Modeling and Analysis for Surface roughness in Machining EN-31 steel using Response Surface Methodology

This paper utilizes the regression modeling in turning process of En-31 steel using response surface methodology (RSM) with factorial design of experiments. A first-order and second-order surface roughness predicting models were developed by using the experimental data and analysis of the relationship between the cutting conditions and response (surface roughness). In the development of predictive models, cutting parameters of cutting velocity, feed rate, depth of cut, tool nose radius and concentration of lubricants were considered as model variables, surface roughness were considered as response variable. Further, the analysis of variance (ANOVA) was used to analyze the influence of process parameters and their interaction during machining. From the analysis, it is observed that feed rate is the most significant factor on the surface roughness followed by cutting speed and depth of cut at 95% confidence level. Tool nose radius and concentration of lubricants seem to be statistically less significant at 95% confidence level. Furthermore, the interaction of cutting velocity/feed rate, cutting velocity/ nose radius and depth of cut/nose radius were found to be statistically significant on the surface finish because their p-values are smaller than 5%. The predicted surface roughness values of the samples have been found to lie close to that of the experimentally observed values

Anatomical variations of internal jugular vein as seen by site rite II ultrasound machine--an initial experience in Pakistani population

Objective: To determine the anatomical variations of the internal jugular vein (IJV) in Pakistani adult population with the help of Site Rite II ultrasound machine.Material and Method: The right IJV relation to the carotid artery was visualized at four different landmarks (angle of the mandible, thyroid cartilage, cricoid cartilage, and the supraclavicular area). Size of IJV in comparison to carotid artery was also seen. Results: In 49 cases the IJV was found in aberrant relation to carotid artery at the angle of the mandible (p value Conclusion:Care should be taken while cannulating IJV at the angle of the mandible and supra clavicular area by external landmark guided technique. Ultrasound guided technique should be used in every anticipated difficult cas

DESIGN AND DEVELOPMENT OF MECHANICAL REGENERATIVE BRAKING SYSTEM FOR ROAD VEHICLES

An innovative mechanical regenerative braking system for road vehicles, developed by the authors and patented, has been described. This system has been installed on an experimental solar electric vehicle and the energy saving during on road experiments has been studied and test results presented in this article. It has been concluded that by using this system about 70% of the energy, that might have gone waste while applying brakes, can be saved and the driving range can be increased

A note on the conceptual design of polymeric composite automotive bumper system

In this paper, a conceptual design approach to the development of polymeric-based composite automotive bumper system is presented. Various methods of creativity, such as mindmapping, product design specifications, brainstorming, morphology chart, analogy and weighted objective methods are employed for the development of composite bumper fascia and for the selection of materials for bumper system. The evaluation of conceptual design for bumper fascia is carried out using weighted objective method and highest utility value is appeared to be the best design concept. Polymer-based composites are the best materials for bumper fascia which are aesthetically pleasant, lighter weight and offer many more substantial advantages

Left Main Coronary Artery Revascularization in Patients with Impaired Renal Function: Percutaneous Coronary Intervention versus Coronary Artery Bypass Grafting

Introduction: The evidence about the optimal revascularization strategy in patients with left main coronary artery (LMCA) disease and impaired renal function is limited. Thus, we aimed to compare the outcomes of LMCA disease revascularization (percutaneous coronary intervention [PCI] vs. coronary artery bypass grafting [CABG]) in patients with and without impaired renal function. Methods: This retrospective cohort study included 2,138 patients recruited from 14 centers between 2015 and 2,019. We compared patients with impaired renal function who had PCI (n= 316) to those who had CABG (n = 121) and compared patients with normal renal function who had PCI (n = 906) to those who had CABG (n = 795). The study outcomes were in-hospital and follow-up major adverse cardiovascular and cerebrovascular events (MACCE). Results: Multivariable logistic regression analysis showed that the risk of in-hospital MACCE was significantly higher in CABG compared to PCI in patients with impaired renal function (odds ratio [OR]: 8.13 [95% CI: 4.19–15.76], p < 0.001) and normal renal function (OR: 2.59 [95% CI: 1.79–3.73]; p < 0.001). There were no differences in follow-up MACCE between CABG and PCI in patients with impaired renal function (HR: 1.14 [95% CI: 0.71–1.81], p = 0.585) and normal renal function (HR: 1.12 [0.90–1.39], p = 0.312). Conclusions: PCI could have an advantage over CABG in revascularization of LMCA disease in patients with impaired renal function regarding in-hospital MACCE. The follow-up MACCE was comparable between PCI and CABG in patients with impaired and normal renal function

