Ingeniería de competencias en procesos de fabricación desde industria 4.0. Aplicación al grado de ingeniería mecánica

Resumen

In the Horizon 2030 it is foreseen that industries will be increasingly influenced by Key Enabling Technologies (KETs), working at macro and micro scales as a cyber-physical system to blend in with the context of which they are part, and even with locations in urban areas. This determines their flexible adaptation to consumer demands, basing their organisational and productive strategies on intensive knowledge systems supported by artificial intelligence, which must support functions as training centres under dual training models, functions to which it is necessary to add the effective integration between the human and technological factors typical of the 5.0 industry. Manufacturing 4.0 systems, and their projection into Manufacturing.5.0, must be equipped with the capacity to adapt to volatile, uncertain, complex and ambiguous (VUCA) contexts, which means an evolution of the skills associated with 4.0 operators, in order to successfully tackle open, more complex problems that require more creative solutions, transforming them into 5.0 operators. In this sense, the rapprochement between the human and technological factors, mediated through neuroadaptative interfaces, allows the existing gap between companies, workers and institutions to be bridged. For this convergence to be possible, it will require unprecedented innovation and must be tackled with new models and frameworks that integrate scientific and technical areas in a multi- and trans-disciplinary manner. Therefore, a new model of organization of the instructional practice is required, in the university and business field as Sociotechnical Cybephysical Manufacturing Systems, which with the help of the KETs will be aligned with the objectives of conceiving Sociotechnical Cybephysical Manufacturing Systems focused on the human factor. In order to adopt this new approach, in which the continuous acquisition of new skills and the real-time reconfiguration of manufacturing systems are crucial, it is essential to design the operational environment with a high demand for innovation and creativity. This makes it necessary to design Sociotechnical Cybephysical Manufacturing Systems with adaptive human-technological interfaces that support the resolution of problems in real time, making this system co-evolve towards the desired end, so as to facilitate the adaptive coupling between the human and technological factors for the best performance of the tasks to be carried out. For this purpose, the application of the contributions of neuroscience and its associated techniques has been taken into account, which has required the updating of the concept of competence by that of neurocompetence, associating the acquisition of knowledge, skills and abilities with neurocognitive and neurobiological components. To this end, neuroinstruction is conceived as a symbiotic connector between the neurocognitive processes on which the activity of construction, application and development of competences is based. The approach to training in competencies, with no solution to the continuity of instruction in the academic, professional and dual fields, makes it necessary to develop a model of Neurocompetence Engineering and Neuroinstruction Engineering focused on the human factor through the Design for Human Factor in Industry 4.0 framework (DfHFinI4.0). All this allows us to explain the relationships established between the elements of the Sociotechnical Cybephysical Manufacturing Systems and its modelling based on the characteristics of the student/operator 4.0 towards its transition to 5.0, as well as the task to be performed, with the help of adaptive interfaces that act in real time. This model of Neuroinstructional Engineering integrates the conceptual frameworks of the Activity Theory and the Law of Requisite Variety, which incorporates technologies and methodologies for the acquisition of neurocompetences through the use of the connective paradigm, taking into account its development under criteria of minimal complexity based on its fractal-simplex character. For its implementation with intelligent ICTs, the construction of KBS is proposed, under the MAS-CommonKADS methodology and the distributed cyberphysical systems. This allows the neuroinstructional environments designed under the proposed Neuroinstruction Engineering model to facilitate learning situations based on digital twins of students and 4.0 operators in the Cloud. The above can be integrated into PERA 4.0 Manufacturing Systems Reference Architectures. To validate and verify the potential and scope of the Neuroinstruction Engineering model, a neuroinstruction situation is designed and developed containing the implementation of the e-Turning App, which includes various tools to guide the engineer in his learning.