30 research outputs found

    Laser welding of Ti6Al4V alloy by disk laser: analysis and optimization

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    2010 - 2011Titanium alloys have been successfully applied in many industrial fields because of their better performance and lighter weight than other commonly used structural materials. The conventional welding methods used for titanium alloys are tungsten inert gas (TIG) and plasma arc welding. In recent decades, autogenous processes with highly concentrated energy sources have become popular; these joining processes are laser and electron-beam welding. The power source can be concentrated in very small areas so as to achieve energy densities up to 10,000 times higher than those of the arc processes. Laser welding allows joints to be made with limited distortion. The fullyautomated process, ensures high productivity and high-quality joints. Laser technology is acquiring industrial interest because the electron-beam processes have limitations, such as the need to operate in vacuum, the increased costs and the emission of X-rays. Titanium alloys are widely used in the aircraft industry, because of their high strength-to-weight ratio, corrosion resistance, operating temperature and bonding with composite materials (electrochemical compatibility, similar coefficients of thermal expansion). The criteria for the design, manufacture and operation were changed to obtain structures that are lighter and more efficient than the ones made of aluminum. However, the structures in carbonfiber- reinforced-polymer require the use of metal structures, especially in areas of great concentration of loads. In spite of several advantages, these alloys lead to excessive manufacturing costs related to the cost of the raw materials, the high volumes of waste and the complex and expensive finishing. For these reasons, it is cheaper to produce semi-finished products by welding simpler parts, instead of casting and forming processes; therefore, laser welding can be used due to its high productivity and quality end-products. The aim of the thesis work is to find the better input process parameters values to weld 3 mm and 1 mm Ti6Al4V sheets using a 2 kW Yb:YAG disk laser. Both bead on plate and butt tests have been performed, and the beads quality is characterized in terms of geometric features, porosity content, microstructure, hardness and strength. This work is organized in five chapters. Chapter 1 discusses the principles of operation and the different types of laser including disk laser, used in the experimental part. Chapter 2 presents the properties of titanium and its alloys, highlighting the various fields of application. Chapter 3 presents a review of the different technologies used for welding of titanium alloys, focusing primarily on laser welding and its mechanisms. Chapter 4 describes the titanium alloy, equipment and methodologies used in the experimental work. Finally, Chapter 5 presents the results obtained. [edited by author]X n.s

    Strategic Planning and Design of Supply Chains: a Literature Review

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    In this paper, a literature review of the mathematical models for supply chain design is proposed. The research is based on the study and analysis of publications of the last twelve years from the most widespread international journal about operations management and logistics. The aim of the work lies in identifying tendencies in the literature and related open issues about the strategic decisions, economic parameters, constraints and model features considered in the strategic planning and design of supply chains. After a description of the review methodology, comparison parameters and paper exhaustiveness, some guidelines are given in order to support future works in this field

    An enhancement to the Bees Algorithm with slope angle computation and Hill Climbing Algorithm and its applications on scheduling and continuous-type optimisation problem

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    This paper focuses on improvements to the Bees Algorithm (BA) with slope angle computation and Hill Climbing Algorithm (SACHCA) during the local search process. First, the SAC was employed to determine the inclination of the current sites. Second, according to the slope angle, the HCA was utilised to guide the algorithm to converge to the local optima. This enabled the global optimum of the given problem to be found faster and more precisely by focusing on finding the available local optima first before turning the attention on the global optimum. The proposed enhancements to the BA have been tested on continuous-type benchmark functions and compared with other optimisation techniques. The results show that the proposed algorithm performed better than other algorithms on most of the benchmark functions. The enhanced BA performs better than the basic BA, in particular on higher dimensional and complex optimisation problems. Finally, the proposed algorithm has been used to solve the single machine scheduling problem and the results show that the proposed SAC and HCA-BA outperformed the basic BA in almost all the considered instances, in particular when the complexity of the problem increases

    Honey Bees Inspired Optimization Method: The Bees Algorithm

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    Optimization algorithms are search methods where the goal is to find an optimal solution to a problem, in order to satisfy one or more objective functions, possibly subject to a set of constraints. Studies of social animals and social insects have resulted in a number of computational models of swarm intelligence. Within these swarms their collective behavior is usually very complex. The collective behavior of a swarm of social organisms emerges from the behaviors of the individuals of that swarm. Researchers have developed computational optimization methods based on biology such as Genetic Algorithms, Particle Swarm Optimization, and Ant Colony. The aim of this paper is to describe an optimization algorithm called the Bees Algorithm, inspired from the natural foraging behavior of honey bees, to find the optimal solution. The algorithm performs both an exploitative neighborhood search combined with random explorative search. In this paper, after an explanation of the natural foraging behavior of honey bees, the basic Bees Algorithm and its improved versions are described and are implemented in order to optimize several benchmark functions, and the results are compared with those obtained with different optimization algorithms. The results show that the Bees Algorithm offering some advantage over other optimization methods according to the nature of the problem

    Industry 4.0 enabling sustainable supply chain development in the renewable energy sector:A multi-criteria intelligent approach

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    The aim of this paper is to provide a multi-criteria decision-making intelligent approach based on Industry 4.0 and Triple Bottom Line principles for sustainable supply chain development in the renewable energy sector. In particular, the solar photovoltaic energy supply chain is used as a case study, encompassing the entire energy production process, from supply to disposal. An exhaustive literature review is conducted to identify the main criteria affecting social, economic and environmental sustainability in the photovoltaic energy supply chain, and to explore the potential impact of Industry 4.0 on sustainability. Subsequently, three Fuzzy Inference Systems combining quantitative and qualitative data are built to calculate the supply chain's social, economic and environmental sustainability. Experts' opinions are used to identify the impact of Industry 4.0 technologies on the three pillars of sustainability for each supply chain stage. Finally, a novel sustainability index, Sustainability Index 4.0, is formulated to compute the overall sustainability of the photovoltaic energy supply chain in seven countries. The results show the applicability and usefulness of the proposed holistic model in helping policy makers, stakeholders and users to make informed decisions for the development of sustainable renewable energy supply chains, taking into account the impact of Industry 4.0 and digital technologies

    Supply Chain Design and Multi-objective Optimisation with the Bees Algorithm

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