Efficiency Of Machining Process Research Articles

The influences of alloying elements and processing conditions on the machinability of wrought aluminium alloys: A literature review

Today, wrought aluminium alloys are ranked among the most important materials with low specific density, strength features, corrosion resistance, machinability and recyclability properties in numerous application fields. Machining process of these alloys involves a number of considerations to ensure the highest quality and productivity. Key machinability issues include the rate of tool wear, workpiece surface finish and integrity and machining process sustainability. Understanding and optimising these parameters can lead to improving the machinability, better surface finish, longer tool life, and overall, more efficient and cost-effective machining processes for wrought aluminium alloys. The machining of wrought aluminium alloys remains a challenging task due to their unique characteristics, such as high strength, thermal conductivity and refined grain structures with mechanical and/or heat treatment. Although considerable progress has been made in the development of cutting tool materials and machining techniques for wrought aluminium alloys, further research is required to improve the machinability of these materials and reduce the associated costs and time needed for production. Having access to relevant information about these characteristics can help industries and researchers make informed decisions and achieve better outcomes when machining of these important materials. Accordingly, in the current research work, a comprehensive study has been carried out on machining of wrought aluminium from different points of view.

Tool chip contact length analysis of dry and cryogenic turning of aerospace alloy Ti-6Al-4V

Tool chip contact length is a vital machining index being representative of manufacturing efficiency. Various machining factors including tool wear and energy consumption are governed by tool chip contact length. The current work was undertaken to make a comparative analysis of dry and cryogenic turning of Ti-6Al-4V in terms of their sustainability and productivity indices. During experimentation, cutting speeds of 50 m/min and 125 m/min were selected working at feed rates ranging from 0.16 mm/rev to 0.24 mm/rev. Scanning electron microscopy was utilized to analyse the results. It was observed that machining under cryogenic conditions, in comparison with dry conditions, resulted in up to 51 % lower tool chip contact length. The results were also investigated in terms of chip formation for both machining environments. In addition, benefits of lower tool chip contact length were quantified in terms of lesser tool wear and better energy consumption. Tool chip contact length and chip formation analysis, indicative of the machining process efficiency, highlights that cryogenic condition is more sustainable and productive than dry conditions.

Energy efficiency identification and surface roughness prediction using cutting force signal for computer numerical controlled machine systems

The energy efficiency identification of machining process plays an indispensable part in achieving energy-efficient manufacturing and improving energy utilization as well as productivity and surface quality. However, there is a great difficulty to track energy efficiency in real-time based on one kind of traditional power signal. Because energy consumption is affected by many factors such as machine tool current performance, tool wear conditions and cutting parameters selection. This paper puts forward an energy efficiency recognition method as well as surface roughness prediction model based on the cutting force signals. The CEEMDAN (Complete Ensemble Empirical Mode Decomposition with Adaptive Noise) algorithm is employed to decompose the cutting force signal into multiple IMF (intrinsic mode function) components; and characterization of energy efficiency of machining process is recognized through proportion of components based on PCA—Fast ICA algorithm. Then, a surface roughness prediction model is proposed using support vector regression (SVR) based on specific cutting energy consumption (SCEC). The orthogonal test is designed considering spindle speed, feed rate, depth of cutting and width of cutting in 3 levels to obtain the influence degree of cutting parameters on cutting force, specific energy consumption, and the surface roughness. The energy efficiency of 27 group experiments is classified into high, medium and low levels according to energy efficiency value. Finally, using the data of orthogonal test, energy efficiency state was identified. The result show that time–frequency of cutting force signals for high, medium and low energy efficiency could be extracted, and the average absolute error of surface roughness predict is 0.058. That illustrated that the proposed method could meet the industry requirement for energy efficiency monitoring and surface roughness prediction to achieve sustainable manufacturing.

