Dimensional Machining Research Articles

Optimization of the objective function –surface quality by end-milling dimensional machining of some aluminum alloys

In the aerospace industry, the milling of aluminum alloy parts is a machining process with the primary purpose of removing high volumes of material. Aluminum alloys are materials that have relatively good machinability, which helps the process because many of the components of the aircraft are of high dimensions. These parts have many pockets more or less deep, and the removal by cutting off about 90% of the initial volume of the workpiece is a matter of consideration. The manufacturing process is protracted and involves long semi-finishing and finishing operations, so it is recommended that any researcher who begins and finishes an experimental study should do it base on a specific experimental plan. Mathematical statistics techniques and methods are used, but also optimization methods that lead to a rational choice of process parameters, process input data and objective functions that need to be improved. This scientific paper presents applied research based on an extremely pertinent active experiment that has led to some practical solutions applied in the aerospace industry worldwide. The dedicated objective function on which the study conducted in this case was the mean arithmetic deviation of the surface profile. The independent variables were chosen by the concrete application of a dispersion analysis applied to the milling process, namely the cutting speed, the cutting depth and the feed per tooth. Interpretation of the results was performed by a graphical evaluation of the normality of the data distribution, by presenting the histogram responses as well as by the dispersion diagrams. It was used for a better correlation a 3D graphical analysis that followed the Ra variation of the mean arithmetic deviation of the machined surface profile under the influence of the cutting parameters and the independent variables respectively. The obtained conclusions led to the validation of the experimental model and the application of the research presented within an aerospace industry organization with important global valences.

WeUp: Wireless User Perception Based on Dimensional Reduction and Semi-Supervised Clustering

Wireless user perception (WeUP) is considered one of the most important factors in designing next-generation wireless communications systems. The recognition of WeUP involves lots of labor cost up to now. In order to solve this problem, this paper proposes an accuracy recognition algorithm for WeUP based on dimensional reduction and semi-supervised clustering. Usually, the WeUP is highly reflected in the key quality indicator (KQI). we build up a database of KQI including more than 1000 cells to train a deep belief autoencoder (DBA) for dimensional reduction (DR). Then we feed the historical unlabeled and manual-labeled negative data set after dimensional reduction into semi-supervised clustering model. After that, we find out a recognition range, which is the most similar to manual-labeled objects with unsatisfied WeUP. Simulation results show that our proposed method achieves an accurate recognition of unsatisfied WeUP over 93%.The study indicates that dimensional reduction and semi-supervised machine learning method is effective in recognizing unsatisfied WeUP in wireless networks.

COMBINATION OF DIAMOND-ELECTROCHEMICAL HONING AND GALVANIC CHROME-PLATING

For the English abstract and full text of the article please see the attached PDF-File (English version follows Russian version).ABSTRACT Electrochemical methods have found their greatest usefulness in the dimensional machining of surfaces of machine parts, based on complex processes of metal dissolution. The authors study the results of bench tribological tests of the results of application of the combined method of diamond electrochemical honing and galvanic chroming, creating high-strength surface layers, that showed the measure of intensity of wear, deviation from the optimum regimes, the causes and nature of emergence of coating defects. To fulfill the test conditions, appropriate equipment, technological equipment, tools were used, and an appropriate type of electrolyte medium was provided. The structure of the created equipment, in particular, included modernized vertical honing semi-automatic machines and mechanical devices. Based on the test results, the possibility of combining two methods of electrochemical metal surface treatment subject to high tribological load was confirmed. Keywords: machine parts, tribology, combined treatment, electrochemical processing, diamond electrochemical honing, galvanic chroming, wear, dimensional machining.

