An experimental and simulation study on parametric analysis in turning of inconel 718 and GFRP composite using coated and uncoated tools

Process simulation is one of the important aspects in any manufacturing/production context because it generates the scenarios to gain insight into process performance in reasonable time and cost. With upcoming worldwide applications of Inconel 718 and Glass Fiber Reinforced Polymer (GFRP) composites, machining has become an important issue which needs to be investigated in detail. In turning of hard materials (such as Inconel 718), cutting tool environment features high-localized temperatures (~1000ºC) and high stress (~700 MPa) due to contact between cutting tool and work piece. The tool may experience repeated impact loads during interrupted cuts and the work piece chips may chemically interact with the tool materials. Therefore, the use of coated tool is preferred for turning of Inconel 718. It is observed that performance of machining process is influenced by different machining parameters such as spindle speed, depth of cut and feed rate as in case of turning. Material removal rate (MRR) and flank wear in turning of Inconel 718 using physical vapour deposition (PVD) and chemical vapour deposition (CVD) coated on carbide insert tool are reported. A simulation model based on finite element approach is proposed using DEFORM 3D software. The simulation results are validated with experimental results. The results indicate that simulation model can be effectively used to predict the flank wear and MRR in turning of Inconel 718. For simultaneous optimization of multiple responses, a fuzzy inference system (FIS) is used to convert multiple responses into a single equivalent response so that uncertainty and fuzziness in data can be addressed in an effective manner. The single response characteristics so generated is known as Multi Performance characteristic Index (MPCI). A non-linear empirical model has been developed using regression analysis between MPCI and process parameters. The optimal process parameters are obtained by a recent population-based optimization method known as imperialistic competitive algorithm (ICA). Analysis of variance (ANOVA) is performed to identify the most influencing factors for all the performance characteristics. The optimal conditions of process parameters during turning of Inconel 718 and GFRP composites are reported. It is observed that flank wear is combatively less when machined with PVD coated tool than CVD coated tool in turning of both Inconel 718 and GFRP composite

Experimental investigation and modeling of hot machining operation using high-strength material

High strength work materials have tremendous applications in the field of aerospace, nuclear, biomedical, automotive, etc. It is a challenging task to machine these high strength materials. Costly cutting tools are required to machine those materials. Hot machining is another alternative approach for hot machining those hard material using low cost cutting tools. Basic concept behind the hot machining is to soften the material by heating technique which reduces the shear strength of the workpiece as well as reduces the forces required to machine the workpiece at the time of machining. In the present investigation, experimental investigation of hot machining operation has been carried out using flame heating for machining high manganese steel using ordinary carbide insert. Hot machining operation has been investigated to study the advantages of hot machining operation over conventional machining operation. Tool wear, surface roughness, chip reduction coefficient, tool life and power consumption have been measured as per the design of response surface methodology technique. This technique has been used to determine the optimum conditions for the desired responses (minimum tool wear, minimum surface roughness, minimum chip reduction coefficient, minimum power consumption and maximum tool life). Principal component analysis (PCA) coupled with Grey relational analysis (GRA) and weighted principal component analysis (WPCA) have been used for optimizing the multi-performance characteristics. WPCA has been proved to provide better results as compared to PCA coupled with GRA with the help of confirmatory test. Fuzzy TOPSIS approach has been used for optimizing performance characteristics namely, tool life and power consumption. It has been proved that Fuzzy TOPSIS is an alternative approach for practical based problems using the decisions that have been taken by decision maker based on experience and skill. FEM modelling has been carried out to determine temperature at the chip/tool interface and validated by experimental results