Multicriteria Optimisation of Machining Operations Using a Spreadsheet Model

The rapid development of new materials and tools demonstrates the need for efficient and feasible machining processes. Modern production systems must guarantee sustainable, flexible, productive and high-quality production at low cost. Therefore, the combination of technological data with advanced software solutions is very important, especially when using complex CNC machining systems, where the reliability of the technological information is crucial, as simple measures can make a very positive contribution to the productivity achieved. When optimising the machining parameters, costs and machining time must be taken into account. The article deals with the optimisation of the turning process with a large number of influencing variables (machine, workpiece material, tool, cutting parameters, costs, etc.) and two objectives: the fastest possible machining (minimisation of machining time) and the lowest possible machining costs. The model is designed in an Excel spreadsheet and the multi-criteria optimisation is carried out using the approximation method. Step by step, we can find the optimal processing regime for each selected case.

Ductile-brittle transition mechanism of SiC particle-reinforced Al-MMCs under ultrasonic assisted grinding with single grain

High volume fraction (45 %) silicon carbide particle-reinforced Al matrix composites (SiCp/Al-MMCs) play an important role in various engineering fields due to their excellent properties, but the high hardness and brittleness of the SiC reinforcements result in poor surface integrity during conventional grinding (CG). Ultrasonic assisted grinding (UAG) is an efficient machining process to improve the quality of finished surface for hard-brittle materials. In this study, comparison tests between UAG and CG with single grain were designed and the grinding force, specific grinding energy, material removal rate, surface and subsurface morphology, and the ductile-brittle transition mechanism of SiC particle were investigated. The results showed that ultrasonic vibration can increase the critical depth of ductile-brittle transition for SiC particles, making it easier to realize the micro brittle fracture and effectively reduce the surface and subsurface damage of SiCp/Al composites.

A novel method based on deep reinforcement learning for machining process route planning

Efficient and high-quality machining process route planning is crucial in the realm of manufacturing. Traditional methods heavily rely on human-computer interaction, which can be inefficient. To enhance the efficiency of machining process route planning, this paper introduces a novel framework based on deep reinforcement learning (DRL), designed to automatically generate machining process routes for designated parts. The framework treats machining process route planning as a Markov decision process, making it amenable to DRL techniques. For effective representations of parts, the framework utilizes directed attributed adjacency graphs, wherein nodes represent machining features and edges represent their relationships. To effectively process the graphs, convolutional graph neural networks are employed as the underlying neural networks in the framework. After training, the framework is able to generate efficient machining process routes while adhering to machining process rules. Experimental studies conducted on a number of aircraft structural parts serve as examples to show the feasibility and effectiveness of the proposed approach. The experimental results underscore the effectiveness of the proposed method in machining processes planning for parts and its ability to overcome limitations in traditional methods. As a result, this study contributes to the enhancement of process planning efficiency within the manufacturing domain, carrying practical implications.

Dosage Based Directional Minimum Quantity Fluid Application in Machining

There is an ever-increasing focus on surface integrity and machined surface quality of the machined surface and sub-surface to improve product quality, thereby improving its service life and sustainability. Machined sub-surface quality is influenced by the cutting tool system, cutting conditions and the cutting fluid system. However, past work on the influence of cutting fluid application, especially targeted application of minimal quantity fluid (MQF; varying minimum quantity of coolant and lubricant) which has never been addressed on surface integrity, is limited or non-existent. Thus, an experimental study involving face turning of AISI 1045 steel with flat-faced uncoated carbide tool was conducted with different cutting fluid combinations and at varied locations in the tool–workpiece space. This study is aimed to address machining performance effects (tool–chip contact area, cutting forces, etc.) and machining induced surface integrity (surface roughness and residual stresses). Results showed that the coolant application on the tool flank face improved the surface integrity. In addition, results emphasized the importance of targeted MQF on surface integrity and cutting tool performance, thus providing a cleaner and more efficient machining process.