Technology of high-speed combined machining with brush electrode

The new method was proposed for high-precision dimensional machining with a brush electrode when the true position of bundles of metal wire is adjusted by means of creating controlled centrifugal forces appeared due to the increased frequency of rotation of a tool. There are the ultimate values of circumferential velocity at which the bundles are pressed against a machined area of a workpiece in a stable manner despite the profile of the machined surface and variable stock of the workpiece. The special aspects of design of processing procedures for finishing standard parts, including components of products with low rigidity, are disclosed. The methodology of calculation and selection of processing modes which allow one to produce high-precision details and to provide corresponding surface roughness required to perform finishing operations (including the preparation of a surface for metal deposition) is presented. The production experience concerned with the use of high-speed combined machining with an unshaped tool electrode in knowledge-intensive branches of the machine-building industry for different types of production is analyzed. It is shown that the implementation of high-speed dimensional machining with an unshaped brush electrode allows one to expand the field of use of the considered process due to the application of a multipurpose tool in the form of a metal brush, as well as to obtain stable results of finishing and to provide the opportunities for long-term operation of the equipment without its changeover and readjustment.

Achievement of required surface roughnesses in complex profile channels by dynamic combined processing

At present for processing of complex geometrical channels of workpieces electrochemical dimensional processing, vibro-impact machining and vibro-extruding are widely used. However combined electrochemical mechanical processing, that unites anodic dissolution and plastic flow of material in space and time, provides the required characteristics of surface layer. Local action anodic dissolution changes cold work amount and accelerates dissolution of micro- and macro-cusps, this causes annealing of physical and mechanical parameters in processed segments and accross the whole surface profile the required strengthening degree is attained. The authors examine annealing model for microsurface by grain displacement in channel where extrusion forcing is dictated by grains size and profile of narrow blade channel and also by actual processing conditions. Operating conditions that are recommended for implementation of combined electrochemical mechanical processing of impeller and turbine type workpieces are found by experiments. In consequence of field research they determined availability of standard microgeometry across the whole surface profile by combined processing with vibrations hashing with up to 2030 Hz frequency and low voltage current (in operation range from 1,2 till 1,8 V). Therein technological cycle decreases up to two fold, this reduces inadmissible jumping of blade edges and dimensional allowance.

Achievable tolerances in robotic feature machining operations using a low-cost hexapod

Portable robotic machine tools potentially allow feature machining processes to be brought to large parts in various industries, creating an opportunity for capital expenditure and operating cost reduction. However, robots lack the machining capability of conventional equipment, which ultimately results in dimensional errors in parts. This work showcases a low-cost hexapod-based robotic machine tool and presents experimental research conducted to investigate how the widely researched robotic machining challenges, e.g. structural dynamics and kinematics, translate to achievable tolerance ranges in real-world production to highlight currently feasible applications and provide a context for considering technology improvements. Machining trials assess the total dimensional errors in the final part over multiple geometries. A key finding is error variation which is in the sub-millimetre range, although, in some cases, upper tolerance limits < 100 μ m are achieved. Practical challenges are also noted. Most significantly, it is demonstrated that dimensional machining error is mainly systematic in nature and therefore that the total error can be dramatically reduced with in situ measurement and compensation. Potential is therefore found to achieve a flexible, high-performance robotic machining capability despite complex and diverse underlying scientific challenges. Overall, the work presented highlights achievable tolerances in low-cost robotic machining and opportunities for improvement, also providing a practical benchmark useful for process selection.

ИССЛЕДОВАНИЕ ПРОФИЛЯ ПРЕЦИЗИОННЫХ ОТВЕРСТИЙ, ПОЛУЧАЕМЫХ МЕТОДОМ ЭЛЕКТРОЭРОЗИОННОЙ ОБРАБОТКИ

During EDM holes of small diameter portions of the lower electrode-tool bits are exposed to the side longer than the upper, which leads to increased errors resulting form the opening. The article analyzes the profile obtained by EDM holes. It is found that the taper value increases with machining depth. Experiments confirmed the adequacy of the methodology for determining the value of additional calibration pass, using the ellipse function. The data will improve the accuracy of dimensional electrical discharge machining of small diameter holes.&#x0D;

