Solid modeling for optimizing metal removal of three-dimensional NC end milling

In the past few years there has been a lot of interest and excitement generated by solid modeling. Numerous papers have been presented on the value and benefits of this technology. Many talented individuals have contributed to the state of the art. Solid modeling has played a larger role at SIGGRAPH in the past three years, with tutorials, panel discussions and technical papers. All this material has been presented for the most part by academics, researchers and developers of solid modeling systems. The users of solid modeling systems have yet to be heard from. The reason is that there have been very few of them out there in the past. However, that situation is slowly changing. Now that several CAD/CAM vendors are marketing solid modeling systems, a small cadre of users does exist. This panel will be composed primarily of users of solid modeling systems. They will discuss topics of interest to potential users (and also developers) of solid modelers. Questions to be addressed include: What is the status of solid modeling systems from a user standpoint? Can the present solid modelers be used in a production environment today? Should a solid modeling system replace the present wire frame and surface systems or be integrated with them? What are the problems associated with using a solid modeling system? How good is the user interface? Does the necessary application software exist? The primary intent of this Panel discussion is to give the potential user some idea as to whether the available solid modeling systems are useful for his applications. It is beginning to look like the next generation CAD/CAM system for mechanical design will be a solid modeler. The big question is “when will this occur?”

<div class="section abstract"><div class="htmlview paragraph">Aluminium alloys enrolled their applications in automobile sectors, agricultural equipment, machine tools and aerospace because of their weight-to-strength ratio. Aluminium alloy 7075-T651 is an inevitable material used in engineering sectors. Turning is a metal removal process, to obtain net geometrical aspects and better surface finish of the products. The machinability of the turning operation is based on different factors; however, turning factors and material of tool plays a significant position in the turning process. To identify the truthful cutting parameters to achieve multi-responses in turning operation, the experiment was designed via Response Surface Methodology (RSM) Central Composite Design (CCD) and the experimental results are analyzed under the desirability approach. By trialing 26 interpretations in the desirability approach; the optimal cutting parameter settings of speed 800 rpm, feed rate 0.140315 mm/rev and depth of cut 0.3501 mm have been revealed to enhance surface roughness (SR) and metal removal rate (MRR).The confirmation test addresses better agreement with the predicted value of responses, the result of the investigation directed to the industries for the variant aluminium alloy parts manufacturing.</div></div>

Parametric optimizination of machining parameter in CNC turning of al based hybrid metal matrix composites

Application of desirability approach for multi-response optimization of machining parameters of age-hardened hybrid aluminum composites

The present study concentrated on the variation of process parameters on metal removal rate (MRR) used in turning of widely used material (stainless steel 304 and Mild steel). Turning is essential and robust process of material removal in the form of chips. The Turning process involved lots of process parameters as tool geometry, feed rate, rotational speed of job and rigidity of machine tools etc. In the present work study was done on the following cutting parameters as cutting speed (85,150 and 250 rpm), feed rate (0.13, 0.28 and 0.15, 0.09 mm/sec), depth of cut (0.4, 0.7 and 1 mm). The three label orthogonal array for process parameters were selected for metal removal rate analysis. The carbide tipped cutting tool was selected as cutting tool of positive rake angle. The analysis of process parameters was done through Minitab 17 software. The orthogonal array was selected 3*3; by the use of signal to noise (S/N) ratio is to minimise the variation due to uncontrolled parameters with the help of Taguchi method. Total nine experiments were performing on stainless steel and other set of nine experiments were perform on the mild steel. The experimental results reveals that moderate cutting speed 150 rpm, 0.09 mm/sec feed rate and 1 mm depth of cut yield good results for stainless steel 304 grade and mild steel.

In modern machining industries, tool chatter detection and suppression along with maximized metal removal rate is a challenging task. Inexpedient vibration between cutting tool and work piece promotes unstable cutting. This results in enhanced detritions of tool and poor surface finish along with unpredictable metal removal rate. In the present work, effect of machining parameters such as depth of cut ( d), feed rate ( f) and spindle speed ( N) on chatter severity and metal removal rate have been ascertained experimentally. Experimentally recorded raw chatter signals have been denoised using wavelet transform. An artificial neural network model based on feed forward back propagation network has been proposed for predicting stable cutting zone and metal removal rate in turning process. It has been deduced that Tangent Sigmoid activation function in an artificial neural network is the best option to achieve the aforesaid objectives. Well correlation between the artificial neural network predicted results and experimental ones validate the developed technique of ascertaining the tool chatter severity.

