Studi Optimisasi Heat Flux dan Welding Speed pada Pengelasan Laser Fiber terhadap Lebar Lasan, Kedalaman Penetrasi dan Tegangan Sisa Esshete 1250 dengan Metode Elemen Hingga

Parameter input pengelasan laser berpengaruh terhadap kualitas hasil pengelasan. Hasil pengelasan berupa lebar lasan, kedalaman penetrasi dan tegangan sisa menentukan kualitas dari sambungan logam. Penelitian ini dilakukan untuk mendapatkan hasil pengelasan laser optimal digunakan Finite Element Method (FEM) dan Response Surface Methodology (RSM). Proses simulasi pada material Esshete 1250 dilakukan sebanyak 12 kali dengan parameter input yang berbeda. Parameter input yang pertama adalah heat flux dengan variasi power input 2000 W, 2250 W, 2500 W, dan 2750 W. Parameter input yang kedua adalah welding speed dengan variasi 2,5 m/min, 3 m/min, dan 3,5 m/min. Hasil simulasi menggambarkan pengaruh heat flux yang semakin tinggi akan meningkatkan lebar lasan, memperdalam kedalaman penetrasi dan meningkatkan tegangan sisa. Hasil simulasi juga menggambarkan pengaruh welding speed yang semakin tinggi akan mempersempit lebar lasan, mengurangi kedalaman penetrasi, dan mengurangi tegangan sisa. Hasil dari simulasi divalidasi menggunakan persamaan matematis dan didapatkan hasil yang valid. ====================================================================================================== Laser welding input parameters have significant effect on the welding bead profile. Welding bead profile like width weld, penetration depth, and residual stress determine the quality of butt joint. This study was done to get optimal laser welding bead profile parameters using Finite Element Method (FEM) and Response Surface Methodoly (RSM). Simulation process on Esshete 1250 materials were done 12 times with different input parameters. The first input parameters were power input 2000 W, 2250 W, 2500 W, and 2750 W. The second parameters were welding speed of 2,5 m/min, 3 m/min, and 3,5 m/min. From the result simulation were known that the higher heat flux will increase weld width, deepen penetration depth, and increase residual stress. Another case, the higher welding speed will make narrow weld width, reduce penetration depth, and reduce residual stress. Simulation result was validated with mathematical equation and obtained valid result

Development of a multi-objective optimization algorithm based on lichtenberg figures

This doctoral dissertation presents the most important concepts of multi-objective optimization and a systematic review of the most cited articles in the last years of this subject in mechanical engineering. The State of the Art shows a trend towards the use of metaheuristics and the use of a posteriori decision-making techniques to solve engineering problems. This fact increases the demand for algorithms, which compete to deliver the most accurate answers at the lowest possible computational cost. In this context, a new hybrid multi-objective metaheuristic inspired by lightning and Linchtenberg Figures is proposed. The Multi-objective Lichtenberg Algorithm (MOLA) is tested using complex test functions and explicit contrainted engineering problems and compared with other metaheuristics. MOLA outperformed the most used algorithms in the literature: NSGA-II, MOPSO, MOEA/D, MOGWO, and MOGOA. After initial validation, it was applied to two complex and impossible to be analytically evaluated problems. The first was a design case: the multi-objective optimization of CFRP isogrid tubes using the finite element method. The optimizations were made considering two methodologies: i) using a metamodel, and ii) the finite element updating. The last proved to be the best methodology, finding solutions that reduced at least 45.69% of the mass, 18.4% of the instability coefficient, 61.76% of the Tsai-Wu failure index and increased by at least 52.57% the natural frequency. In the second application, MOLA was internally modified and associated with feature selection techniques to become the Multi-objective Sensor Selection and Placement Optimization based on the Lichtenberg Algorithm (MOSSPOLA), an unprecedented Sensor Placement Optimization (SPO) algorithm that maximizes the acquired modal response and minimizes the number of sensors for any structure. Although this is a structural health monitoring principle, it has never been done before. MOSSPOLA was applied to a real helicopter’s main rotor blade using the 7 best-known metrics in SPO. Pareto fronts and sensor configurations were unprecedentedly generated and compared. Better sensor distributions were associated with higher hypervolume and the algorithm found a sensor configuration for each sensor number and metric, including one with 100% accuracy in identifying delamination considering triaxial modal displacements, minimum number of sensors, and noise for all blade sections.Esta tese de doutorado traz os conceitos mais importantes de otimização multi-objetivo e uma revisão sistemática dos artigos mais citados nos últimos anos deste tema em engenharia mecânica. O estado da arte mostra uma tendência no uso de meta-heurísticas e de técnicas de tomada de decisão a posteriori para resolver problemas de engenharia. Este fato aumenta a demanda sobre os algoritmos, que competem para entregar respostas mais precisas com o menor custo computacional possível. Nesse contexto, é proposta uma nova meta-heurística híbrida multi-objetivo inspirada em raios e Figuras de Lichtenberg. O Algoritmo de Lichtenberg Multi-objetivo (MOLA) é testado e comparado com outras metaheurísticas usando funções de teste complexas e problemas restritos e explícitos de engenharia. Ele superou os algoritmos mais utilizados na literatura: NSGA-II, MOPSO, MOEA/D, MOGWO e MOGOA. Após validação, foi aplicado em dois problemas complexos e impossíveis de serem analiticamente otimizados. O primeiro foi um caso de projeto: otimização multi-objetivo de tubos isogrid CFRP usando o método dos elementos finitos. As otimizações foram feitas considerando duas metodologias: i) usando um meta-modelo, e ii) atualização por elementos finitos. A última provou ser a melhor metodologia, encontrando soluções que reduziram pelo menos 45,69% da massa, 18,4% do coeficiente de instabilidade, 61,76% do TW e aumentaram em pelo menos 52,57% a frequência natural. Na segunda aplicação, MOLA foi modificado internamente e associado a técnicas de feature selection para se tornar o Seleção e Alocação ótima de Sensores Multi-objetivo baseado no Algoritmo de Lichtenberg (MOSSPOLA), um algoritmo inédito de Otimização de Posicionamento de Sensores (SPO) que maximiza a resposta modal adquirida e minimiza o número de sensores para qualquer estrutura. Embora isto seja um princípio de Monitoramento da Saúde Estrutural, nunca foi feito antes. O MOSSPOLA foi aplicado na pá do rotor principal de um helicóptero real usando as 7 métricas mais conhecidas em SPO. Frentes de Pareto e configurações de sensores foram ineditamente geradas e comparadas. Melhores distribuições de sensores foram associadas a um alto hipervolume e o algoritmo encontrou uma configuração de sensor para cada número de sensores e métrica, incluindo uma com 100% de precisão na identificação de delaminação considerando deslocamentos modais triaxiais, número mínimo de sensores e ruído para todas as seções da lâmina