Finite Element Analysis of Cutting Forces Generated in Turning Process using Deform 3D Software

Accurate and precise attempts were taken to study the affect of important machining variables on performance characteristics in turning of AISI H13 using ceramic tool. A three dimensional machining model using DEFORM 3D, a FEM based software were used for predicting the cutting forces, temperature etc by Langrangian model. The results obtained from simulation are compared with experimental results and are found in good accord. A novel model has been developed for the prediction of cutting forces based on cutting speed, feed and depth of cut and will be valid for turning of AISI H13 using ceramic tool. Apart from this simulation shows distribution of contact temperature, stress, strain and strain rate in tool and workpiece. These results may be useful for tool developers for complete understanding without performing costly and time consuming experimentation.

Optimization of arc ignition process for machines of arc dimensional machining

The article examines the arc ignition at the arc dimensional machining (ADM). The audit found that: − This process not paying attention in scientific literature. − Feed rate of the electrode-tool with no arc combustion is set non-optimal. The main aim of research is to optimize the process of electrode-tool feed rate at the arc ignition and, thus, reduce shock loads to the electrode-tool. The nature of the change of the working fluid pressure in the electric erosion chamber at arc ignition is given. The pressure value is experimentally determined at which the automatic change of the maximum rate to working is ensured by the system of automatic feed of the electrode-tool to the workpiece. A functional of optimal arc ignition process of arc dimensional machining is proposed. It is possible to determine the maximum permissible rate of electrode-tool feed and reduce the likelihood of tool failure during the arc ignition. Thus, during machining due to rapid electrode-tool feed in the machining area, the technological operation time is decreased. Research results can be used by designers that create an automatic system of electrode-tool feed at dimensional (ADM), arc (EAM), blasting (BEAM) and other related electric erosion methods of metal machining.

Performance of autonomous quantum thermal machines: Hilbert space dimension as a thermodynamical resource.

Multilevel autonomous quantum thermal machines are discussed. In particular, we explore the relationship between the size of the machine (captured by Hilbert space dimension) and the performance of the machine. Using the concepts of virtual qubits and virtual temperatures, we show that higher dimensional machines can outperform smaller ones. For instance, by considering refrigerators with more levels, lower temperatures can be achieved, as well as higher power. We discuss the optimal design for refrigerators of a given dimension. As a consequence we obtain a statement of the third law in terms of Hilbert space dimension: Reaching absolute zero temperature requires infinite dimension. These results demonstrate that Hilbert space dimension should be considered a thermodynamic resource.

An Approach to Generate Three Dimensional Machining Process Model According to Information from Design Model Based on Definition

Faced with the problem of generation for 3D machining process model, an approach to generate three dimensional machining process model according to information from design model based on definition is proposed. Compared with the existing methods, the approach utilizes multiple information of design model based on definition and takes many phases into consideration of 3D process model generation. The structure of 3D machining process model is defined and the course of 3D process model generation is researched, including multiple information acquirement, generation of procedure geometric models and annotation. Finally, the framework of system and application for 3D machining process model generation are presented for validation purposes.

Simulation and optimization of machining parameters in drilling of titanium alloys

The present study attempts to analyse the effect of various drilling parameters such as spindle speed, feed rate and drill bit diameter on performance characteristics such as thrust force, torque and circularity at entry and exit of the holes in drilling of titanium alloy using coated drill bit. A three dimensional machining model based on Lagrangian approach is developed using DEFORM-3D software. The performance characteristics obtained through simulation model is compared with experimental results. The simulation model closely agree with the experimental results as percentage relative error of 4.93, 9.01, 6.04 and 3.0 is observed for thrust, torque circularity at entry and circularity at exit respectively. The experimental data is used to develop valid empirical models to relate performance characteristics with drilling parameters using non-linear regression analysis. The empirical model helps to predict various performance characteristics without resorting to rigorous analysis through the numerical model. The values of various performance characteristics predicted from empirical models are compared with experimental results and the percentage relative error within 10% is observed. Finally, an improved version of latest evolutionary approach known as Harmony Search (HS) algorithm has been proposed to obtain favorable machining conditions through optimization of each performance characteristic. The optimal value of circularity at entry is obtained as 0.985 (approaching towards ideal value of one) when spindle speed, feed rate and drill bit diameter are set at 530.86 (≈531) RPM, 44.8 (≈45) mm/min and 7mm, respectively. Similarly, optimal value of circularity at exit reaches 0.979 with same spindle speed and drill bit diameter but feed rate of 50mm/min.