In this paper, a new attempt has been made in the area of tool-based micromachining for automated, non-contact, and flexible prediction of quality responses such as average surface roughness (Ra), tool wear ratio (TWR) and metal removal rate (MRR) of micro-turned miniaturized parts through a machine vision system (MVS) which is integrated with an adaptive neuro-fuzzy inference system (ANFIS). The images of machined surface grabbed by the MVS could be extracted using the algorithm developed in this work, to get the features of image texture [average gray level (Ga)]. This work presents an area-based surface characterization technique which applies the basic light scattering principles used in other optimal optical measurement systems. These principles are applied in a novel fashion which is especially suitable for in-process prediction and control. The main objective of this study is to design an ANFIS for estimation of Ra, TWR, and MRR in micro-turning process. Cutting speed (S), feed rate (F), depth of cut (D), Ga were taken as input parameters and Ra, TWR, MRR as the output parameters. The results obtained from the ANFIS model were compared with experimental values. It is found that the predicted values of the responses are in good agreement with the experimental values.

The work reported in this paper deals with the mechanism of metal removal in electrothermic machining. An empirical relation between the metal removal rate and the current has been established. The effect of tool materials and polarity on metal removal rate has also been analysed.

This paper investigates on electrochemical micromachining of woven fabric masked stainless steel SS304 using 0.5 mm copper tool electrode with sodium nitrate (NaNO3) Electrolyte. Investigation is carried out to express the performance measures of micro hole such as metal removal rate (MRR), taper angle (TA) and surface roughness (SR). The experimental plan is based on taguchi L16 orthogonal array. Various input process parameters such as voltage, duty ratio, rotational speed, feed rate of tool and electrolyte concentration are varied at four levels. Significant contributions by input process parameters for each output responses such as metal removal rate, taper angle and surface roughness are analysed using contour plots. It is evident that significant contribution to metal removal rate mainly depends on rotational Speed and feed rate of tool. Similarly, duty ratio and feed rate of tool are the significant contributors for both taper angle and surface roughness. Multi response optimization are done for the three output responses using VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method to identify the significant process parameter. Performance score of VIKOR and TOPSIS proved that rotational speed of tool, feed rate and duty ratio are important parameters contributing significantly for precision of microfeatures. Both the multi response optimisation methods mutually concluded the best performance is achieved at voltage 21 V, duty ratio 80%, rotational speed of tool 600 rpm, feed rate of tool 0.8 μm s−1 and electrolyte concentration 0.2 M. The confirmation test showed an improvement of performance grade by approximately 0.245.

Stir casting was utilized to generate the composites. The AA 2618–10wt% zirconium carbide 10wt% rice husk ash hybrid composite had the highest hardness value. In comparison to pure AA 2618, it had a 72% increase. The rule of mixture was used to compute theoretical density, whereas the Archimedes rule was utilized to evaluate real density. For AA 2618, AA 2618/zirconium carbide, and rice husk ash hybrid composites, simple carbide inserts were used for turning. Surface roughness, metal removal rate, and tool wear were among the numerous responses examined. RSM was utilized to analyze and optimize the test outcomes. Feed rate was the most critical issue for surface roughness and material removal rate. Tool wear was shown to be most strongly controlled by tool speed, whereas metal removal rate was found to be least significantly influenced by the weight percent of reinforcement.