Optimisation of laser welding of deep drawing steel for automotive applications by Machine Learning: A comparison of different techniques

Laser welding is particularly relevant in the industry thanks to its simplicity, flexibility and final quality. The industry 4.0 and sustainable manufacturing framework gives massive attention to in situ and non-destructive inspection methods to predict laser weld final quality. Literature often resorts to supervised Machine Learning approaches. However, selecting the ApTest method is non-trivial and often decision making relies on diverse and unclearly defined criteria. This work addresses this task by proposing a statistical comparison method based on nonparametric tests. The method is applied to the most relevant supervised Machine Learning approaches exploited in literature to predict laser weld quality, specifically, considering the optimisation of a new production line, hence focussing on supervised Machine Learning methods that do not require massive data set, that is, Generalized Linear Model (GLM), Gaussian Process Regression, Support Vector Machine, Classification and Regression Tree, and Genetic Algorithms. The statistical comparison is carried out to select the best-performing model, which is then exploited to optimise the production process. Additionally, an automatic process to optimise Machine Learning models and process parameters is resorted to, basing on Bayesian approaches, to reduce operator effect. This work provides quality and process engineers with a simple framework to compare Machine Learning approaches performances and select the most suitable process modelling technique

Studi Optimisasi Heat Flux dan Welding Speed pada Pengelasan Laser Fiber terhadap Lebar Lasan, Kedalaman Penetrasi dan Tegangan Sisa Esshete 1250 dengan Metode Elemen Hingga

Parameter input pengelasan laser berpengaruh terhadap kualitas hasil pengelasan. Hasil pengelasan berupa lebar lasan, kedalaman penetrasi dan tegangan sisa menentukan kualitas dari sambungan logam. Penelitian ini dilakukan untuk mendapatkan hasil pengelasan laser optimal digunakan Finite Elemen Method (FEM) dan Response Surface Methodology (RSM). Proses simulasi pada material Esshete 1250 dilakukan sebanyak 12 kali dengan parameter input yang berbeda. Parameter input pertama adalah heat flux dengan variasi power input 2000 W, 2250 W, 2500 W, dan 2750 W. Parameter input yang kedua adalah welding speed dengan variasi 2,3 m/min, 3 m/min, dan 3,5 m/min. Hasil simulasi menggambarkan pengaruh heat flux yang semakin tinggi akan meningkatkan lebar lasan, memperdalam kedalaman penetrasi dan tegangan sisa. Hasil simulasi juga menggambarkan pengaruh welding speed yang semakin tinggi akan mempersempit lebar lasan, mengurangi kedalaman penetrasi, dan mengurangi tegangan sisa. Hasil dari simulasi divalidasi menggunakan persamaan matematis dan didapatkan hasil yang valid

