Prediction of welding responses using AI approach : adaptive neuro-fuzzy inference system and genetic programming

Laser welding of thin sheets has widespread application in various fields such as battery manufacturing, automobiles, aviation, electronics circuits and medical sciences. Hence, it is very essential to develop a predictive model using artificial intelligence in order to achieve high-quality weldments in an economical manner. In the present study, two advanced artificial intelligence techniques, namely adaptive neuro-fuzzy inference system (ANFIS) and multi-gene genetic programming (MGGP), were implemented to predict the welding responses such as heat-affected zone, surface roughness and welding strength during joining of thin sheets using Nd:YAG laser. The study attempts to develop an appropriate predictive model for the welding process. In the proposed methodology, 70% of the experimental data constitutes the training set whereas remaining 30% data is used as testing set. The results of this study indicated that the root-mean-square error (RMSE) of tested data set ranges between 7 and 16% for MGGP model, while RMSE for testing data set lies 18–35% for ANFIS model. The study indicates that the MGGP predicts the welding responses in a superior manner in laser welding process and can be applied for accurate prediction of performance measures

Remanufacturing and Advanced Machining Processes for New Materials and Components

"Remanufacturing and Advanced Machining Processes for Materials and Components presents current and emerging techniques for machining of new materials and restoration of components, as well as surface engineering methods aimed at prolonging the life of industrial systems. It examines contemporary machining processes for new materials, methods of protection and restoration of components, and smart machining processes. • Details a variety of advanced machining processes, new materials joining techniques, and methods to increase machining accuracy • Presents innovative methods for protection and restoration of components primarily from the perspective of remanufacturing and protective surface engineering • Discusses smart machining processes, including computer-integrated manufacturing and rapid prototyping, and smart materials • Provides a comprehensive summary of state-of-the-art in every section and a description of manufacturing methods • Describes the applications in recovery and enhancing purposes and identifies contemporary trends in industrial practice, emphasizing resource savings and performance prolongation for components and engineering systems The book is aimed at a range of readers, including graduate-level students, researchers, and engineers in mechanical, materials, and manufacturing engineering, especially those focused on resource savings, renovation, and failure prevention of components in engineering systems.

Remanufacturing and Advanced Machining Processes for New Materials and Components

"Remanufacturing and Advanced Machining Processes for Materials and Components presents current and emerging techniques for machining of new materials and restoration of components, as well as surface engineering methods aimed at prolonging the life of industrial systems. It examines contemporary machining processes for new materials, methods of protection and restoration of components, and smart machining processes. • Details a variety of advanced machining processes, new materials joining techniques, and methods to increase machining accuracy • Presents innovative methods for protection and restoration of components primarily from the perspective of remanufacturing and protective surface engineering • Discusses smart machining processes, including computer-integrated manufacturing and rapid prototyping, and smart materials • Provides a comprehensive summary of state-of-the-art in every section and a description of manufacturing methods • Describes the applications in recovery and enhancing purposes and identifies contemporary trends in industrial practice, emphasizing resource savings and performance prolongation for components and engineering systems The book is aimed at a range of readers, including graduate-level students, researchers, and engineers in mechanical, materials, and manufacturing engineering, especially those focused on resource savings, renovation, and failure prevention of components in engineering systems.

Remanufacturing and Advanced Machining Processes for New Materials and Components

Remanufacturing and Advanced Machining Processes for Materials and Components presents current and emerging techniques for machining of new materials and restoration of components, as well as surface engineering methods aimed at prolonging the life of industrial systems. It examines contemporary machining processes for new materials, methods of protection and restoration of components, and smart machining processes. • Details a variety of advanced machining processes, new materials joining techniques, and methods to increase machining accuracy • Presents innovative methods for protection and restoration of components primarily from the perspective of remanufacturing and protective surface engineering • Discusses smart machining processes, including computer-integrated manufacturing and rapid prototyping, and smart materials • Provides a comprehensive summary of state-of-the-art in every section and a description of manufacturing methods • Describes the applications in recovery and enhancing purposes and identifies contemporary trends in industrial practice, emphasizing resource savings and performance prolongation for components and engineering systems The book is aimed at a range of readers, including graduate-level students, researchers, and engineers in mechanical, materials, and manufacturing engineering, especially those focused on resource savings, renovation, and failure prevention of components in engineering systems

Remanufacturing and Advanced Machining Processes for New Materials and Components

