Publicação
Evaluation and development of a production system with CNC machines for SMEs in the context of the concept of Industry 4.0
| Resumo: | This thesis explores the integration of CNC machines into the framework of Industry 4.0, with a focus on the challenges and opportunities for small and medium-sized enterprises (SMEs). As Industry 4.0 promotes the digital transformation of traditional manufacturing processes through technologies like the Internet of Things (IoT), artificial intelligence (AI), and cyber-physical systems (CPS), SMEs must adapt to these innovations to remain competitive. The research addresses the development of solutions for improving production systems using CNC machines within SMEs. The study provides a comprehensive review of CNC machine technologies and their evolution in the context of Industry 4.0. Examining key types of CNC machines, such as lathes, milling, bending, and punching machines, the research delves into how these machines can be improved through digital connectivity and advanced automation. Furthermore, the work analyses the integration of CNC systems with Industry 4.0 technologies like CAM and MES, outlining their potential to transform manufacturing processes to work smarter. A significant portion of the research focuses on the barriers SMEs face in adopting Industry 4.0 technologies, including high costs, lack of skilled labour, and limited access to the necessary infrastructure. However, the study also identifies opportunities, such as cost savings from predictive maintenance, improved operational efficiency, and the potential for customized production. Through a combination of literature review, observation and a questionnaire survey for SMEs, the research provides insights into how SMEs can incrementally adopt these technologies, while also addressing the unique constraints they face. In conclusion, this thesis contributes valuable knowledge to the field of smart manufacturing, offering a framework for SMEs to successfully implement Industry 4.0 technologies in their production systems. Proposing a model of Smart Factory for integrating CNC machines with digital technologies, the work highlights the potential benefits for SMEs, for increasing of productivity and competitiveness. |
|---|---|
| Autores principais: | Neto, Acendino Alves da Silva |
| Assunto: | CNC (Computer Numerical Control) CNC Machines Industry 4.0 SME (Small-medium enterprise) Smart Factory CNC (Controlo Numérico de Computadorizado) Indústria 4.0 Fábrica Inteligente Engenharia e Tecnologia::Outras Engenharias e Tecnologias |
| Ano: | 2025 |
| País: | Portugal |
| Tipo de documento: | tese de doutoramento |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade do Minho |
| Idioma: | inglês |
| Origem: | RepositóriUM - Universidade do Minho |
| Resumo: | This thesis explores the integration of CNC machines into the framework of Industry 4.0, with a focus on the challenges and opportunities for small and medium-sized enterprises (SMEs). As Industry 4.0 promotes the digital transformation of traditional manufacturing processes through technologies like the Internet of Things (IoT), artificial intelligence (AI), and cyber-physical systems (CPS), SMEs must adapt to these innovations to remain competitive. The research addresses the development of solutions for improving production systems using CNC machines within SMEs. The study provides a comprehensive review of CNC machine technologies and their evolution in the context of Industry 4.0. Examining key types of CNC machines, such as lathes, milling, bending, and punching machines, the research delves into how these machines can be improved through digital connectivity and advanced automation. Furthermore, the work analyses the integration of CNC systems with Industry 4.0 technologies like CAM and MES, outlining their potential to transform manufacturing processes to work smarter. A significant portion of the research focuses on the barriers SMEs face in adopting Industry 4.0 technologies, including high costs, lack of skilled labour, and limited access to the necessary infrastructure. However, the study also identifies opportunities, such as cost savings from predictive maintenance, improved operational efficiency, and the potential for customized production. Through a combination of literature review, observation and a questionnaire survey for SMEs, the research provides insights into how SMEs can incrementally adopt these technologies, while also addressing the unique constraints they face. In conclusion, this thesis contributes valuable knowledge to the field of smart manufacturing, offering a framework for SMEs to successfully implement Industry 4.0 technologies in their production systems. Proposing a model of Smart Factory for integrating CNC machines with digital technologies, the work highlights the potential benefits for SMEs, for increasing of productivity and competitiveness. |
|---|