Parametric Optimization of Machining Parameters using Graph Theory and Matrix Approach

Abstract This study investigated the multi-performance optimization of turning process for an optimal parametric combination to yield the minimum cutting forces and surface roughness with the minimum power consumption using graph theory and matrix approach. The experiments were carried out as per L 9 orthogonal array with each experiment performed under different machining conditions of feed rate, depth of cut and lubricant temperatures. In GTMA, a performance suitable index evaluates and optimizes the multi-performance characteristics. It is registered that the performance, for which the value of PSI is highest, is the optimum choice for the given machining conditions. The index is obtained from the matrix model developed from the digraphs. Graph theory and matrix approach methodology reveals that a combination of high level of depth of cut and lubricant temperature along with feed rate in the low level is essential in order to simultaneously minimize (optimize) the main cutting force, surface roughness and power consumption during steel turning. Keywords:Graph theory and matrix approach, surface roughness, cutting force and power consumption 1Introduction The need for improving the technological performance of machining operations as assisted by the cutting forces, surface finish, and cutting power and tool life has long been recognized to increase the economic performance of the machining operations. Metal cutting process is a complicated process where the performance depends upon a number of machining and tooling conditions. In a turning operation, it is important to select cutting parameters so that high cutting performance can be achieved. Selection of desired cutting parameters by experience or using handbook does not ensure that the selected cutting parameters are optimal for a particular machine and environment. The effect of cutting parameters is reflected on surface roughness, surface texture, cutting forces and dimensional deviations of the product. Surface roughness, which is used to determine and to evaluate the quality of a product, is one of the major quality attributes of a turning product. Surface roughness is a measure of the technological quality of a product and a factor that greatly influences manufacturing cost. It describes the geometry of the machined surfaces and combined with the surface texture. The mechanism behind the formation of surface roughness is very complicated and process dependen

Optimal Machining Parameters for Achieving the Desired Surface Roughness in Turning of Steel

Due to the widespread use of highly automated machine tools in the metal cutting industry, manufacturing requires highly reliable models and methods for the prediction of output performance in the machining process. The prediction of optimal manufacturing conditions for good surface finish and dimensional accuracy plays a very important role in process planning. In the steel turning process the tool geometry and cutting conditions determine the time and cost of production which ultimately affect the quality of the final product. In the present work, experimental investigations have been conducted to determine the effect of the tool geometry (effective tool nose radius) and metal cutting conditions (cutting speed, feed rate and depth of cut) on surface finish during the turning of EN-31 steel. First and second order mathematical models are developed in terms of machining parameters by using the response surface methodology on the basis of the experimental results. The surface roughness prediction model has been optimized to obtain the surface roughness values by using LINGO solver programs. LINGO is a mathematical modeling language which is used in linear and nonlinear optimization to formulate large problems concisely, solve them, and analyze the solution in engineering sciences, operation research etc. The LINGO solver program is global optimization software. It gives minimum values of surface roughness and their respective optimal conditions

Power Prediction Model for Turning EN-31 Steel Using Response Surface Methodology

Power consumption in turning EN-31 steel (a material that is most extensively used in automotive industry) with tungstencarbide tool under different cutting conditions was experimentally investigated. The experimental runs were planned accordingto 24+8 added centre point factorial design of experiments, replicated thrice. The data collected was statisticallyanalyzed using Analysis of Variance technique and first order and second order power consumption prediction models weredeveloped by using response surface methodology (RSM). It is concluded that second-order model is more accurate than thefirst-order model and fit well with the experimental data. The model can be used in the automotive industries for decidingthe cutting parameters for minimum power consumption and hence maximum productivit