Brittle-to-ductile transition in nanoscratching of silicon and gallium arsenide using Berkovich and Conical tips

Determining the brittle-to-ductile transition (BDT) threshold is crucial for developing efficient machining processes for brittle materials. In this study, nanoscratch tests were performed on the (001) face of single-crystal silicon (Si) and gallium arsenide (GaAs) using a sharp Berkovich and a blunt Conical tip. The aim was to understand the effects of tip shape and microstructural variation on their BDT behaviour. The result showed that the critical cutting depth for BDT (dc) was affected by not only material microstructure but also tip shape. The stress distribution within the deformed sublayer varied with tip shape, ultimately impacting the microstructure evolution and thus deformation/removal mechanism. Using the sharp tip, Si had a slightly smaller dc than GaAs due to the ease of cracking along the {111} plane. In contrast, with the blunt tip GaAs had a smaller dc than Si, attributed to its relatively high brittleness index and higher density of crystallite defects. The defects in GaAs caused strain hardening and hence reduced ductility, while the amorphization of Si enhanced its ductility.

PREDICTION OF NANO-COATED TOOL WEAR USING BAT AND WHALE OPTIMIZATION ALGORITHMS

In the industrial machining process, there have been major advances in near-net-shaped forming, which leads machining to be considered a significant modern phenomenon. Machining turns a huge number of metals into chips every year. This study aimed to determine the wear and mechanical properties of various cutting inserts. Polycrystalline diamond (PCD) and Ceramic Inserts were selected as coated inserts. It was discovered that tool wear at the cutting edge impacts various factors, including the amount of cutting forces created during machining; the surface finish of the workpiece is also compromised, resulting in reduced tool life. Owing to the frequent replacement of cutting tools, the decreased wear rate of cutting tools exponentially raises the costs that companies/machine shops would incur. After the second iteration, this insert began to develop crater wear, which resulted in a poor surface finish and high heat generation. However, the surface finish of this instrument was discovered to be the best during the first iteration. From the outcome, the PCD coated tool with feed speeds and low depth of cuts performed the efficient machining process. The surface finish is also accurate for PCD coated tool. The bat and whale algorithms’ optimization involved to find the best technical parameters to achieve the lowest possible error value based on rake and face wear. The bat and whale algorithms were used to determine the optimized rake and face wear values. The bat algorithm outperforms the whale algorithm in terms of wear value predictions.

Influence of the cutting force upon machining process efficiency

The present paper has as main objective to highlight the influence of the cutting force, which is directly connected to the energy consumption, upon machining process efficiency. In this respect, it is developed an experimental research performed by the means of a turning process, using different cutting parameters. An experimental frame composed from: a longitudinal lathe, carbide cutting tools, steel pieces and the device for measuring the cutting force, which is a dynamometer was designed to measure the cutting forces during the turning process. The data collected were analyzed by the means of a statistical software package, in order to study the influence of the cutting force upon the energy consumption. The results indicated the conditions for reducing the energy consumption, without affecting the product quality nor the process productivity. In order to reduce the energy consumption and the energy costs the cutting force must be reduced. A solution is to reduce the depth of cut and to increase the feed rate, without negatively affecting the cutting process productivity. Another important aspect to be considered in energy consumption reduction is to reduce the cutting speed and to proportionally increase the depth of cut and the feed rate, in order to maintain the cutting process productivity.

Synthesis and polishing characteristics of a novel green GO/diamond hybrid slurry under ultrasonic technology

Ultrasonic polishing (UP), as an efficient and clean precision machining process, is increasingly applied in the hard and brittle material processing. To minimize the surface damage and polishing expenses, this paper aims to prepare novel graphene oxide/diamond hybrid slurries (GDS) by ultrasonication, and to investigate the UP mechanisms for silicon carbide (SiC) ceramics on UP and tribological experiments. Findings showed that GDS exhibited superior polishing performance compared to diamond polishing slurries. Moreover, the promotion effect of GDS was more obvious under UP. The surface roughness was improved by 31.62% after UP using GDS with a graphene oxide (GO) content of 0.1 wt%. On the one hand, the lubrication of GO reduce the wear and coefficient of friction. On the other hand, ultrasonic vibration induces stronger impact kinetic energy of abrasives to remove material and allows for a better uniform distribution of GDS to further enhance the lubrication characteristics of GO nanosheets. The application of GO in UP is a processing technology penetrating the manufacturing industry and even human life, laying the foundation for SiC nano-polishing.

