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Simulation of Cold Forging Processes Using a Mixed Isotropic-Kinematik Hardening Model
Full text linkCold forging is a manufacturing process where a bar stock is inserted into a die and squeezed with a second closed die. It is one of the most widely used chipless forming processes, often requiring no machining or additional operations to get tight tolerances. Because materials to be formed are increasingly harder and the geometrical complexity is greater, the finite element simulation is becoming an essential tool for process design. This study proposes the use of the Chaboche hardening model for the cold forging simulation of a 42CrMoS4Al material industrial automotive ball pin. The material model has been fitted with experimental data obtained from cyclic torsion tests at different reversal plastic strains as well as monotonic torsion tests at different strain rates. Comparison between the classical isotropic hardening and the new mixed hardening model are presented for the different forging steps
Using Machine Learning to Build Test Oracles: an Industrial Case Study on Elevators Dispatching Algorithms
Full text linkThe software of elevators requires maintenance over several years to deal with new functionality, correction of bugs or legislation changes. To automatically validate this software, test oracles are necessary. A typical approach in industry is to use regression oracles. These oracles have to execute the test input both, in the software version under test and in a previous software version. This practice has several issues when using simulation to test elevators dispatching algorithms at system level. These issues include a long test execution time and the impossibility of re-using test oracles both at different test levels and in operation. To deal with these issues, we propose DARIO, a test oracle that relies on regression learning algorithms to predict the Qualify of Service of the system. The regression learning algorithms of this oracle are trained by using data from previously tested versions. An empirical evaluation with an industrial case study demonstrates the feasibility of using our approach in practice. A total of five regression learning algorithms were validated, showing that the regression tree algorithm performed best. For the regression tree algorithm, the accuracy when predicting verdicts by DARIO ranged between 79 to 87%
Abiadura handiko entseguak egiteko forjaketa-mailu baten garapena
Full text linkHammer forging is a widely employed manufacturing process to produce parts with excellent mechanical properties. In order to achieve an optimal process design, finite element modelling is broadly utilized in industry and research. It is well known that to obtain accurate simulation results, accurate material characterization have to be performed. Although material behaviour of metals under hammer forging conditions are of great industrial interest, few materials have been tested in such high strain rates due to the lack of laboratory machines for high-speed testing. With the objective of addressing that gap, this paper presents a novel automatic forging simulator comprised of an instrumented forging hammer capable of performing high-speed deformations. In this work, results of high strain rate tests performed on the developed hammer were evaluated obtaining promising conclusions.Mailu bidezko forjaketa prozesua era askotariko propietate mekaniko altuko piezak fabrikatzeko erabiltzen da. Forjaketa prozesu hauek egoki diseinatzeko, geroz eta gehiago erabiltzen dira elementu finitu bidezko simulazio softwareak. Software hauen sarrera-datuak egokiak izatea berebizikoa da simulazioen emaitzak fidagarriak izan daitezen, horien artean materialaren portaera definitzea atal garrantzitsuenetakoa delarik. Zoritxarrez, deformazio abiadura handian materialek duten portaera mekanikoa karakterizatzeko entsegu-makina komertzial oso gutxi daude. Hutsune hori betetzeko garatu den laborategi eskalako forjaketa-mailu berri bat aurkezten da artikulu honetan. Makina berri honetan egindako entseguetako emaitzen azterketa egin da, lortutako emaitzak itxaropentsuak izanik
Bemrosetta: An open-source hydrodynamic coefficients converter and viewer integrated with Nemoh and Foamm
Full text linkBoundary Element Method (BEM) solvers are extensively used to obtain the hydrodynamic coefficients required to model hydrodynamic forces in oating marine structures. BEM solvers require the discretization of the submerged device surface as a mesh to compute the hydro-dynamic coefficients as radiation damping and added mass, response amplitude operators and linear and second-order exciting forces. Each of these solvers need particular input files and mesh formats, and save the results in specific file formats. Typically, the input and output files are incompatible between different solvers. Researchers handle this problem by converting model results through homemade spreadsheets or macros made in scripting languages. BEMRosetta was created to allow loading and saving the input files, mesh geometries and the hydrodynamic coefficients, in different formats. Furthermore, it also includes a mesh viewer. Additionally, BEM-Rosetta can calculate di erent parameters from the mesh and the hydrodynamic coefficients. Through its integration with the Finite-Order hydrodynamic Approximation by Moment-Matching (FOAMM) toolbox, BEMRossetta allows the state- space model of the radiation convolution term for the desired degrees of freedom be obtained
