Polymers provide superior strength-to-weight ratios, malleability, cost-effectiveness, and recyclability compared to metals and alloys, rendering them highly favoured in the domains of automobile, electrical, medicinal, and thermal engineering. The present study employs a fiber laser as an approach to generate Gaussian beam-shaped micro-channels on thick transparent PMMA material while being submerged in de-ionized water to mitigate the problems associated with infrared laser micro-channeling such as non-uniformity, combustion and region of altered properties due to heat. Micro-channel quality is assessed by measuring three key metrics: depth of cut, kerf width, and heat-affected zone. This analysis considers power, cutting speed, and pulse frequency. The laser transmission channelling experiment is conducted on PMMA employs a central composite rotatable experimental strategy. The optimal settings are set to have a depth of cut of 25.34 mu m, a kerf width of 4.98 mu m, and a HAZ width of 36.32 mu m.

Industries that engage in laser-based material processing are increasingly turning to fiber lasers as one of the most effective laser systems available. Using a pulsed fiber laser system, an experimental investigation of underwater laser micro-channelling on hard to machine thick PMMA has been conducted in this research work. Submerged laser transmission cutting which is also known as underwater laser induced backside machining helps to generate clean kerf edge without presence of mushy region, which is very common during laser machining of thick PMMA with wavelength of near infrared region. Submerged conditions are used here for laser transmission micromachining in order to reduce adverse thermal effects and microcracking or charring inside the material. Pulse frequency, working power, and cutting speed have been selected as the input parameters. As machining responses, the depth of the micro-channel, the width of the kerf, and the width of the heat affected zone (HAZ) have been considered. To find the ideal parametric condition for simultaneously achieving numerous goals, Response Surface Methodology (RSM) and AI-based Teaching Learning-Based Optimisation (TLBO) have been used. The TLBO technique determined that the optimal laser machining settings are a power setting of 13.98 %, a pulse frequency of 50 kHz, and a cutting speed of 0.20 mm/sec. These parameters result in a minimum HAZ width of 4.1874 mu m, a minimum kerf width of 22.3698 mu m, and a maximum depth of cut of 37.1478 mu m. Underwater laser processing reduces heat affected zone and redeposition surrounding micro-channels, creating a cleaner, finer structure.

In the present research work, performance enhancement which plays pivotal role in the modern machining techniques during machining of advanced engineering materials has been attributed. An investigation is conducted on the laser transmission micro-channeling of thick transparent PMMA using Nd: YAG laser. The objective is to examine the impact of three key factors, namely pulse frequency, lamp current and cutting speed, on several quality aspects including depth of cut, kerf width, and heat-affected zone (HAZ) width. General full factorial design is used to design the experiments and empirical models (non-linear) are developed to establish the relationship between the control factors and responses. A feed forward back-propagation neural network (FF-BPNN) is used to model the process and subsequently to predict the responses. The successful capability of FF-BPNN in predicting and enhancing the characteristics of micro-channels fabricated on PMMA has been observed. Furthermore, it has been shown that feedforward backpropagation neural networks (FF-BPNN) can serve as a highly effective tool for acquiring a comprehensive model and determining the ideal configuration of process parameters in laser transmission micro-channeling operations. Additionally, FF-BPNN results and model predicted values are compared with non-linear modelling technique. Finally, mean absolute error is calculated to find out the accuracy of both the techniques.