Belgium

This work focuses on the thermal modeling of the Directed Energy Deposition of a composite coating (316L stainless steel reinforced by Tungsten carbides) on a 316L substrate. The developed finite element model predicts the thermal history and the melt pool dimension evolution in the middle section of the clad during deposition. Numerical results were correlated with experimental analysis (light optical and scanning electron microscopies and thermocouple records) to validate the model and discuss the possible solidification mechanisms. It was proven that implementation of forced convection in the boundary conditions was of great importance to ensure equilibrium between input energy and heat losses. The maximum peak temperature shows a slight increase trend for the first few layers, followed by an apparent stabilization with increasing clad height. That demonstrates the high heat loss through boundaries. While in literature, most of the modeling studies are focused on single or few layer geometries, this work describes a multi-layered model able to predict the thermal field history during deposition and give consistent data about the new materiel. The model can be applied on other shapes under recalibration. The methodology of calibration is detailed as well as the sensitivity analysis to input parameters.Peer reviewe

Particle swarm optimization for cooperative multi-robot task allocation: a multi-objective approach

This paper presents a new Multi-Objective Particle Swarm Optimization (MOPSO) approach to a Cooperative Multi Robot Task Allocation (CMRTA) problem, where the robots have to minimize the total team cost and, additionally, balance their workloads. We formulate the CMRTA problem as a more complex variant of multiple Travelling Salesman Problems (mTSP) and, in particular, address how to minimize the total travel distance of the entire robot team, as well as how to minimize the highest travel distance of an individual robot. The proposed approach extends the standard single-objective Particle Swarm Optimization (PSO) to cope with the multiple objectives, and its novel feature lies in a Pareto front refinement strategy and a probability-based leader selection strategy. To validate the proposed approach, we first use three benchmark functions to evaluate the performance of finding the true Pareto fronts in comparison with four existing well-known algorithms in continuous spaces. Afterwards, we use six datasets to investigate the task allocation mechanisms in dealing with the CMRTA problem in discrete spaces.benchmark functions to evaluate the performance of findingthe true Pareto fronts in comparison with four existing wellknownalgorithms in continuous spaces. Afterwards, we use sixdatasets to investigate the task allocation mechanisms in dealingwith the CMRTA problem in discrete spaces

Studi Optimisasi Diameter Sinar Laser dan Daya Laser pada Pengelasan Laser terhadap Lebar Lasan dan Kedalaman Penetrasi SA-516 Grade 70 dengan Metode Elemen Hingga

Salah satu cara untuk menilai kualitas dari hasil sambungan pengelasan adalah dengan mengetahui dimensi dari weld metal terutama lebar lasan dan kedalaman penetrasi. Parameter pengelasan laser yang digunakan berpengaruh pada kualitas hasil pengelasan. Proses simulasi dan optimisasi dari pengelasan laser dilakukan untuk memprediksi hasil pengelasan laser dan memilih parameter untuk mendapatkan hasil yang optimal. Simulasi dan optimisasi masing – masing dilakukan dengan menggunakan Finite Element Method (FEM) dan Response Surface Methodology (RSM). Simulasi pada material baja SA-516 grade 70 dilakukan sebanyak sembilan kali dengan parameter pengelasan yang berbeda. Parameter masukan pertama adalah variasi diameter sinar laser 1 mm; 0,9 mm; dan 0,8 mm. Kemudian parameter masukan kedua adalah variasi daya laser 1750 W, 2000 W, dan 2250 W. Selain itu, perubahan fasa juga dipertimbangkan dengan menghitung nilai entalpi berdasarkan nilai specific heat dan latent heat peleburan material. Hasil simulasi menunjukkan bahwa semakin kecil diameter sinar laser maka lebar lasan semakin menurun, laju solidifikasi semakin lambat, kedalaman penetrasi, dan lebar HAZ semakin meningkat. Hasil simulasi juga menggambarkan bahwa semakin tinggi daya laser maka lebar lasan semakin meningkat, laju solidifikasi semakin lambat, kedalaman penetrasi, dan lebar HAZ semakin meningkat. Kemudian agar mendapatkan hasil pengelasan yang optimal maka direkomendasikan untuk menggunakan parameter diameter sinar laser 0,8 mm serta daya laser dengan rentang 2000 – 2250 W. Proses validasi dengan perhitungan matematis telah dilakukan dan didapatkan hasil simulasi yang valid. ================= One way to assess the quality of the welded joint results is to know the dimensions of the weld metal especially the weld width and the penetration depth. The laser welding parameters used affect the quality of the weld. Simulation and optimization process of laser welding is done to predict laser welding results and to select parameters to obtain the optimal results. Simulation and optimization are each performed using Finite Element Method (FEM) and Response Surface Methodology (RSM). Simulation of SA-516 grade 70 steel was done nine times with different welding parameters. The first input parameters are laser beam diameter with variations of 1 mm, 0.9 mm, and 0.8 mm. Then the second input parameter is a variation of laser power 1750 W, 2000 W, and 2250 W. In addition, phase change is also considered by calculating the value of enthalpy based on specific heat value and melting latent heat of material. The simulation results show that the smaller the laser beam diameter, the weld width decreases, the solidification rate becomes slower, the penetration depth, and HAZ Width increases. The simulation results also illustrate that the higher the laser power the weld width increases, the solidification rate is slower, the penetration depth, and HAZ Width increases. Then in order to obtain optimal welding results it is recommended to use the laser beam diameter parameter of 0.8 mm and laser power with the range of 2000 – 2250 W. Validation process using mathematical calculations have been done and obtained simulation results are found to be valid

