© 2023, Emerald Publishing Limited.Purpose: The purpose of this paper is to present a practical data-based framework for the prioritization of investment in manufacturing technologies, methods and tools, and to demonstrate its applicability and practical relevance through two case studies of manufacturing firms of different industrial segments. Design/methodology/approach: The proposed framework is based on network theory applied on technology adoption. For this, the database of Industry 4.0 maturity assessments of SENAI was used to develop data visualization tools named “Technology Networks”. Thus, this study is descriptive research with correlational design. Besides, the framework was applied in two companies and semi-structured interviews were carried out with domain experts. Findings: The technology networks highlight the technological adoption patterns of six industrial segments, by considering the answers of 863 Brazilian companies. In general, less sophisticated technologies were positioned in the center of the networks, which facilitates the visualization of adoption paths. Moreover, the networks presented a well-balanced adoption scenario of Industry 4.0 related technologies and lean manufacturing methods and tools. Research limitations/implications: Since the database was not built under an experimental design, it is not expected to make statistical inferences about the variables. Furthermore, the decision to use an available database prevented the editing or inclusion of technologies. Besides, it is estimated that the technology networks given have few years for obsolescence due to the fast pace of technological development. Practical implications: The framework is a tool that may be used by practicing manufacturing managers and entrepreneurs for taking assertive decisions regarding the adoption of manufacturing technologies, methods and tools. The proposition of using network theory to support decision making on this topic may lead to further studies, developments and adaptations of the framework. Originality/value: This paper addresses the topics of lean manufacturing and Industry 4.0 in an unprecedented way, by quantifying the adoption of its technologies, methods and tools and presenting it in network visualizations. The main value of this paper is the comprehensive framework that applies the technology networks for supporting decision making regarding technology adoption.

© 2023 International Committee on Composite Materials. All rights reserved.The transport sector has long had a demand for weight reduction, typically achieved by changing materials or reducing part thickness. Steel and aluminum are the primary materials used in this sector. However, advancements in Fiber Reinforced Polymers (FRPs) technology have allowed for their application in non-structural parts of commercial vehicles and airplanes. The challenge is applying FRPs to structural parts while satisfying requirements for structural performance, quality, and production rate. To achieve both, the manufacturing processes involved must be carefully investigated, including the machining process. This work presents an experimental milling approach to investigate six factors' influence on the quality and production rate of a unidirectional CFRP part. The experiments were conducted using a traditional milling machine tool and a robot-based milling cell. The main objective is to achieve maximum material removal while maintaining defined part quality parameters.

© 2022 ESREL2022 Organizers. Published by Research Publishing, Singapore.Health specialists deal with unsafe situations that are conducive to health risks, including the pressures and demands of the practice itself and the full situation of the COVID-19 pandemic, this ends up promoting the increase of psychological disorders, such as anxiety and depression. This study aimed to evaluate the workload conditions of agents within the UBSs, applying the NASA-TLX method. As a field analysis, a case study was prepared and the NASA-TLX evaluation method was applied in a UBS, in the city of Franca - SP, the workload of the employees of this UBS was compared in the COVID-19 vaccination activities, in that employees apply COVID-19 vaccines to the public, and in the COVID 19 service/queue organization, in which employees explain, talk and answer questions from the population about how to organize the queues for the application of COVID-19 vaccines. It was concluded that the workload is excessive in both tasks, that the physical performance in the vaccination activity was superior to the service required to the public, and that the effort in the service activity was greater than in the vaccination activity. In addition, the level of achievement, or self-performance, scale was identified as the minimum intensity for both tasks, which can be justified because they are practical and routine actions, not requiring much of self- performance.

© 2013 IEEE.Industry 4.0 is a socioeconomic phenomenon that affects all industries, transforming not only products, processes, and services, but also business models, organizational structures, and strategies, placing human beings at the center of this digital transformation. Researchers have already demonstrated the importance of intangible resources in the Industry 4.0 adoption process. Nevertheless, there is still a gap in empirical research on how these factors evolve during the process. Therefore, the main objective of this study is to identify how these factors influence each other across different Industry 4.0 maturity levels. To achieve this goal, a qualitative approach was used with multiple case studies comparing responses from companies at higher Industry 4.0 maturity levels and contrasting them with the responses from companies at lower levels, distilling aggregate dimensions through an inductive coding procedure. Experts evaluated the results to find relations between the aggregate dimensions, their evolution and influence on each other. As a result, a conceptual framework was developed that demonstrates the dynamics of intangible factors that could be used by any company to nurture its own Intellectual Capital as a groundwork for the adoption of Industry 4.0. Among these dynamics, the central role of engaged leaders was highlighted in developing structural capital factors. Future studies should conduct interviews with more companies from other industrial sectors as well as on the implementation and management of Intellectual Capital in manufacturing companies to assess the applicability of the proposed conceptual framework.