Among the fastest growing basic materials, polymers have good strength-to-weight ratios, easy to shape, relatively economical, and recyclable which enabled it to become substitutes for metals and alloys in the fields of medical, automobile, aerospace, electronics, thermal and chemical engineering. But a thick transparent PMMA plate creates deep sub-surface cracks due to the burning and charring of polymeric chains, making the operation with Nd: YAG laser radiation extremely difficult. In the current research, a 75 W nanosecond pulsed Nd: YAG laser system is applied to make micro-channel with adequate depth on a thick transparent PMMA plate by using transmission cutting technique. The input process factors considered are pulse width, laser power, cutting speed, and pulse frequency in order to examine the quality characteristics, the depth of cut and heat affected zone (HAZ) in and around the formed micro-channel. To design the experiment of laser transmission channelling of thick PMMA plate of 11 mm, a central composite design (CCD) methodology is used. Due to open-air laser processing, undesirable laser processing effects have been minimised, resulting in a finer and cleaner micro-channel structure with adequate depth of cut, kerf width and minimal Heat Affected Zone (HAZ) width with laser power of around 9 W, pulse frequency of around 33 kHz and cutting speed of 2 mm/sec.

The objective of this study is to explore the impact of process parameters on the cut width and heat affected zone (HAZ) width of micro-channels manufactured using fiber laser on copper work piece. The study aimed to identify the optimal values for these responses. The analysis was conducted using response surface methodology (RSM), where tests were performed according to a predetermined experimental design. The scanning speed, pulse frequency, and working power were varied during the trials. The present study aims to elucidate and examine the operational principles underlying the creation of micro-channels on pure copper using a fiber laser operating at a wavelength of 1064 nm. Ultimately, by identifying the most effective combination of process parameters, the best values for both the width of the cut and the width of the heat affected zone (HAZ) are attained. This research study offers a comprehensive technical framework for the application of fiber laser processing on pure copper.

Underwater laser transmission micro -channelling of thick transparent polymethyl methacrylate (PMMA) using a neodymium -doped yttrium aluminium garnet (Nd: YAG) laser is the focus of this study. Experiments are conducted to determine the effect of three significant variables, namely pulse frequency, lamp current, and cutting speed, on heat -affected zone (HAZ) width, cut depth, and kerf width. Experiments are designed systematically utilising the full factorial design method. The purpose of constructing empirical models, specifically non-linear ones, is to establish and clarify the relationship between control factors and corresponding responses. A feed forward backpropagation neural network (FF-BPNN) is employed for predicting the measured response. Additionally, an assessment is made between the FF-BPNN results and the values predicted by the model. On the basis of the anticipated results, it can be concluded that the FF-BPNN model is preferable in predicting both the depth of cut and kerf width. In contrast, when specifically contemplating the measurement of HAZ width, the application of a non-linear model is more advantageous. As a measure of accuracy, the mean absolute error is computed for both the feedforward backpropagation neural network (FF-BPNN) and the nonlinear modelling technique.

Analyzing the performance of fiber laser micro-marking on aluminium alloy under focus-defocus conditions entails determining the way varying the focus position during the marking process impacts the overall performance. A special process variable defocus height refers to the distance between the focal point of the laser beam and the surface of the material being marked. In micro-marking, the focal point can be moved above or below the surface to generate distinct effects. The paper determines the optimal parameters for laser micro-marking on aluminium 7075 alloy, including laser power, pulse frequency, scan speed, defocus height (the distance between the top surface and the focal point), and duty cycle, for mark quality and characteristics such as depth and mark width. Experimental results showcase that laser parameters affect mark width and depth nonlinearly. In addition, small variations in laser power, scanning speed, or focus height, have led to moderate changes in dimensions of the mark geometry. A target mark of 40 mu m in width and 25 mu m in depth is achieved by combining optimum settings like a power of 23.862w, a duty factor of 45%, a pulse frequency of 76.0506Khz, a scanning speed of 0.70mm/s, and a defocus height of 0.7mm.

The demand for scaling up polymeric materials for mass production or scaling down for microscale applications is at its peak in the modern era. Laser beam technology enables the formation of micro-channels on polymers, specifically polymethyl methacrylate (PMMA). This study examines the viability and cost-effectiveness of employing the diode pump fiber laser transmission technique to create micro-channels on thick, transparent PMMA under air-assisted circumstances for biomedical engineering and micro-fluidics applications. The analysis has included process variables such as pulse frequency, power, and cutting speed, as well as machining parameters including depth of cut, kerf width, and heat-affected zone (HAZ) width. The results of multi -objective optimization indicate that the following parameters-a pulse frequency of 51.30 kHz, a working power of 13 % of 50 W, and a cutting speed of 0.60 mm/s-contribute to the desired microfluidics response values: 12.54 mu m depth of cut, 24.05 mu m kerf width, and 5.98 mu m HAZ width.

