Publicação
Augmented Intelligence in Logistics: A methodology to assess the reliability of Augmented Intelligence in logistic processes
| Resumo: | This thesis explores the integration of Augmented Intelligence (AuI) in logistics, aiming to enhance the collaboration between human expertise and advanced machine learning technologies. The primary objective is to develop a robust methodology for assessing the feasibility and effectiveness of AuI integration within logistics processes. The proposed methodology was evaluated through interviews with logistics and IT experts, providing insights into its practical applicability and areas for improvement. The feedback highlighted the necessity for systematic project management, thorough validation of company-specific processes, and a comprehensive understanding of existing systems and their interrelations. These insights led to recommendations for enhancing the methodology's flexibility, empirical validation, and customization to fit diverse organizational needs. The findings suggest that AuI can significantly improve decision-making, operational efficiency, and overall productivity in logistics. However, successful integration requires careful planning, continuous improvement mechanisms, and alignment with strategic business objectives. This thesis concludes with recommendations for future research, emphasizing the need for in-depth case studies, longterm impact assessments, and the development of performance metrics tailored to AuI applications in logistics. By addressing these aspects, this research contributes to the growing body of knowledge on AuI and its transformative potential in the logistics sector, paving the way for more intelligent, efficient, and adaptive logistics operations. |
|---|---|
| Autores principais: | Samsonyuk, Ivan Sergievich |
| Assunto: | Logistics Supply Chain Augmented Intelligence Artificial Intelligence SDG 8 - Decent work and economic growth SDG 17 - Partnerships for the goals |
| Ano: | 2024 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade Nova de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório Institucional da UNL |
| Resumo: | This thesis explores the integration of Augmented Intelligence (AuI) in logistics, aiming to enhance the collaboration between human expertise and advanced machine learning technologies. The primary objective is to develop a robust methodology for assessing the feasibility and effectiveness of AuI integration within logistics processes. The proposed methodology was evaluated through interviews with logistics and IT experts, providing insights into its practical applicability and areas for improvement. The feedback highlighted the necessity for systematic project management, thorough validation of company-specific processes, and a comprehensive understanding of existing systems and their interrelations. These insights led to recommendations for enhancing the methodology's flexibility, empirical validation, and customization to fit diverse organizational needs. The findings suggest that AuI can significantly improve decision-making, operational efficiency, and overall productivity in logistics. However, successful integration requires careful planning, continuous improvement mechanisms, and alignment with strategic business objectives. This thesis concludes with recommendations for future research, emphasizing the need for in-depth case studies, longterm impact assessments, and the development of performance metrics tailored to AuI applications in logistics. By addressing these aspects, this research contributes to the growing body of knowledge on AuI and its transformative potential in the logistics sector, paving the way for more intelligent, efficient, and adaptive logistics operations. |
|---|