened steels have been mainly concerned with the turning process, whilst the milling process has received little attention due to the complexity of the process. Thus, the aim of present study is to develope a tool life model in end milling of hardened steel AISI D2 using PVD TiAIN coated carbide cutting tool. The hardness of AISI D2 tool lies within the range of 56-58 HRC. The independent variables or the primary machining parameters selected for this experiment were the cutting speed, feed, and depth of cut. First and second order models were developed using Response Surface Methodology (RSM). Experiments were conducted within specified ranges of the parameters. Design-Expert 6.0 software was used to develop the tool life equations as the predictive models. The predicted tool life results are presented in terms of both 1st and 2nd order equations with the aid of a statistical design of experiment software called Design-Expert version 6.0. Analysis of variance (ANOVA) has indicated that both models are valid in predicting the tool life of the part machined under specified condition and the prediction of average error is less than 10%

Modeling of surface roughness during end milling of AISI H13 hardened tool steel

Hard machining, a frequently used term in today’s machine tool industries, refers to the machining of material with a hardness value over 45 HRC. The concept of hard machining was developed in 80s; however, the prevalent industrial implementation of hard part machining was adopted during the last decade [1]. Advantages in hard machining incorporate the complete machining process with a single fixture setup, eliminating intermediate heat treatment and final grinding process while still meeting the dimensional and surface roughness specifications [2]. The widespread demand of hardened tool steel like AISI H13 requires high speed machining (HSM). Over the last decade, HSM has been used to manufacture molds/dies made from AISI H13. Many progressive works have been carried out to improve the high speed machining performance of H13. However, despite the significant importance of surface finish most of the machining researchers to date have concentrated on chip morphology, tool life and wear mechanism. In hard part machining, surface finish is a major quality criterion. With an accurate level of roughness it is possible to eliminate final grinding process, sometime even the hand polishing [3]. Considering its importance some researchers conducted their studies on surface quality during hard machining. Choudhury at el. [4] applied Taguchi method for the prediction of surface roughness during the end milling of AISI H13 tool steel and found that roughness value tends to decrease with increasing cutting speed and decreasing feed rate. El-Baradie [5] drew similar conclusion on cutting speed. He observed that increase of cutting speed maximizes productivity, at the same time, it improves surface quality. However, in all of the above cases and other works related to the surface roughness study it was found that the lowest achievable surface finish was only 0.2 μm. at high cutting speed mode. In most of the cases roughness values were sufficiently high to fall in the grinding region (above 0.2 to 0.4 μm). Moreover, material removal rate was limited for using lower radial depth of cut and feed per tooth (Rd = 0.3 mm to 0.8 mm and f = 0.10 mm/tooth). In this context, considering the influence of surface finish on mold/die for net shape manufacturing, current paper deals with the performance of PCBN and PVD-TiAlN coated carbide tool inserts in terms of surface roughness during the end milling of H13 hardened tool steel (52 HRC). In this regard, mathematical models based on the experimental results were developed in order to predict the surface finish during the end milling of H13 hardened tool steel

Development of tool life prediction model of TiAlN coated tools during the high speed hard milling of AISI H13 steel