Polymers provide superior strength-to-weight ratios, malleability, cost-effectiveness, and recyclability compared to metals and alloys, rendering them highly favoured in the fields of thermal, medical, electronics, and automotive engineering. The present study employs a fiber laser as an approach to generate Gaussian beam-shaped micro-channels on thick transparent PMMA (polymethyl methacrylate) material while being submerged in de-ionized water to mitigate the problems associated with infrared laser micro-channeling such as non-uniformity, burning, and heat-affected zone (HAZ). The assessment of micro-channel quality involves the measurement of three key parameters: depth of cut (DOC), kerf width (KW), and HAZ width. This analysis takes into account factors such as operational efficiency, cutting speed, and pulse frequency. The laser transmission channelling experiment conducted on PMMA employs a central composite rotatable experimental design (CCRD). The utilisation of underwater laser processing serves to mitigate the occurrence of heat-affected zones and the deposition of materials in the vicinity of micro-channels. Therefore, this methodology generates accurate and well-defined micro-channel structures.

Laser transmission welding (LTW) is a widely used polymer welding technology in industries today. The performance of LTW is governed by a number of process parameters, and fine-tuning those parameters is critical for the process to achieve the intended results. Optimization of process parameters for enhancing LTW performance, like weld strength and weld width, is always tricky since they are inherently contradictory. Therefore, in this research, an effort is made to optimize the LTW parameters utilizing the three best-known optimization approaches, and the performance of those optimization approaches in LTW process optimization is compared. First, the response surface method (RSM) is employed to build empirical equations that establish an empirical correlation between process variables and desired performance features. These empirical equations are then employed as objective functions for process optimization utilizing the RSM-based desirability function approach (DFA), particle swarm optimization (PSO), and teaching learning-based optimization (TLBO) algorithms. The performance of the chosen optimization approaches is compared with reference to optimum results, accuracy, convergence rate, and computing time. PSO and TLBO algorithms outperform the DFA approach for single and multi-objective optimizations. TLBO is found to have faster convergence, whereas PSO takes less time for computation.

Monel k-500 is a nickel-copper alloy with excellent resistivity towards corrosion, strength and hardness. This makes drilling of precision holes into the super alloy tricky. However, laser beam machining (LBM) employing low power fiber laser has been a potential and successful process in performing laser trepanned drilling operation on nickel based super alloy to produce superior quality holes. The laser drilling process involves a number of process parameters. Each of it is important for the success of the drilling operation. This research paper studies the process parameters and the performance characteristics of laser drilling on difficult to cut Monel k-500 super alloy. Input process parameters for this study include sawing angle, power setting, duty cycle, pulse frequency and trepanning speed. An experiment matrix has been designed to establish the relation between each significant process parameter and hole characteristics like hole taper and heat affected zone (HAZ). Teaching learning-based optimization (TLBO) algorithm has been applied to perform single objective optimization and multi objective optimization to achieve optimized values of hole taper and HAZ. It is also demonstrated that the algorithm used in the study is a powerful tool capable of obtaining optimal parameters setting of LBM.