A study on the machining characteristics of specimens with spherical shape using laser-assisted machining

Materials such as nickel-based alloys have high strength and excellent resistance to many corrosive environments, and are widely used in various industrial fields, but are difficult to machine using conventional machining. To machine difficult-to-cut materials, thermally enhanced machining (TEM) has been developed internationally. One of the currently applied thermally enhanced machining methods, laser assisted machining (LAM), uses laser preheating to locally soften materials ahead of the cutting tool before machining. There have been no research works by LAM for three-dimensionally shaped specimens. Compared to a plate shape, it is more difficult to predict the optimum LAM preheating temperature for a three-dimensional shape, because with a 3D surface, the shape of the preheated spot changes continuously during machining. In this study, LAM was applied to spherical shaped specimens of three different materials, AISI 1045, Inconel 718 and titanium alloy for three dimensional machining. Before the machining experiments, thermal analysis was carried out by finite element analysis (FEA) to determine the optimum preheating temperature. A contouring machining method was used in the experiments. Cutting force and surface roughness were measured to analyze machining characteristics, and were found to be improved by LAM. These results can be applied to similar machining of difficult-to-cut materials.

Teaching of mechanical engineering concepts through three-dimensional geometric modeling

In the present pedagogical work, the importance of teaching mechanical engineering concepts using three-dimensional spatial visualization was emphasized and explained using specific examples. Elementary concepts of the mechanical engineering such as vortex flow, geometric and dimensional tolerances, orthographic projections, machine components, and hydraulic machinery were depicted in three dimensions, using a computer-aided geometric modeling software. The conventional schematic methods used to describe the mechanical engineering concepts were mapped into spatial three-dimensional geometric models. These three-dimensional geometric models bring clarity in understanding the complex engineering concepts in an accurate and precise way because of the ease in visualization. An improvement in students’ level of understanding is recorded through percentage marks obtained in the students’ performance in the classroom environment.

High temperature deformation mechanisms and constitutive modeling for Al/SiCp/45 metal matrix composites undergoing laser-assisted machining

The material removal mechanism in LAM of Al/SiCp composite. In the present study, material removal mechanisms were inferred from the analysis of the chip and chip root morphology at different cutting conditions, and the shear zone stress was determined by using three dimensional machining theory with a new approach to determining shear angles for saw-tooth chips formed in LAM of Al/SiCp composite. Based on the deformation mechanisms associated with LAM, a constitutive equation which predicted the shear zone stress was proposed, and the effects of operating conditions on the shear zone stress were determined from a systematic experimental study. A comparison of the constitutive equation predictions with the experimental results showed a smaller than the estimated uncertainty (15%) in the stress calculation.

Observed Intraseasonal and Interannual Variability of Arabian Sea Warm Pool along the Gulf of Aden to Strait of Malacca shipping Lane during 1951–2010