Remanufacturing and Advanced Machining Processes for Materials and Components presents current and emerging techniques for machining of new materials and restoration of components, as well as surface engineering methods aimed at prolonging the life of industrial systems. It examines contemporary machining processes for new materials, methods of protection and restoration of components, and smart machining processes. • Details a variety of advanced machining processes, new materials joining techniques, and methods to increase machining accuracy • Presents innovative methods for protection and restoration of components primarily from the perspective of remanufacturing and protective surface engineering • Discusses smart machining processes, including computer-integrated manufacturing and rapid prototyping, and smart materials • Provides a comprehensive summary of state-of-the-art in every section and a description of manufacturing methods • Describes the applications in recovery and enhancing purposes and identifies contemporary trends in industrial practice, emphasizing resource savings and performance prolongation for components and engineering systems The book is aimed at a range of readers, including graduate-level students, researchers, and engineers in mechanical, materials, and manufacturing engineering, especially those focused on resource savings, renovation, and failure prevention of components in engineering systems

Experimental and theoretical investigations of nanosecond fibre laser micromachining

Pulsed ytterbium-doped fibre lasers based on a master oscillator power amplifier (MOPA) architecture possess attractive characteristics over their Q-switched diode-pumped solid-state counterparts. These include a relatively low cost of ownership and a flexible operating window with respect to the pulse duration, shape and repetition rate. For micro machining applications, given this inherent large processing window available with respect to the pulse characteristics, the effect of process parameters on particular machining outcomes needs to be investigated. The literature review conducted identified four important gaps in the knowledge surrounding the nanosecond fibre laser machining of materials. These gaps included the optimisation of the nanosecond fibre laser machining during milling operations, with the aim of obtaining both high surface quality and material removal rates, as well as the need for complimentary theoretical and experimental studies on the basic nanosecond laser material interaction for a wide range of engineering materials. In addition, the characterisation of the nanosecond laser machining of bulk metallic glasses, and the investigation of processing conditions leading to crystallisation of their amorphous structure, were identified as knowledge gaps that need to be addressed. The first knowledge gap was the focus of Chapter 3. The particular parameters under investigation in this study were the pulse duration and repetition frequency, the pulse overlap, the scanning strategy and the distance between linear machined tracks when processing aluminium. The results showed that, for each of the pulse durations studied, the specific frequency at which both the highest energy and average power are delivered leads to the maximum material removal rate (MRR) achievable, and to high values of surface roughness. It was also observed that the lowest surface roughness obtained corresponds to a specific frequency range which is common for all pulse durations. Following this, a design of experiments was conducted for a given pulse duration with the aim of identifying an optimum combination of parameters with respect to the attained surface roughness while operating at the frequency resulting in the highest MRR. This optimisation study resulted in a 60% decrease in the achieved surface roughness and also showed that the distance between machined tracks had the highest influence on the surface finish among the parameters considered. In the following chapter, a theoretical model was developed to predict the topographical evolution of the single pulse craters as a result of the time-dependent temperature rise in the processed materials when the laser beam is incident on its surface. In addition to this theoretical study, in an to attempt to understand the laser material interaction on a more fundamental level, single pulse experiments were conducted at varying laser fluence values and pulse durations leading to the formation of single craters on the surface of a number of materials namely, titanium, silicon and silicon carbide. In particular, different pulse lengths were investigated at decreasing values of fluence until no visible effect on the material surface could be observed. Based on this investigation, the fluence corresponding to the ablation threshold for each material at different pulse durations could be found whilst identifying the relationship between the laser processing parameters and the dimensions of the single craters. Scanning Electron Microscopy (SEM) micrographs of the craters were also used to observe phenomena such as melt ejection as a result of varying the process parameters. The experimental results were compared with the theoretical predictions and a good agreement between both set of data was found with respect to the achieved depths and diameters of the craters. The additional knowledge gaps were the focus of Chapter 5. In particular, the characterisation of nanosecond laser machining of a zirconium-based bulk metallic glass (BMG) was conducted using the approach employed in Chapter 4. Similar conclusions were reached with regard to the single pulse material removal behaviour when varying the fluence and pulse duration. In addition, milling of the material with different parametric combinations was implemented to investigate the crystallisation behaviour of the BMG. To complement these experimental tests, the theoretical model reported in Chapter 4 was further developed to predict the heating and cooling rates of the milling process. From this study, it was found that varying the process parameters of the machining of BMG results in a variation in the critical cooling rate (from the melt temperature to the glass transition temperature) which may result in crystallisation of the material