The Transmission welding using incremental scanning technique (TWIST) combines linear feed with an oscillating laser beam to enhance weld quality and expand the process window. However, TWIST welding is influenced by nonlinear process variables, and achieving multiple objectives concurrently is challenging due to conflicting performance attributes. In industrial practice, time constraints and project specifications limit the effectiveness of methodologies tailored to specific workpiece materials or single performance optimization. The present study employs an artificial neural network (ANN) to establish a correlation between TWIST welding parameters and desired performance attributes. Various ANN model architectures are evaluated, with the 5-11-6-2 architecture achieving the highest accuracy (correlation coefficient of 0.998). For multi-objective optimization, the non-dominated sorted genetic algorithm (NSGA-II) and non-dominated sorted teaching learning-based optimization (NSTLBO) algorithm are employed, utilizing the ANN model's fitness function as the objective. The newly developed two-step model provides operators with the flexibility to prioritize factors based on project requirements, resulting in improved outcomes. Comparative analysis of the algorithms using seven metrics demonstrates that NSGA-II outperforms NSTLBO in solution prediction, albeit with slightly increased computing time. NSGA-II offers a broader range of Pareto optimum solutions compared to NSTLBO, which converges narrowly and restricts non-dominated sets. Validation experiments confirm the adequacy of both algorithms, supporting the effectiveness of the two-step model. The proposed methodology enables practitioners to achieve better weld quality, accommodate conflicting performance attributes, and effectively optimize multiple objectives in industrial applications.

About thirty-five years after the appearance the additive manufacturing has taken a great role in main stream manufacturing process. On the basis of computerized CAD model additive manufacturing helps to fabricate parts by adding materials on layer at a time. Auxiliary inputs like fixtures, cutting tool and coolants are not required to be used for its production. Additive manufacturing permits optimization of the design and the production of customized parts on demand. As the advantages of additive manufacturing are more than the advantages of traditional manufacturing it has gain an attention and imagination of the public. As a result, many of the publications are inspired to call additive manufacturing as the third industrial revolution. The following domains show plenty of promising performances of 3-D printing in various fields. Products related to customized health care for the improvement of population health and quality of life, reduction in environmental influence in the field of sustainable manufacturing and supply chain simplification for increasing efficiency and responsiveness in demand fulfillment. All these favorable advantages in additive manufacturing have made it necessary for further research in the domain of life cycle energy consumption, evaluation and probable occupational hazard assessment.

Owing to the increasing use of polymers in microfluidic devices, lightweight automotive and modern industries, laser transmission welding has evolved as a reliable method over the years. In this paper, sensitivity analysis has been performed to find out the critical parameters and to compare the relative impact of process variables on weld quality. Two transparent PMMA materials have been joined using low power laser with 1064 nm wavelength. The results are analyzed for laser transmission welding processes by considering corresponding parameters such as laser power, pulse frequency and scanning speed. Scanning speed is found to be dominant parameter based on statistical method while sensitiveness of weld strength and weld width are maximum for laser power. Optimization of process variable helps to obtain desired responses. A novel metaheuristic Teaching Learning Based Algorithm has been used to maximize the weld strength and minimize the weld width. Copyright (c) 2021 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the International Conference on Applied Research and Engineering 2021

Manufacturing industries are very much interested in laser beam machining for its efficiency in material removal. As a result, this non-conventional machining process bears a great determination for its modelling and optimization. Difficulty lies in the development of an accurate model between the input and output variables and the non-linear behaviour of the process makes it complex under various situations. A new process variable of sawing angle makes it more complicated for quality characteristics. The present study deals with a research effort for examination of the influences of the process parameter of fiber laser beam machining regarding cutting of Titanium superalloy (Ti6Al4V). Sawing angle, power, duty cycle, pulse frequency and scanning speed are the input variables in laser beam machining process and quality characteristics of laser machined workpiece along with kerf taper and heat affected zone are the output variables. Empirical findings and existing knowledge in regard to modelling, optimizing, monitoring and controlling of the LBM process have been used by the artificial intelligence (AI) technique. This study bears an application of AI technique regarding metaheuristic-based particle swarm optimization (PSO) in regard to the quality features of LBM in modelling and optimization.