Considering the demand for reduced cycle time and increased productivity hard turning and milling have become a useful alternative when high material removal rate is an immense requirement. Advantages in hard machining incorporate the complete machining process with a single fixture setup, eliminating intermediate heat treatment and final grinding process while still meeting the dimensional and surface roughness specifications [1]. Over the last decade high speed machining has been used extensively to produce mould and die from hardened material like AISI H13 tool steel. Many progressive works have been carried out to improve the high speed machining performance of H13. Despite the widespread adoption of milling process in fabricating mould and die, most of the research works till to date concentrated on hard turning. J. J. Junz Wang & M. Y. Zheng, 2003 et al [1], illustrated the machining characteristics of AISI H13 tool steels of hardness 41 and 20 HRC and found that the higher cutting and frictional energies are required in the chip shearing as well as in the nose ploughing processes of the softer tool steel. Poulachon et al. [2] , showed that the major influencing parameter on tool-wear happens to be the presence of carbides in the steel microstructure. Ghani et al. [3] applied Taguchi method to optimize cutting parameters in end milling of H13 steel at high speed cutting. They found that feed and depth of cut possess the most significant effect over tool life for a given range of cutting speed, feed and depth of cut. Recently with the advent of new fabrication and coating technology, tool insert like TiAlN coated carbide is receiving increasing attention from both industrial and research communities. Coated carbide tools enjoy lower price than CBN tools, (normally used for hard machining) but have a shorter tool life with lower material removal in comparison to PCBN. Early prediction of tool wear during high speed machining by coated carbide is quite important since high tool wear has an adverse effect on surface finish, which is considered to be the major quality criterion of finished part. In this context, in present study, an appropriate model for effective prediction of tool life has been developed during the high speed end milling of H13 tool steel using PVD-TiAlN coated tool inserts. RSM is a statistical method that combines design of experiments, regression analysis and statistical inferences [4]. RSM also reduces total number of trials needed to generate the experimental data in order to response model. The application of RSM in machining parameter optimization was first reported to be used by SM.Wu, 1965. Since then many researchers have been using this technique to design their experiments and model the responses. Alauddin et al. [5] used RSM to optimise the surface finish in end milling of Inconel 718 under dry condition. They developed contours to select a combination of cutting speed, and feed without increasing the surface roughness. Öktem et al. [6] incorporated RSM with developed genetic algorithm to optimize cutting parameters for better surface quality in case of Inconel 718. S. Saikumar and M. S. Shunmugam et al. [7] also combined RSM with differential evolution and genetic algorithms to draw a comparison between these methods. In current study, the model has been developed by RSM in terms of cutting speed (v), feed (f) and axial depth of cut (a). Experimental runs were designed based on the principles of central composite design (CCD) of RSM. Tool life data collected from the experimental trials were used to formulate the RSM models

Ankle fractures: the operative outcome

Ankle fractures are commonly seen in orthopaedic practice. This retrospective study of patients with ankle fractures who underwent surgical treatment in our institution from January 2000 to December 2003 was undertaken to analyze the common causes and patterns of ankle fractures; and the functional outcome of operative treatment for these fractures. Eighty patients were identified and reviewed. There were 65 male (81.3%) and 15 female patients (18.7%) with age ranging from 13 to 71 years old (mean, 32.3y). Common causes of ankle fractures were trauma (especially motor vehicle accidents), sports injuries and the osteoporotic bones in the elderly. Weber C (64.0%) was the most common pattern of fracture at presentation. The most common operative treatment for ankle fractures was open reduction and internal fixation (73 patients, 91.2%). Excellent and good outcomes were achieved in 93.8% of cases when measured using the Olerud and Molander scoring system for foot and ankle. In conclusion, operative treatment for ankle fractures restores sufficient stability and allowed mobility of the ankle joint

The effect of cryogenic cooling in machinability of stainless steel during turning

A high cutting temperature inherently characterizes high production machining. Such a high cutting temperature adversely effects tool life, dimensional and form accuracy and surface integrity of the product. Currently, an effort is being made to control this problem by reducing heat from the cutting zone through proper selection of machining parameters, cutting fluid application and heat resistant tools. The objective of this project is to investigate the effect of cryogenic cooling in machinability of stainless steel during turning. Cryogenic cooling is a promising new technology, which economically addresses the current processes environmental, and health, concerns. Cooling the cutting tool with liquid nitrogen (-320°F) is expected to maintain tool hardness and life. Cooling the chip makes it brittle and aids removal. Because nitrogen is an abundant atmospheric constituent and the quantities used are small, there is no unfavorable environmental effect or health impact or coolant disposal cost, and the chips are readily recycled. It was assumed that using cryogenic cooling during turning operation would discover some improvement in machinability of stainless steel by using cryogenic cooling during turning operationLarge number of research works performed in the area of metal cutting has contributed towards understanding the basic principles of improving machinability. It is therefore worthwhile to explore the possibility to strengthen the continuity of these works. This research intends to emphasize on chatter analysis to establish a co-relation between chatter and machinability, which is seldom highlighted by scientists and researchers. Chatter is an unwanted phenomenon in machining due to its adverse effects on the product quality, operation cost, machining accuracy, tool life, machine-tool bearings, and machine-tool life. The term defines the self-excited violent dynamic motion between the cutting tool and work piece [1]. Chatter analysis could be another accurate, precise, effective and efficient method to analyze instantaneous cutting environment and performance. Cryogenic cooling is the cooling approach to replace conventional coolant by liquefied gas in machining process [2]. In most cases, the liquid nitrogen (LN2) is chosen because of its availability and cost. There were many research works [3-5] on the application of cryogenic cooling to improve the machinability of the hard to cut materials. Liquid nitrogen (LN2) as a cryogenic coolant has been widely investigated, especially for machining hard to cut material [6,7]. Cryogenic cooling is being looked at as a potential replacement of conventional mineral oil based coolants because the latter is being rejected on grounds on serious environmental and health problems that it causes [8]. It is therefore essential to design efficient cryogenic cooling systems for high speed machining applications of hard-to-machine materials. The impact of cryogenic cooling on chip breaking and tool wear intensity during end milling and turning has been investigated by various researchers [9] but there has not been any study on the impact of cryogenic cooling on chip formation and chatter

