1,721,348 research outputs found
Statistical analysis of MIG-laser CO2 hybrid welding of Al–Mg alloy
No full textStatistical based experimental analysis techniques are particularly useful in the engineering world for improving the understanding of the manufacturing processes and the development of new ones. In this paper the innovative arc-laser welding process (hybrid welding) is investigated by means of a regression model and a full factorial experiment. Both the regression model and the factorial experiment output were checked by the analysis of variance. In particular the main effects and interactions between process parameters on weld penetration for 3 mm 5005 Al-Mg alloy bead-on-plate samples were calculated and plotted. The results showed the significance of some parameters and indicated the way to maximize the weld penetration
[INVITED] Computational intelligence for smart laser materials processing
No full textComputational intelligence (CI) involves using a computer algorithm to capture hidden knowledge from data and to use them for training âintelligent machineâ to make complex decisions without human intervention. As simulation is becoming more prevalent from design and planning to manufacturing and operations, laser material processing can also benefit from computer generating knowledge through soft computing. This work is a review of the state-of-the-art on the methodology and applications of CI in laser materials processing (LMP), which is nowadays receiving increasing interest from world class manufacturers and 4.0 industry. The focus is on the methods that have been proven effective and robust in solving several problems in welding, cutting, drilling, surface treating and additive manufacturing using the laser beam. After a basic description of the most common computational intelligences employed in manufacturing, four sections, namely, laser joining, machining, surface, and additive covered the most recent applications in the already extensive literature regarding the CI in LMP. Eventually, emerging trends and future challenges were identified and discussed
Advances in Welding Metal Alloys, Dissimilar Metals and Additively Manufactured Parts
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Computationally Distributed, Self-Organizing Control of Manipulators in the Operational Space
No full textA Novel Practical Technique to Integrate Inequality Control Objectives and Task Transitions in Priority Based Control
No full textThe task priority based control is a formalism which allows to create complex control laws with nice invariance properties, i.e. lower priority tasks do not affect the execution of higher priority ones. However, the classical task priority framework (Siciliano and Slotine) lacked the ability of enabling and disabling tasks without causing discontinuities. Furthermore, tasks corresponding to inequality control objectives could not be efficiently represented within that framework. In this paper we present a novel technique to integrate both the activation and deactivation of tasks and the inequality control objectives in the priority based control. The technique, called iCAT (inequality control objectives, activations and transitions) task priority framework, exploits novel regularization methods to activate and deactivate any row of a given task in a prioritized hierarchy without incurring in practical discontinuities, while maintaining as much as possible the invariance properties of the other active tasks. Finally, as opposed to other techniques, the proposed approach has a linear cost in the number of tasks. Simulations, experimental results and a time analysis are presented to support the proposed technique
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