Abstract
The digitalization and evolution of information technologies within the industry 4.0 have allowed the creation of the virtual model of the production system, called Digital Twin, with the capacity to simulate different scenarios, providing support for better decision-making. This tool not only represents a virtual copy of the physical world that obtains information about the state of the value chain but also illustrates a system capable of changing the development of productive activity towards personalized production, extending product versatility. Decentralized production seeks to respond to these needs because it allows the agglomeration of several services with different geographic locations, promoting the sharing of resources. This paper proposes an architecture for the development of a digital platform of personalization and decentralization of production based on sharing of sustainable resources. With a single tool, it is possible to define the entire production line for a product. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
Industry 4.0 brought modernization to the productive system through the network integration of the constituent entities that, combined with the evolution of information technologies, allowed an increase in productivity, product quality, production cost optimization, and product customization to customer needs. In this paper a model was created using the open-source tool Knime that, based on a set of data provided by Bosch, parameterized the model with several pre-processing techniques, resource selection, and minimization of over-fitting, allowing the development of a final improved model for internal product failure prediction at Bosch production line. The study shows that model efficiency improved with the application of resource selection and reduction techniques, with Logistic Regression and PCA resource selection techniques standing out, obtaining a Recall of 100% and precision and accuracy, both with 99.43%. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
Energy and materials are increasingly important in industrialized countries, and they impact the economy, sustainability, and people's future. The purpose of this work was to study the relationship between energy and the circular economy using methods such as Pearson's correlation and a principal component analysis. Thus, 12 strong correlations were found, with 5 of them between the following relevant variables from two different subjects: the correlations of the raw material consumption, the domestic material consumption, and the material import dependency with the final energy consumption in transport (0.81, 0.92, and 0.81); the correlation of the circular material use rate with the final energy consumption in households (0.70); and the correlation of the material import dependency with the final energy consumption in industry (0.89). The time series forecast was only conclusive for the waste generated, showing that it will increase in the next 10 years.