Glassy Materials Based Microdevices

Microtechnology has changed our world since the last century, when silicon microelectronics revolutionized sensor, control and communication areas, with applications extending from domotics to automotive, and from security to biomedicine. The present century, however, is also seeing an accelerating pace of innovation in glassy materials; as an example, glass-ceramics, which successfully combine the properties of an amorphous matrix with those of micro- or nano-crystals, offer a very high flexibility of design to chemists, physicists and engineers, who can conceive and implement advanced microdevices. In a very similar way, the synthesis of glassy polymers in a very wide range of chemical structures offers unprecedented potential of applications. The contemporary availability of microfabrication technologies, such as direct laser writing or 3D printing, which add to the most common processes (deposition, lithography and etching), facilitates the development of novel or advanced microdevices based on glassy materials. Biochemical and biomedical sensors, especially with the lab-on-a-chip target, are one of the most evident proofs of the success of this material platform. Other applications have also emerged in environment, food, and chemical industries. The present Special Issue of Micromachines aims at reviewing the current state-of-the-art and presenting perspectives of further development. Contributions related to the technologies, glassy materials, design and fabrication processes, characterization, and, eventually, applications are welcome

Laser-induced forward transfer (LIFT) of water soluble polyvinyl alcohol (PVA) polymers for use as support material for 3D-printed structures

The additive microfabrication method of laser-induced forward transfer (LIFT) permits the creation of functional microstructures with feature sizes down to below a micrometre [1]. Compared to other additive manufacturing techniques, LIFT can be used to deposit a broad range of materials in a contactless fashion. LIFT features the possibility of building out of plane features, but is currently limited to 2D or 2½D structures [2–4]. That is because printing of 3D structures requires sophisticated printing strategies, such as mechanical support structures and post-processing, as the material to be printed is in the liquid phase. Therefore, we propose the use of water-soluble materials as a support (and sacrificial) material, which can be easily removed after printing, by submerging the printed structure in water, without exposing the sample to more aggressive solvents or sintering treatments. Here, we present studies on LIFT printing of polyvinyl alcohol (PVA) polymer thin films via a picosecond pulsed laser source. Glass carriers are coated with a solution of PVA (donor) and brought into proximity to a receiver substrate (glass, silicon) once dried. Focussing of a laser pulse with a beam radius of 2 µm at the interface of carrier and donor leads to the ejection of a small volume of PVA that is being deposited on a receiver substrate. The effect of laser pulse fluence , donor film thickness and receiver material on the morphology (shape and size) of the deposits are studied. Adhesion of the deposits on the receiver is verified via deposition on various receiver materials and via a tape test. The solubility of PVA after laser irradiation is confirmed via dissolution in de-ionised water. In our study, the feasibility of the concept of printing PVA with the help of LIFT is demonstrated. The transfer process maintains the ability of water solubility of the deposits allowing the use as support material in LIFT printing of complex 3D structures. Future studies will investigate the compatibility (i.e. adhesion) of PVA with relevant donor materials, such as metals and functional polymers. References: [1] A. Piqué and P. Serra (2018) Laser Printing of Functional Materials. Weinheim, Germany: Wiley-VCH Verlag GmbH & Co. KGaA. [2] R. C. Y. Auyeung, H. Kim, A. J. Birnbaum, M. Zalalutdinov, S. A. Mathews, and A. Piqué (2009) Laser decal transfer of freestanding microcantilevers and microbridges, Appl. Phys. A, vol. 97, no. 3, pp. 513–519. [3] C. W. Visser, R. Pohl, C. Sun, G.-W. Römer, B. Huis in ‘t Veld, and D. Lohse (2015) Toward 3D Printing of Pure Metals by Laser-Induced Forward Transfer, Adv. Mater., vol. 27, no. 27, pp. 4087–4092. [4] J. Luo et al. (2017) Printing Functional 3D Microdevices by Laser-Induced Forward Transfer, Small, vol. 13, no. 9, p. 1602553

Optimization of Operation Sequencing in CAPP Using Hybrid Genetic Algorithm and Simulated Annealing Approach

In any CAPP system, one of the most important process planning functions is selection of the operations and corresponding machines in order to generate the optimal operation sequence. In this paper, the hybrid GA-SA algorithm is used to solve this combinatorial optimization NP (Non-deterministic Polynomial) problem. The network representation is adopted to describe operation and sequencing flexibility in process planning and the mathematical model for process planning is described with the objective of minimizing the production time. Experimental results show effectiveness of the hybrid algorithm that, in comparison with the GA and SA standalone algorithms, gives optimal operation sequence with lesser computational time and lesser number of iterations

Optimization of Operation Sequencing in CAPP Using Hybrid Genetic Algorithm and Simulated Annealing Approach

In any CAPP system, one of the most important process planning functions is selection of the operations and corresponding machines in order to generate the optimal operation sequence. In this paper, the hybrid GA-SA algorithm is used to solve this combinatorial optimization NP (Non-deterministic Polynomial) problem. The network representation is adopted to describe operation and sequencing flexibility in process planning and the mathematical model for process planning is described with the objective of minimizing the production time. Experimental results show effectiveness of the hybrid algorithm that, in comparison with the GA and SA standalone algorithms, gives optimal operation sequence with lesser computational time and lesser number of iterations