Power Balancing in Cascaded H-Bridge and Modular Multilevel Converters Under Unbalanced Operation: A Review
Full text linkMultilevel Voltage-Source Converters (VSC) based on modular structures are envisioned as a prominent alternative for grid and industry applications. Foremost among these are the Cascaded H-Bridge (CHB) and the Modular Multilevel Converter (MMC). In this context, depending on the application and the power conversion structure, unbalanced operating conditions can be asked to the converter. Previous investigations regarding the operation and the solutions for modular structures under unbalanced conditions have already addressed this topic, but information is dispersed over a wide number of sources. This paper identifies, classifies, and analyzes the intercluster active power balancing strategies for the adequate operation of the most commonly used modular structures in some typical unbalanced operating scenarios: the Static Synchronous Compensator (STATCOM) under unbalanced voltage and/or current conditions, the unequal power generation in large-scale photovoltaic (PV) power plants, and the uneven power distribution in a battery energy storage system (BESS). Each of the applications has been independently studied so as to provide a comprehensive analysis of the alternative techniques found in the specialized literature, clearly explaining their respective strengths and drawbacks. Several future challenges have been identified
during the study, which will involve greater research effort in this key research topic
Trends and Proposals for European Industrial Engineering
Full text linkThis article analyses the trends in scientific publications (Web of Science) in the field of industrial engineering (IE) from 1950 to the present. Specifically, it presents the evolution of the emergence of ‘concepts’ associated with IE for decades, their quantitative or qualitative nature and the prominence of the different world regions in their origin. The analysis reveals a decline in the capacity of the academe and the industry to propose new ‘concepts’ during the last 20 years, a considerable variation of the leading role of world regions in IE and significant changes in the preponderance of IE ‘concepts’ with a quantitative or qualitative character. To foster the capacity of the IE academe in contributing to European industrial development, the transformations that the industry will have to face during the next decades are proposed as areas of development of the research activity. Enhancing training and research on the consequences of digitisation on industrial management, enlarging the optimization scope from company to value chain and industrial ecosystems and prioritizing research aimed at developing new ‘concepts’, methodologies and tools are suggested as some of the future paths for IE
Development and experimental validation of a macroscopic analytical model aiming to generate metal-FRP stacks drilling cutting force and torque
Full text linkComposites materials and especially FRP are increasingly employed in many fields of applications (transport, aerospace, …) due to the current trend of improving global energy performances of new designs notably by mass saving. However the use of metallic materials such as aluminum and titanium alloys is still necessary in many cases and a lot of structures are made of a dual technology called stacks (panels composed of different layers of FRP and metal bounded together). Combining the different properties of these materials offers many advantages regarding the mechanical and structural aspects. This is nevertheless for the same reason that machining and especially drilling stacks is a laborious task: the tools and cutting conditions are way too divergent to avoid vibrations, problems of dimensional tolerances and delamination of the composite. The knowledge and characterization of the drilling cutting forces is a first step to solve these issues. The purpose of this article is to provide an accurate macroscopic analytical model fitted for stacks and compare it quantitatively with experimental tests. The given model is divided in two parts (i.e. respectively adapted for the two materials) and is based on the discretization of the cutting edge. The proposed algorithm is able to predict accurately drilling force and torque along time in function of the cutting conditions, the tool and material configurations. A reverse least squared method is used to obtain the empirical input parameters, allowing to minimize the number of experimental drilling tests to obtain the empirical input parameters
Resonant Dual Active Bridge Partial Power Converter for Electric Vehicle Fast Charging Stations