Machining feasibility and Sustainability study associated with air pressure, air flow rate, and nanoparticle concentration in Nanofluid minimum quantity lubrication-assisted hard milling process of 60Si2Mn steel

In recent years, more efficient hard machining processes have notably increased in demand for higher productivity but environmental friendliness. High hardness and strength as well as the enormous amount of cutting temperature are still the biggest obstacles. Nanofluid minimum quantity lubrication (NFMQL)–assisted hard machining has become a feasible and promising solution to overcome these problems. The work presents the experimental study on the effects of air pressure (5, 6, and 7 bar), air flow rate (150, 200, and 250 L/min), and Al2O3 nanoparticle concentration (0.5, 1.0, and 1.5%) on minimum quantity lubrication (MQL) hard milling process of 60Si2Mn (50÷52HRC) using vegetable oil as the based fluid. Box–Behnken experimental design and ANOVA analysis were employed to investigate the influences and interaction effects of input parameters on cutting forces, surface roughness, and surface microstructure. This study will be used for selecting the optimum air pressure, air flow rate, and Al2O3 nanoparticle concentration for efficient cooling lubrication performance of MQL in sustainable hard machining. The obtained results show that the optimal values for air pressure and nanoparticle concentration. For Q = 200 L/min, the optimal p is 6.0 bar and the optimal nanoparticle concentration (NC) is 0.9%. For Q = 250 L/min, the optimal p is 5.2 bar, and the optimal NC is 1.2%. Furthermore, using air flow rate Q = 250 L/min gives better results than Q = 200 L/min, but the selection will be depended on the specific equipment conditions.

An Investigation on Cut Quality of Aluminum Matrix Composites Cut by Abrasive Waterjet

Abstract: Metal matrix composites are difficult to machine in traditional machining methods. Abrasive water jet machining is a state-of-the art technology which enables machining of practically all engineering materials. Abrasive water jet machining is a very efficient machining process which overcomes tool wear issues and cutting temperature issues. This experimental investigates a particular study performed on hybrid metal matrix composites prepared by AA6082 and reinforced 7.5% of TiB2 and 1% graphite in aluminum alloy and processed with abrasive water jets that are formed with garnet 80 mesh size. Particularly roughness average majorly influences with water jet traverse speed. Among interaction effects stand of distance is majorly influenced with geometrical properties except diameter error. Although developing the statistical models for predicting the machining characteristics and geometrical accuracy and the study carried out in this work would help to choose the parameters carefully. Keywords: Abrasive Waterjet Cutting, Abrasives, Metal Matrix Composites, Sand Casting

Tribological Properties and 3D Topographic Parameters of Hard Turned and Ground Surfaces.

Precision machining of automotive industrial parts is a highlighted topic in mechanical engineering due to the increased need for efficient and high-quality machining processes. This study is aimed to contribute to the field of surface topography evaluation by analyzing tribology-related topography parameters parallelly and finding connections between them. Hard machining experiments were carried out for the widely applied case-hardened material 16MnCr5 and the 3D topography of the machined surfaces was measured and analyzed. Based on a comprehensive design of experiments cubic response functions were determined for the analyzed parameters and the coefficients of determination were calculated. It was found that the cubic response function is reliable for predicting the topography parameter values and there are strong relationships between counterpart parameters under certain circumstances The findings could help clarify the roles of the analyzed parameters in some tribological properties within the analyzed cutting circumstances.

A novel correction method to attain even grinding allowance in CNC gear skiving process

Power skiving is currently an efficient machining process to manufacture gears. In practical applications, uneven gear profile deviations caused by the asymmetric cutting edge of a skiving cutter affect gear profile accuracy and finishing cost. Therefore, this paper proposes a novel method to attain the even grinding allowance on both gear flanks in the CNC skiving. A quadratic polynomial function is adopted to correct an asymmetric rack profile, which is used to generate the skiving cutter profile. Pressure angles, protuberances, and polynomial coefficients on two sides of the rack are determined analytically according to the requisite grinding allowance and the conjugation relationship between the gear and the cutter. Skived tooth profiles for internal/external gears are simulated based on the CNC machine motion, and its normal deviation can be estimated. As the numerical results demonstrate, the profile deviations on both gear flanks are close to the required settings, and the even grinding allowance is achieved on the active involute sections. Additionally, a radial basis function (RBF) regression model is constructed to conveniently determine the design parameters of the skiving cutter.