Modelling of tool life by response surface methodology in hard milling of AISI D2 tool steel

Tool life prediction is an important factor that has profound influence on the higher productivity in industrial activities. High metal removal rate is intended to reduce the manufacturing cost and operation time. The productivity interms of a machining operation and machining cost, as well as quality assurance, and the quality of the workpiece machined surface and its integrity are strongly depend on tool wear and consequently it depends on the life of the tool. Moreover, despite having the target of achieving optimum superficial finishing with the shortest possible time one must take into account the consideration of tool life, so that the complete finishing operation can be carried out with just one tool, avoiding the intermediate stops in order to change the tool due to its wear [1] Eventually, sudden failure of cutting tools lead to loss of productivity, rejection of parts and consequential economic losses [2] There are various methodologies and strategies that were adopted by researchers in order to predict tool wear or tool life in milling and turning. Response surface methodology (RSM) which is classified into designed experiments approach seems to be the most wide-spread methodology for the surface roughness prediction. RSM is an important methodology used in developing new processes, optimizing their performance, and improving the design and/or formulation of new products. [3] It is a dynamic and foremost important tool of design of experiment (DOE), wherein the relationship between responses of a process with its input decision variables is mapped to achieve the objective of maximization or minimization of the response properties. Many researchers have used RSM for their experimental design and analysis of the results in end milling, but very few of them were engaged in machining hard material which is commonly known as hard milling. Vivancos [4] presented a model for the prediction of surface roughness in high-speed side milling of hardened die steels. Palanisamy et al. [2] predicted the response variable tool wear based on DOE combined with RSM technique in a universal milling machine on AISI 1020 steel using carbide insert. The development of a surface roughness model for end milling EN32 casehardening carbon steel (160 BHN steel) using design of experiments and RSM was discussed by Mansor & Abdalla [5] As has been seen here, the most work done exclusively in milling of carbon steel where the hardness values are less than 40 HRC

Photon parameters for gamma-rays sensing properties of some oxide of lanthanides

In the present research work, the mass attenuation coefficients (μm) representing the interaction of gamma photons with some oxide of lanthanides (Lu2O3Yb2O3, Er2O3, Sm2O3, Dy2O3, Eu2O3, Nd2O3, Pr6O11, La2O3 and Ce2O3) were investigated using WinXCom software in the wide energy range of 1 keV–100 GeV. The calculated values of μm afterwards were used to evaluate some gamma rays sensing properties as effective atomic effective atomic numbers (Zeff), effective electron densities (Nel), half value layer (HVL) and mean free path (MFP). The computed data observes that, the Lu2O3 shown excellent γ-rays sensing response in the broad energy range. At the absorption edges of the high elements present in the lanthanide compounds, more than a single value of Zeff were found due to the non-uniform variation of µm. Comparisons with experiments wherever possible have been achieved for the calculated µm and Zeff values. The calculated properties are beneficial expanded use of designing in radiation shielding, gas sensors, glass coloring agent and in electronic sensing devices