Although curved-surface solid modeling systems achieve a higher level of accuracy than faceted systems, they also introduce a host of topological, geometric, and numerical complications. A method for calculating accurate boundary representations of solid models is introduced that reduces the impact of these complications. The method uses a pair of bounding polyhedral approximations to enclose the boundary of each object. A structural analysis automatically determines where to make adaptive refinements to the polyhedrons to assure the topological validity of the results. Potential singularities are localized. The implementation is an experimental extension to the Geometric Design Processor (GDP) solid modeling system. >

Because of having a high reduction potential, the zero-valent iron (ZVI) is often applied for the remediation of wastewater or groundwater with heavy metals. The purpose of this study was aimed to investigate the reaction behavior of heavy metals with ZVI nanoparticles in the wastewater. The affecting factors, such as initial pH, dosage of nanoscale ZVI and initial concentration of heavy metal, on the removal efficiency of heavy metals by ZVI in the wastewater were examined by the batch experiments in this study. It was found that the removal of heavy metals was affected by initial pH. The rate and efficiency of metal removal increased with decreasing initial pH. Greater than 90% of the heavy metals were removed when the initial pH was controlled at 2. In addition, the rate and efficiency of metal removal increased as the dosage of nanoscale ZVI increased. The removal efficiency of heavy metal was higher than 80% when 2.0 g/L of ZVI was added in the wastewater. On the other hand, the slow rate and low efficiency of metal removal from the wastewater treated by nanoscale ZVI was found in the wastewater with high concentration of heavy metal.

PLANT DESIGN ON MICROCOMPUTERS

Stainless steel is the most widely used alloys of steel. The reputed variety of stainless steel having customised material properties as per the design requirements is Duplex Stainless Steel and Austenitic Stainless Steel. The Austenite Stainless Steel alloy has been developed further to be Super Austenitic Stainless Steel (SASS) by increasing the percentage of the alloying elements to form the half or more than the half of the material composition. SASS (Grade-AL-6XN) is an alloy steel containing high percentages of nickel (24%), molybdenum (6%) and chromium (21%). The chemical elements offer high degrees of corrosion resistance, toughness and stability in a large range of hostile environments like petroleum, marine and food processing industries. SASS is often used as a commercially viable substitute to high cost non-ferrous or non-metallic metals. The ability to machine steel effectively and efficiently is of utmost importance in the current competitive market. This paper is an attempt to evaluate the machinability of SASS which has been a classified material so far with very limited research conducted on it. Understanding the machinability of this alloy would assist in the effective forming of this material by metal cutting. The novelty of research associated with this is paper is reasonable taking into consideration the unknowns involved in machining SASS. The experimental design consists of conducting eight milling trials at combination of two different feed rates, 0.1 and 0.15 mm/tooth; cutting speeds, 100 and 150 m/min; Depth of Cut (DoC), 2 and 3 mm and coolant on for all the trials. The cutting tool has two inserts and therefore has two cutting edges. The trial sample is mounted on a dynamometer (type 9257B) to measure the cutting forces during the trials. The cutting force data obtained is later analyzed using DynaWare supplied by Kistler. The machined sample is subjected to surface roughness (Ra) measurement using a 3D optical surface profilometer (Alicona Infinite Focus). A comprehensive metallography process consisting of mounting, polishing and etching was conducted on a before and after machined sample in order to make a comparative analysis of the microstructural changes due to machining. The microstructural images were capture using a digital microscope. The microhardness test were conducted on a Vickers scale (Hv) using a Vickers microhardness tester. Initial bulk hardness testing conducted on the material show that the alloy is having a hardness of 83.4 HRb. This study expects an increase in hardness mostly due to work hardening may be due to phase transformation. The results obtained from the cutting trials are analyzed in order to judge the machinability of the material. Some of the criteria used for machinability evaluation are cutting force analysis, surface texture analysis, metallographic analysis and microhardness analysis. The methodology followed in each aspect of the investigation is similar to and inspired by similar research conducted on other materials. However, the novelty of this research is the investigation of various aspects of machinability and drawing comparisons between each other while attempting to justify each result obtained to the microstructural changes observed which influence the behaviour of the alloy. Due to the limited scope of the paper, machinability criteria such as chip morphology, Metal Removal Rate (MRR) and tool wear are not included in this paper. All aspects are then compared and the optimum machining parameters are justified with a scope for future investigations.

Mathematical and MATLAB based process optimization by simulated annealing algorithm for wire electrical discharge machining of EN31