Induction hardening is a heat treatment that has been increasingly employed in the industry in recent years. It is a complex, highly coupled, and multiphysical process involving electromagnetism, thermal, mechanical, and metallurgical physics. One of the main quality requirements of the process is the hardened case depth generated in the workpiece. The usual method to measure the hardened case and ensure the quality of the parts is to use destructive techniques, which generate material and energy waste and production inefficiencies. Additionally, selecting process parameters such as current, frequency, or scanning speed typically requires several trial-and-error iterations. The goal of this work is to provide a hybrid digital twin (DT) that acts as a nondestructive test technique, predicting the resulting hardened case in real-time and enabling the correction of process parameters during the induction hardening process, ultimately achieving a zero-waste manufacturing scheme. For this purpose, a DT based on an artificial neural network (ANN) model is developed, predicting the hardened case depth in real-time using four monitored input variables: induction frequency, current, and two temperature measurements on the surface of the hardened part. The required data for DT development and training are obtained using a finite element model. Several ANN architectures are evaluated, and the configuration with the best regression results is chosen for implementation in an industrial induction hardening machine. The hardened case predictions obtained from the developed DT demonstrate high accuracy within the analyzed frequency and current range.

Mechanical clearances are present in mechanical systems due to manufacturing tolerances, assembly imperfections, wear, and material deformation. Their presence can significantly influence dynamic behavior, vibration levels, and long-term component performance. As a result, the characterization, monitoring, and estimation of clearances have become important research topics. Considerable research has been devoted to the dynamic analysis of mechanical systems with clearances using multibody formulations, while more recent studies have explored hybrid model-based estimation techniques and data-driven methods for clearance identification. The development of such approaches requires experimental platforms capable of systematically reproducing and investigating clearance-induced dynamic behaviors. This work presents the development of a configurable slider–crank test bench designed for experimental investigation of mechanical clearance, which allows the selection of clearance location and magnitude, operating speed, and mechanism orientation. A multibody model was developed to support the system design, monitor its operation, and provide a numerical reference for the obtained experimental data, retrieved from accelerometers and encoders. The results obtained during experimental tests demonstrate that the platform generates repeatable measurements while remaining sensitive to variations in operating conditions and clearance configurations. Results also served to assess the ability of multibody formulations and clearance modeling approaches to correctly characterize the dynamic effects caused by joint clearances. Formulations that describe the system motion using minimal coordinates resulted in reduced uncertainty in simulation results. The selected contact models succeeded at capturing the effect of revolute joint clearances on the accelerations of the mechanism, establishing a first step in the detailed description of the contact dynamics that is necessary for the use of forward-dynamics simulation results in the development of hybrid model-based and data-driven clearance characterization methods.

La aparición de holguras por desgaste en la maquinaria industrial tiene un impacto importante ensu rendimiento y vida útil. Una holgura reduce la eficiencia de la máquina y provoca incrementosde temperatura, ruidos y vibraciones, lo que puede dañar ciertos componentes o causar el falloprematuro del equipo. Para reducir estos efectos, es necesario efectuar tareas de mantenimiento deforma regular. El proceso de caracterización de las holguras y su simulación ha sido objeto de estudio de lacomunidad de dinámica multicuerpo. Los métodos propuestos requieren una descripción precisa dela dinámica de los sólidos unidos por las juntas con holgura. La representación de este fenómenoen la simulación depende de la selección de varios parámetros que caracterizan la geometría de laholgura. En la práctica, estos parámetros son complejos de obtener y pueden variar durante eltiempo debido, por ejemplo, a cambios en las condiciones de operación de la máquina. Además,muchos de estos parámetros no se pueden medir directamente mediante sensores. Los observadores de estados, como los basados en el filtro de Kalman, se emplean para estimarvariables o parámetros que no se conocen con certeza, lo que los convierte en una alternativa paradetectar la presencia de holguras en un mecanismo. Los filtros de Kalman se han empleado conmodelos multicuerpo para estimar fuerzas y parámetros de configuración de modelos, además delpropio estado del sistema. Sin embargo, aún no se han aplicado al ámbito de las holguras de formasistemática, especialmente en el contexto de montajes experimentales. Los primeros pasos haciauna solución siguiendo el enfoque de estimadores implica la selección de los métodos másadecuados para cuantificar el problema de la holgura de forma directa, incluyendo la selección desensores, tipo de filtro y la identificación de las magnitudes más relevantes del problema. En este trabajo, la máquina objeto de estudio se basa en un mecanismo de biela-manivela. Se hacombinado un modelo ideal del mecanismo con un filtro de Kalman extendido consiguiendo estimarlas fuerzas en la holgura. El siguiente paso es conseguir estimar el tamaño de la holgura, para loque se están estudiando diferentes alternativas, como la estimación de parámetros mediante unfiltro de Kalman “unscented”. De esta forma, será posible monitorizar la aparición y evolución deholguras con el fin de evitar daños críticos en la maquinaria.