Miniaturised experimental simulation of ingot-to-billet conversion

Ingot-to-billet conversion processing, one process of which is known as “cogging”, is an important production step in high-value metallurgical manufacturing. It is necessary to homogenise and refine the microstructure of high-performance alloys before they proceed to subsequent processing stages. Despite its importance, the process is still not very well understood for many modern advanced alloys and few published studies exist. The limited knowledge of the deformation and microstructure evolution leads to difficulties in achieving the desired accuracy in microstructural control. Traditional uni-axial testing is not fully representative of the forging processes seen in industry, and does not capture different elements of open-die forging parameters. Given significant costs of large multi-tonne workpiece ingots and the difficulties with their non-destructive evaluation, it is crucial to develop a laboratory-scale evaluation for the cogging process so that scrapping and re-processing can be avoided. The “Micro Future Forge” has been developed as a reproducible laboratory-scale experimental method for exploring the various thermo-mechanical process mechanisms of hot open die forging. This novel methodology employs a purpose-built apparatus, that has been designed to be cost-effective and portable. The test set-up uses a remotely operated manipulator assembly constructed predominantly from standard off-the-shelf components in conjunction with a conventional uni-axial load frame. This combination allows for high operational scalability. Multi-directional open-die forging (cogging) of single and dual-phase alloys has been successfully accomplished using the described apparatus, demonstrating an ability to attain the desired beneficial refinement of the microstructure. Application of this experimental approach provides precisely controlled conditions and allows high research specimen throughput to discover new insights into the structural transformations that occur in industry-scale forgings, while offering savings in energy, material, time and capital investment. The obtained experimental data can be used for thermo-mechanical process optimisation of high-performance alloys, guiding larger scale testing and manufacturing trials (e.g., AFRC Catapult Future Forge), as well as informing the development of digital-twins for various high-value metallurgical manufacturing processes.Ingot-to-billet conversion processing, one process of which is known as “cogging”, is an important production step in high-value metallurgical manufacturing. It is necessary to homogenise and refine the microstructure of high-performance alloys before they proceed to subsequent processing stages. Despite its importance, the process is still not very well understood for many modern advanced alloys and few published studies exist. The limited knowledge of the deformation and microstructure evolution leads to difficulties in achieving the desired accuracy in microstructural control. Traditional uni-axial testing is not fully representative of the forging processes seen in industry, and does not capture different elements of open-die forging parameters. Given significant costs of large multi-tonne workpiece ingots and the difficulties with their non-destructive evaluation, it is crucial to develop a laboratory-scale evaluation for the cogging process so that scrapping and re-processing can be avoided. The “Micro Future Forge” has been developed as a reproducible laboratory-scale experimental method for exploring the various thermo-mechanical process mechanisms of hot open die forging. This novel methodology employs a purpose-built apparatus, that has been designed to be cost-effective and portable. The test set-up uses a remotely operated manipulator assembly constructed predominantly from standard off-the-shelf components in conjunction with a conventional uni-axial load frame. This combination allows for high operational scalability. Multi-directional open-die forging (cogging) of single and dual-phase alloys has been successfully accomplished using the described apparatus, demonstrating an ability to attain the desired beneficial refinement of the microstructure. Application of this experimental approach provides precisely controlled conditions and allows high research specimen throughput to discover new insights into the structural transformations that occur in industry-scale forgings, while offering savings in energy, material, time and capital investment. The obtained experimental data can be used for thermo-mechanical process optimisation of high-performance alloys, guiding larger scale testing and manufacturing trials (e.g., AFRC Catapult Future Forge), as well as informing the development of digital-twins for various high-value metallurgical manufacturing processes

Ultra-high precision machining of rapidly solidified aluminium (RSA) alloys for optics

The advancement of ultra-precision is one of the most adaptable machining processes in the manufacturing of very complex and high-quality surface structures for optics, industrial, medical, aerospace and communication applications. Studies have shown that single-point diamond turning has an outstanding ability to machine high-quality optical components at a nanometric scale. However, in a responsive cutting process, the nanometric machinability of these optical components can easily be affected by several factors. The call for increasing needs of optical systems has recently led to the development of newly modified aluminium grades of non-ferrous alloys characterized by finer microstructures, defined mechanical and physical properties. To date, there has been a lack of sufficient research into these new aluminium alloys. In modern ultra-precision machining, the high demands for smart and inexpensive cutting tools are becoming more relevant in recent precision machines. In monitoring and predicting high-quality surface, cutting forces in single point diamond turning are believed to be as critical as other machining processes due to their potential effects on the quality of surface roughness. Undermining such an important factor is a compromise between the machining process's efficiency and the increased cost of production. Therefore, a comprehensive scientific understanding of the Nano-cutting mechanics is critical, particularly on modelling and analysis of cutting force, surface roughness, chip vii formation, acoustic emission, material removal rates, and molecular dynamic simulation of the rapidly solidified aluminium alloys to bridge the gap between fundamentals and industrial-scale application. The study is divided into three essential sections. First, the development of a force sensor. Secondly, investigation of the effect of cutting parameters (i.e., cutting speed, feed rate, and cutting depth) on cutting force, acoustic emission (AE), material removal rate (MRR), chip formation, Nose radius, and surface roughness (Ra), which play a leading role in the determination of machine productivity and efficiency of single-point diamond turning of rapidly solidified aluminium alloys. Thirdly, a 3-D molecular dynamic (MD) simulation of RSA 6061 is also carried out to further understand the nanometric mechanism and characterization of the alloy. The experiment was mainly conducted using Precitech Nanoform ultra-grind 250 lathe machines on three different advanced optical aluminium alloys materials; these are RSA 443, RSA 905, and RSA 6061.Thesis (PhD) -- Faculty of Engineering, the Built Environment and Information Technology, School of Engineering, 202