Full text linkThis paper presents an analysis and design of a DC-DC charging unit for an electric vehicle fast charging station. Due to the benefits that partial power processing achieves in terms of size reduction and efficiency improvement, it is decided to implement a partial power converter architecture. This type of architectures reduce the power to be processed by the converter, but they require an isolated topology. Therefore, a dual active bridge series resonant converter is selected for the study due to its benefits in terms of soft switching conditions. Design wise, it is decided to ensure zero voltage switching at the secondary side of the converter. Indeed, one of the benefits of the implemented partial power converter is the reduced voltage that exists at the primary side. This way, lower voltage overshoots and switching losses are expected. Finally, via simulations, it is confirmed that partial power processing can be achieved with a resonant converter and that zero voltage switching operation is ensured at the secondary side through the entire charging process
Bibliometric analysis of consumer product interface accessibility evaluation tools
Full text linkWith the aging of the population the design of products whose interfaces are accessible becomes necessary. In this way as many people as possible could interact with the products. Inclusive Design works with this approach and the use of specific tools is an important resource. Thus, the aim of this paper is to identify the most interesting tools to use in the inclusive design processes of consumer product interfaces and to explore the opportunities for improving them. First, a literature review is carried out to identify the main tools used for interface accessibility evaluation. Then, each of them is analyzed and those that have been designed for the evaluation of the interfaces of consumer products are analyzed in depth. Thus, 21 tools are analyzed in detail and classified into 7 groups. In conclusion, exclusion calculation is identified as a concept for accessibility evaluation and the Exclusion Calculator as a tool to perform this calculation. In addition, improvement opportunities are proposed in order to strengthen the tool and the evaluation through it.Con el envejecimiento de la población el diseño de productos cuyas interfaces sean accesibles se convierte en necesario para que el mayor número de personas posibles puedan interactuar con los productos. El Diseño Inclusivo trabaja este enfoque y el uso de herramientas específicas resulta de gran ayuda. Así, el objetivo de este comunicado es identificar las herramientas más interesantes para usar en los procesos de diseño inclusivo de interfaces de productos de consumo y explorar las oportunidades de mejora de estas. Para ello, primeramente, se realiza una revisión bibliográfica a través de la cual se identifican las principales herramientas usadas para la evaluación de la accesibilidad de las interfaces. A continuación, se analiza cada una de ellas y se profundiza en aquellas que han sido pensadas para la evaluación de las interfaces de los productos de consumo. Así, son 21 las herramientas analizadas a detalle clasificándolas en 7 grupos. Como conclusión se identifica el cálculo de la exclusión como concepto para la evaluación de la accesibilidad y el Exclusion Calculator como herramienta para realizar dicho cálculo. Además, se proponen oportunidades de mejora de cara a reforzar la herramienta y la evaluación a través de ella
Machine Learning-Based Fault Detection and Diagnosis of Faulty Power Connections of Induction Machines
Full text linkInduction machines have been key components in the industrial sector for decades, owing to different characteristics such as their simplicity, robustness, high energy efficiency and reliability. However, due to the stress and harsh working conditions they are subjected to in many applications, they are prone to suffering different breakdowns. Among the most common failure modes, bearing failures and stator winding failures can be found. To a lesser extent, High Resistance Connections (HRC) have also been investigated. Motor power connection failure mechanisms may be due to human errors while assembling the different parts of the system. Moreover, they are not only limited to HRC, there may also be cases of opposite wiring connections or open-phase faults in motor power terminals. Because of that, companies in industry are interested in diagnosing these failure modes in order to overcome human errors. This article presents a machine learning (ML) based fault diagnosis strategy to help maintenance assistants on identifying faults in the power connections of induction machines. Specifically, a strategy for failure modes such as high resistance connections, single phasing faults and opposite wiring connections has been designed. In this case, as field data under the aforementioned faulty events are scarce in industry, a simulation-driven ML-based fault diagnosis strategy has been implemented. Hence, training data for the ML algorithm has been generated via Software-in-the-Loop simulations, to train the machine learning models