A systematic method of optimization of machining parameters considering energy consumption, machining time, and surface roughness with experimental analysis

For improving energy efficiency of machining process, extensive studies focused on how to establish energy consumption model and optimize cutting parameters. However, the existing methods lack a systematic method to promote the widespread use of energy efficiency methods in industry. This paper proposes a systematic method integrating energy model, experiment design, and multi-objective optimization model. Firstly, the energy model is established considering cutting energy and non-cutting energy. Then, the orthogonal experiment is designed with the three levels of four factors of spindle speed, feed speed, cutting depth, and cutting width in the X and Y cutting directions. The data of energy consumption, surface quality, and machining time are obtained to study the effects of different cutting elements and cutting directions. Meanwhile, the standby, spindle idling, feed, SEC (specific energy consumption), material cutting, and idling feed models of the CNC machine tools are established based on the experimental data. Additionally, five sets of experimental data are tested for verifying the accuracy of the established energy consumption model, which can reach 99.4%. Finally, a multi-objective optimization model for high efficiency and energy saving of processing process is established to optimize the cutting parameters considering energy consumption, processing time, and surface quality simultaneously. Combining the case of milling with constraints including machine tool performance, tool life, processing procedures, and processing requirements, the Pareto solution set is used to solve the Pareto of the target model. Through drawing a three-dimensional needle graph and two-dimensional histogram, the optimal cutting parameter combination for rough machining and semi-finish machining is provided assisting in promoting the application of the sustainable techniques in the industry.

Study on surface integrity of titanium alloy machined by electrical discharge-assisted milling

• Electrical discharge-assisted milling (EDAM) can improve the surface integrity of Ti-4Al-6 V. • EDAM can reduce the surface roughness compared with conventional milling (CM). • Compared with CM, the residual tensile stress generated by EDAM is smaller. • The microhardness of machined surface after EDAM is relatively smaller than CM. • Moderate capacitance has more positive influence for surface integrity. Electrical discharge-assisted milling (EDAM) is an efficient machining process for titanium alloys according to previous studies. However, a complete understanding of the surface integrity of titanium alloy machined with EDAM is not yet sufficient. Therefore, in this paper, surface defects such as chip layer adhesion, debris, feed marks, and burrs were investigated and identified. Among them, the adhesion of the chip layer is the most common surface defect and is the factor that has the greatest influence on the surface quality. In addition, surface roughness, micro-hardness, and residual stress were analyzed and discussed. The results show that the surface roughness of EDAM is significantly improved compared to conventional milling (CM). Also, the residual stress generated by EDAM is much smaller than that of CM, and the main type of residual stress is residual compressive stress. Similarly, the surface microhardness after EDAM is also slightly smaller than that of CM. This increased surface integrity is due to the material softening effect due to the heat generated by the discharge spark. Consequently, EDAM is a good candidate method for efficient machining of titanium alloys.

Comparison between milling roughing operations in full slotting manufacturing: trochoidal, plunge and conventional milling

Manufacturing improvements in terms of manufacturing-chain costs and times reduction are becoming a real need in the industry, especially for roughing operations. To satisfy these industrial requirements, more efficient machining processes have been developed, such as High Efficiency Milling (HEM). According to the above mentioned direction, trochoidal milling appears as an efficient method for roughing operations of full slots. This work presents an analysis in terms of production time between conventional, plunge and trochoidal milling to determine which process configuration is more productive.

