Abstract
Industry 4.0 has taken extraordinary importance in massive production strategies. This new revolution represents automation in factories and interconnectivity among devices and procedures. In a technological framework, when managing large amounts of data combined with in-depth statistical analysis as a convenient tool for decision-making, Industry 4.0 modeling constitutes an indispensable support. This chapter has the objective to present, in a comprehensive way, the role of statistical analysis in a steepest ascent innovative strategy for the Industry 4.0 modeling based on released information from a production system. The method analyzes the route that data follows from a production system to a computer software for statistical analysis. This includes empirical techniques such as designed experimentation. After this procedure, human intervention exists only for consecutive analysis and decision-making purposes. Results and conclusions are disclosed at the end of this document.
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García-Nava, P.E., Rodríguez-Picón, L.A., Méndez-González, L.C., Pérez-Olguín, I.J.C., Romero-López, R. (2023). The Technological Role of Steepest Ascent Optimization in Industry 4.0 Modeling. In: Méndez-González, L.C., Rodríguez-Picón, L.A., Pérez Olguín, I.J.C. (eds) Innovation and Competitiveness in Industry 4.0 Based on Intelligent Systems. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-031-29775-5_7
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