All the available historic surface marine meteorological data collected from Voluntary Observing Ships (VOS) in the tropical Indian Ocean during the period 1951–2010, archived by National Centre for Atmospheric Research, Boulder, Colorado, USA are assembled, quality controlled, processed and analyzed. Data for all the meteorological parameters stratified into 4° latitude by 1° longitude boxes, over five day durations, for all the 60 years are quality controlled, averaged and analyzed to portray the observed spatio-temporal evolution of all these parameters as Hovmoller diagrams for the Gulf of Aden to Strait of Malacca shipping lane. Two dimensional machine contouring is carried out with appropriate colour shading intensities to highlight the maxima and minima in the analyzed fields. The observed intraseasonal and interannual variability of these parameters is characterized along this shipping lane. These analyzed distributions amply highlight the observed variability of the surface meteorological parameters both on intraseasonal and interannual time scales during 1951–2010. Composites of SST and other marine meteorological parameters for strong and weak ASWP regimes, for strong and weak monsoon years, for El Nino (+1Y) and La Nina (+1Y) years and for Positive and Negative IOD (+1Y) years are presented.

A simulation approach for estimating flank wear and material removal rate in turning of Inconel 718

The present work attempts to study the effect of important machining variables on performance characteristics such as material removal rate and tool wear in turning of Inconel 718 using chemical vapour deposition (CVD) coated tungsten carbide (WC) tool. A three dimensional machining model using Lagrangian approach has been developed using DEFORM 3D. The machining simulation is carried out to predict the flank wear and material removal rate (MRR). Flank wear is calculated using Usui’s wear model in the simulation model. The results from simulation model are compared with experimental data generated by the use of Taguchi’s L16 orthogonal array for reducing the experimental runs. Analysis of variance (ANOVA) is performed to identify the most influencing variables for both the performance characteristics. It is found that simulation results are in good agreement with experimental results. A valid simulation models helps the tool engineers to gather relevant process related information without resorting to costly and time consuming experimentation.

Limit model of electrochemical dimensional machining of metals

The method of precision electrochemical machining is studied by using a model in which the current output has the form of a step function of current density. The problems of maximum stationary and quasistationary machining are formulated and solved, which made it possible to study the nonstationary process with sufficient accuracy.

An Integrated Geometric Modeling Methodology for 2.5D Cylindrical Prismatic Part for Computer Aided Process Planning

The field of solid modeling has created numerous techniques for unambiguous computer representations of three-dimensional objects. Its data structures and algorithms have been used in a broad range of applications: Computer-Aided Design and Computer-Aided Manufacturing (CAD/ CAM), robotics, computer vision, computer graphics and visualization, virtual reality, etc. This research paper is used to generate process plan from feature-based modeling, based on an integrated geometric modeling system that supports both feature-based modeling and information storage. Present system is developed only for milling components and limited to selective machining features for prismatic components and further implemented for more machining features to develop algorithms for modeling the components through the input of machining features. As a result, feature information is directly available to downstream activities, and feature extraction is no longer needed. The various systematic steps involved in this approach are study of Design, identification of Features, selection of Processes, Tools and Machines, Machining and Inspection [DFPTMMI]. Machining features generated in the design stage are recognized and stored under the Visual Basic control of CATIA software ActiveX interface. Algorithms are developed for individual features and these algorithms are embedded in Visual Basic forms. This system is discussed and suited for 2.5 Dimensional part approach, however, that can be extended to 3 dimensional prismatic part and complex features machining. Finally a process planning chart has been presented as a model process planning.

Variance inflation in high dimensional Support Vector Machines

Many important machine learning models, supervised and unsupervised, are based on simple Euclidean distance or orthogonal projection in a high dimensional feature space. When estimating such models from small training sets we face the problem that the span of the training data set input vectors is not the full input space. Hence, when applying the model to future data the model is effectively blind to the missed orthogonal subspace. This can lead to an inflated variance of hidden variables estimated in the training set and when the model is applied to test data we may find that the hidden variables follow a different probability law with less variance. While the problem and basic means to reconstruct and deflate are well understood in unsupervised learning, the case of supervised learning is less well understood. We here investigate the effect of variance inflation in supervised learning including the case of Support Vector Machines (SVMS) and we propose a non-parametric scheme to restore proper generalizability. We illustrate the algorithm and its ability to restore performance on a wide range of benchmark data sets.