Preface

The Proceedings of the 4th International Conference on Aeronautical, Aerospace and Mechanical Engineering (AAME 2021) contain the scholarly papers presented during a virtual conference on 26-28 February, 2021. The designated physical conference venue was Sanya, China. The AAME series of conferences have been held in different parts of the world for the last three years already. This year (2021), due to COVID-19 restrictions, the conference was held online.The AAME 20201 conference has attracted more than 30 participants from renowned universities in Australia, Japan, Singapore, Russia, Egypt, South Africa, Malaysia and China. Together with the assistance of the International Technical Committee, which is formed by members from universities and research organisations around the world, the conference attracted many submissions of high quality papers. The papers accepted in these proceedings have passed the vigorous review process and amended to the satisfaction of reviewers. The online conference serves to provide the opportunity for the audience to raise critiques and comments on the presentations. It is on this basis that these proceedings are good references to future research investigations and publications.The proceedings have Six sections. Each section has 5 to 8 papers related to a topic. Section 1 and 2 (Mechanical Design and Manufacturing Technology) has 10 papers in total on machine tools, special products 3D printing and new processes. Study of materials properties is essential to develop efficient machining and formation processes for cost effective manufacturing. The 10 papers cover broad industrial level research to improve effectiveness and efficiency of manufacturing.Section 3 (Power Machinery and Engineering) has 6 papers focusing on mechanical power applications. The broad application areas in machinery and its design are highlighted in the short conference version of the papers. Authors have applied relevant computational and experimental analysis techniques demonstrating close relationship between theory and practice.Section 4 (Modern Electronics and Information Engineering) has 6 papers related to more fundamental treatment of aerodynamics, acoustics, heating and cooling phenomena. These studies have many immediately viable industry applications in aircraft electronics, satellite operations, noise control and so on. The papers have presented valuable experimental data supporting future electronic and information engineering in aeronautics and astronautics scientific fields.Section 5 (Supersonic Flow and Fluid Mechanics) has 5 papers on mechanics and properties of polymer materials and their applications to space vehicles, aircraft structures, high flow environment. Computational approaches such as computational fluid dynamics, finite element analysis, large body simulation are used to analyse some of the most complex microstructures in the materials thereby contributing to knowledge in the fields of liquid and applied mechanics.Section 6 (Aerospace Science and Transportation Engineering) has 8 papers closely related to aircraft design, airline operations, flight control. These researches have advanced understanding of their respective engineering disciplines and in many respects, fill the gap of understanding of the aerospace systems so as to improve their reliability and quality.The variety of research topics presented in the AAME 2021 conference and novelty exhibited in the papers published in these proceedings once again demonstrated the value of the online conference enabling researchers of different nationalities and different engineering fields to participate in a live research conversation. I would like to thank the conference committee, the conference secretariat, keynote speakers and all participants for their hard work making the AAME 2021 conference a success as well as publishing a valuable knowledge literature contributing to state-of-the-art developments in aeronautical, aerospace and mechanical engineering.John P.T. MoProfessor of Manufacturing EngineeringBSc(Engg), MSc(Engg), PhD(Loughborough), FIEAust CPEng NER APEC Engineer IntPE(Aus),CEng, FIMechE, MHKIE, MFIESchool of EngineeringRMIT UniversityEmail: john.mo@rmit.edu.auMarch 2021, Melbourne, AustraliaList of Conference Committees are available in this pdf.

Tribological performance based machinability investigations in cryogenic cooling assisted turning of α-β titanium Alloy

Machining of titanium is considered as a challenging process due to its ability to interact with various tool materials when critical cutting temperature is exceeded, resulting in excessive tool wear and poor surface finish, etc. To exhibit an efficient machining process, this research study has experimentally investigated the key quality indicators of machinability, namely surface roughness, cutting temperature, tool wear, in-depth analysis of worn tool and cutting force in the machining process of α-β titanium alloy, which used in critical applications, under three sustainable cooling environments i.e., dry, liquid nitrogen (LN2) and carbon dioxide (CO2). The effect of cutting speed and feed rate on such performance measures were examined under a function of cooling strategy as the best substitute in machining. As a result, the feasibility of LN2 cooling has been confirmed to be more significant for the machining of α-β titanium alloy when compared to dry and CO2 machining strategies. To sum up, cryogenic cooling (LN2 cooling) assisted machining of α-β titanium has acquiesced as a sustainable strategy in the context of environmental consciousness.