Laser transmission welding (LTW) is a proven technique, but it is not yet at its peak. Polymeric products are increasingly being used in various applications, including packaging, appliances, medical electronics, automobile, and aerospace, due to their ease of manufacture, low cost, and recycling capability.LTW is a cutting-edge welding technique used to join polymers and plastics. The key benefits of LTW over traditional plastic welding methods are the contactless and vibration-free energy input, precise control of the applied energy, and the resulting reproducibility and low thermal load of the components. However, material restriction continues to be a significant issue when it comes to the welding of polymers. The researchers are focusing on LTW of polymer combinations that are difficult to weld due to differing degrees of incompatibility. This article covers many of the critical scientific and technological aspects of laser welding of thermoplastic materials, demonstrating the process fundamentals and how the degree of sophistication for LTW of polymers has progressed over time. This frame of reference addresses various techniques and novel ideas for polymer LTW. Furthermore, many LTW applications are presented, showing how rapidly the market accepted this novel technology.

Because of numerous advantageous characteristics of polymers and their expanding usage in microfluidic devices, automotive, household, packaging, and biomedical sectors, laser transmission welding (LTW) has emerged to meet the need for a potent polymer welding technology for industrial use. This paper presents an experimental investigation, mathematical modeling, and parameters optimization of wobble LTW of dissimilar transparent polymers. A low-power Nd:YVO4 laser is used to fuse transparent acrylic and polycarbonate plaques using a black marker ink line applied at the weld interface. Planned experiments and corresponding analyses are performed to develop the mathematical models and investigate the effect of beam wobbling on the process responses. The wobbling of the beam creates homogenized heat distribution and turbulence inside the weld pool, which improves material intermixing and joint strength. Morphological analysis reveals the presence of a number of tiny bubbles on the top surface of the weld bead, which strengthens the micromechanical joining at the weld interface. Artificial intelligence-based teaching learning-based optimization (TLBO) algorithm and desirability function analysis (DFA)-based optimization method are employed to improve the weld quality and to obtain the desired response. TLBO produces more accurate results than DFA because of its strong convergence towards global optima.

In the manufacturing industry critical importance lies upon the dimensional accuracy of a machining part especially for precision assembly operation in sheet metal cutting. But the converging diverging shape of the laser beam profile causes the existence of kerf taper in laser cut specimen. Use of low power fibre laser beam machining in the order of 50 watt makes it extremely difficult to perform good quality cut on stainless steel sheet metal. Cutting wedge angle, a relatively uncommon process variable performs a critical role for the determination of unevenness in kerf characteristic. Cutting result of kerf taper with a 50-watt fibre laser is presented in this investigation. The purpose of the investigation is to reveal the ability of the low power fibre laser to cut stainless steel AISI 316 L with 1 mm thickness. The effect of the cutting wedge angle and other process variables like power, duty cycle, pulse frequency and scanning speed has been analysed through an application of Response Surface Methodology (RSM) with CCD technique. Validation of experiments on the proposed model reveals that adjustment of proper process parameters can optimise the required edge quality.

Laser transmission welding (LTW) is widely recognized as an effective joining method for thermoplastic polymers. Excellent mechanical, physical and thermal properties of polypropylene makes it suitable for many application in aerospace, automotive manufacturing and laboratory accessories; however, joining of semi-crystalline and amorphous polymers is very difficult due to their poor compatibility or different crystal structure. To overcome this problem, white ink is applied at the interface of weld to increase the solubility and retain the laser heat input. As white ink is an opaque, containing copolymer resins which helps to enhance the bonding strength. Here, acrylic (amorphous) and polypropylene copolymer (PPCP) (semi-crystalline) each of 4 mm thickness have been joined by low power diode laser. Experimental analysis of the effect of process parameters such as laser power, scanning speed and pulse frequency on the weld zone has been studied. Greater weld strength is achieved at low scan speed. A novel multi objective snap drift cuckoo search (SDCS) optimization technique has been implemented for betterment of weld strength and weld width. A scanning electron microscope (SEM) has been used to observe the welded zone morphology. It is observed that weld strength is primarily dependent on mechanical interlocking between the two layers of polymers.