Ultra-high precision machining of rapidly solidified aluminium (RSA) alloys for optics

The advancement of ultra-precision is one of the most adaptable machining processes in the manufacturing of very complex and high-quality surface structures for optics, industrial, medical, aerospace and communication applications. Studies have shown that single-point diamond turning has an outstanding ability to machine high-quality optical components at a nanometric scale. However, in a responsive cutting process, the nanometric machinability of these optical components can easily be affected by several factors. The call for increasing needs of optical systems has recently led to the development of newly modified aluminium grades of non-ferrous alloys characterized by finer microstructures, defined mechanical and physical properties. To date, there has been a lack of sufficient research into these new aluminium alloys. In modern ultra-precision machining, the high demands for smart and inexpensive cutting tools are becoming more relevant in recent precision machines. In monitoring and predicting high-quality surface, cutting forces in single point diamond turning are believed to be as critical as other machining processes due to their potential effects on the quality of surface roughness. Undermining such an important factor is a compromise between the machining process's efficiency and the increased cost of production. Therefore, a comprehensive scientific understanding of the Nano-cutting mechanics is critical, particularly on modelling and analysis of cutting force, surface roughness, chip vii formation, acoustic emission, material removal rates, and molecular dynamic simulation of the rapidly solidified aluminium alloys to bridge the gap between fundamentals and industrial-scale application. The study is divided into three essential sections. First, the development of a force sensor. Secondly, investigation of the effect of cutting parameters (i.e., cutting speed, feed rate, and cutting depth) on cutting force, acoustic emission (AE), material removal rate (MRR), chip formation, Nose radius, and surface roughness (Ra), which play a leading role in the determination of machine productivity and efficiency of single-point diamond turning of rapidly solidified aluminium alloys. Thirdly, a 3-D molecular dynamic (MD) simulation of RSA 6061 is also carried out to further understand the nanometric mechanism and characterization of the alloy. The experiment was mainly conducted using Precitech Nanoform ultra-grind 250 lathe machines on three different advanced optical aluminium alloys materials; these are RSA 443, RSA 905, and RSA 6061.Thesis (PhD) -- Faculty of Engineering, the Built Environment and Information Technology, School of Engineering, 202

Electron Beam Weld Shape Prediction Based on Electron Beam Probing Technology

Electron beam welding (EBW) is a joining process that has been widely applied in many modern industrial sectors. However, in order to achieve a satisfactory welding quality for a given material and configuration, a trial-and-error approach is usually adopted before moving to the final production. This procedure is often wasteful, time consuming and expensive when the raw material is at high cost, and greatly relies on the operators’ personal experience. To enable a ‘smarter’ welding process and reduce the inconsistent human factor, this PhD study is to develop a novel method based on statistic modelling, numerical modelling and artificial neural networks to predict the weld profile, which is the main criterion for assessing the welding quality. The models are set up with electron beam characteristics collected through a 4-slits technology to determine the actual focal spot size and power density, therefore the uncertainty caused by beam variation can be reduced. Multi-influences caused by electron beam, machine parameters and process environment are considered, and the predictions cover a wide range of linear beam power ranging from 86 J/mm to 324 J/mm. Finally, a novel simulation tool for predicting electron beam weld shape has been developed with assistance of a 4-slits beam probing technology to reduce the amount of manual work traditionally needed to achieve high-efficiency and high-quality welding joints. Validated by experimental results, the model is able to predict the weld profile with high accuracy and reliability for both partially and fully penetrated welding situations. By combining the numerical model and artificial intelligence, a weld-profile prediction system is to be integrated in current EB welding machines to allow a less-experienced operator to achieve high welding quality

The selected laser melting production and subsequent post-processing of Ti-6Al-4V prosthetic acetabular

&nbsp;Processing and post processing of human prosthetic acetabular cup by using 3D printing. The results showed using 3D printers leads to fabrication customized implants with higher quality.<br /