Design optimisation for stent manufacture

Intravascular stents of various designs are currently used to prop open diseased arteries and there is evidence that different stent geometries have different in-stent restenosis rates. The majority of commercially available stents are designed generically to fit all individuals. Recent advances in imaging and catheter technologies, however, allow measurement of lesion shape and stiffness. Incorporating patient specific data into the stent design process could enable the development of customised stents. Considering the variety of lesion types, it is envisaged that better outcomes will be achieved if a stent is custom designed in such a way that it has variable radial stiffness longitudinally to hold the varying pressure of plaque and healthy artery at the same time while maintaining an acceptable lumen diameter. This type of operation is suitable for topology optimisation potentially allowing for optimal material distribution of a stent. The primary aim of this research is to develop new stent designs for a set of plaque types and investigate the final radius of the lumen after stent implantation. Stent geometries were obtained by topology optimisation for minimised compliance under different stenosis levels and plaque materials. Three types of stenosis levels by area, i.e. 30%, 40% and 50% with each type having three different plaque material properties i.e. calcified, cellular and hypocellular were studied. The optimisation results were transformed to clear design concepts and their performance was evaluated by implanting them in their respective stenosed artery types using finite element analysis. The results were compared with a generic stent in similar arteries, which showed that the new designs showed less recoil. In the hardest (calcified) of plaques studied, topology optimised designs overall resulted in 2%, 2% and 6% residual area stenosis compared to 10%, 29% and 35% from the generic design in arteries with 30%, 40% and 50% stenosis respectively. It was shown that higher material distribution resulted in the central region of the stent in order to resist implantation recoil due to higher plaque compressive loads. Additive manufacturing (AM) was utilised to validate the computational approach used in this thesis. This work provides a proof of concept for stents tailored to specific lesions in order to minimise recoil and maintain a patent lumen in stenotic arteries

Design optimisation for stent manufacture

Intravascular stents of various designs are currently used to prop open diseased arteries and there is evidence that different stent geometries have different in-stent restenosis rates. The majority of commercially available stents are designed generically to fit all individuals. Recent advances in imaging and catheter technologies, however, allow measurement of lesion shape and stiffness. Incorporating patient specific data into the stent design process could enable the development of customised stents. Considering the variety of lesion types, it is envisaged that better outcomes will be achieved if a stent is custom designed in such a way that it has variable radial stiffness longitudinally to hold the varying pressure of plaque and healthy artery at the same time while maintaining an acceptable lumen diameter. This type of operation is suitable for topology optimisation potentially allowing for optimal material distribution of a stent. The primary aim of this research is to develop new stent designs for a set of plaque types and investigate the final radius of the lumen after stent implantation. Stent geometries were obtained by topology optimisation for minimised compliance under different stenosis levels and plaque materials. Three types of stenosis levels by area, i.e. 30%, 40% and 50% with each type having three different plaque material properties i.e. calcified, cellular and hypocellular were studied. The optimisation results were transformed to clear design concepts and their performance was evaluated by implanting them in their respective stenosed artery types using finite element analysis. The results were compared with a generic stent in similar arteries, which showed that the new designs showed less recoil. In the hardest (calcified) of plaques studied, topology optimised designs overall resulted in 2%, 2% and 6% residual area stenosis compared to 10%, 29% and 35% from the generic design in arteries with 30%, 40% and 50% stenosis respectively. It was shown that higher material distribution resulted in the central region of the stent in order to resist implantation recoil due to higher plaque compressive loads. Additive manufacturing (AM) was utilised to validate the computational approach used in this thesis. This work provides a proof of concept for stents tailored to specific lesions in order to minimise recoil and maintain a patent lumen in stenotic arteries