Abstract:The future of machine tools will be dominated by highly flexible and interconnected systems, in order to achieve the required productivity, accuracy, and reliability. Nowadays, distortion and vibration problems are easily solved in labs for the most common machining operations by using models based on the equations describing the physical laws of the machining processes; however, additional efforts are needed to overcome the gap between scientific research and real manufacturing problems. In fact, there is an increasing interest in developing simulation packages based on "deep-knowledge and models" that aid machine designers, production engineers, or machinists to get the most out of the machine-tools. This article proposes a methodology to reduce problems in machining by means of a simulation utility, which uses the main variables of the system and process as input data, and generates results that help in the proper decision-making and machining plan. Direct benefits can be found in (a) the fixture/clamping optimal design; (b) the machine tool configuration; (c) the definition of chatter-free optimum cutting conditions and (d) the right programming of cutting toolpaths at the Computer Aided Manufacturing (CAM) stage. The information and knowledge-based approach showed successful results in several local manufacturing companies and are explained in the paper.
The goal of the research presented in this paper is to design and incorporate new technologies into railway bogie-mounted sensors. It is often impossible to connect the mounted systems to physical wires due to their location in an inaccessible position or the distance to the energy source. Therefore, another power source must be used to solve this problem. Energy harvesting technology is an increasingly popular solution that extracts energy from the ambient environment and transforms it into electrical energy. Using piezoelectric transducers, it is possible to transform the vibrations experienced by the bogie into energy that can be used to power the sensors. A prototype with multiple piezoelectric transducers has been designed, built and subjected to tests to validate the technology. The experimental results for all of the different configurations tested and levels of energy collected are presented.
Abstract:The next future using machine tools will be dominated by highly flexible and interconnected systems, in order to achieve the required productivity, accuracy and reliability. Nowadays, distortion and vibration problems are easily solved for the most common cases by sing models based on equations describing the physical laws dominating the machining process; however additional efforts are needed to overcome the gap between scientific research and the real manufacturing problems. In fact, there is an increasing interest in developing simulation packages based on "deep knowledge and models" that aid the machine designer, the production engineer, or machinists to get the best of their machines. This article proposes a systematic methodology to reduce problems in machining by means of a simulation utility, which recognizes, collects and uses the main variables of the system/process as input data, and generates objective results that help in the proper decision-making. Direct benefits by such an application are found in a) the fixture/clamping optimal design, b) the machine tool configuration, c) the definition of chatter free optimum cutting conditions and the right programming of cutting tool path at the Computer Aided Manufacturing (CAM) stage. The information and knowledge-based approach showed successful results in several local manufacturing companies.
A material based on recycled rubber has been developed to use as a protective coating on road barriers with the aim of improving motorcyclists' security against crash impacts. This material is based on grounded rubber from used tires added by extrusion using low-density polyethylene as adhesive. Compression tests have been performed for different densities of the recycled material to fully describe the mechanical characteristics under high strain rates (in the rank 0.057–5.7 s−1), and a constitutive model composed of a hyperelastic Mooney Rivlin part and a viscoelastic part based on the generalized Maxwell model has been taken to characterize this behavior. Hyperelastic parameters have been obtained by means of the least-squares fitting technique, and particle swarm optimization (PSO) has been used to obtain viscoelastic parameters. The PSO algorithm is shown to be a good optimization method, simple, versatile, and consisting of few parameters that accelerate to the optimal solution. Therefore, this article presents a new and efficient approach to obtaining the parameters for the viscoelastic model. The behavior of the experimental material confirms the theoretically obtained results, so the procedure presented in the article is validated successfully.
Boring operations of deep holes with a slender boring bar are often hindered by the precision because of their low static stiffness and high deformations. Because of that, it is not possible to remove much larger depths of cuts than the nose radius of the tool, unlike the case of turning and face milling operations, and consequently, the relationship between the cutting force distribution, tool geometry, feed rate and depth of cut becomes non-linear and complex. This problem gets worse when working with a rotating boring head where apart from the cutting forces and the variation of the inclination angle because of shape boring, the bar and head are affected by de centrifugal forces. The centrifugal forces, and therefore the centrifugal deflection, will vary as a function of the rotating speed, boring bar mass distribution and variable radial position of the bar in shape boring. Taking in to account all this effects, a load and deformation model was created. This model has been experimentally validated to use as a corrector factor of the radial position of the U axis in the boring head.
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