The possibility of implementing intelligent systems and the respective impact of artificial intelligence on inventory management and warehousing

• Autor(a) principal: Gonçalves, Mafalda Correia Piçarra
• Data de Publicação: 2022
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10071/25016
• topic: Artificial intelligence; Stock management; Warehousing; Industry 4.0; Inteligência artificial; Gestão de stocks; Gestão de armazém; Indústria 4.0

The industry is in a new phase: Industry 4.0. This fourth industrial revolution focuses on improving processes within industries. The basis for this improvement is artificial intelligence, which, by digitizing the operations of companies operating in different sectors, improves their productivity, innovation, reduces costs and improves their markets on the international stage. In the context of retail companies, the sourcing and storage of products is one of the most important operations. Thus, this study intends to investigate the concept of artificial intelligence, that is, its benefits, trust, and risks to, consequently, analyze the possibility of its application in stock and storage management. The first phase of the study underwent a literature review, where all these aspects were thoroughly analyzed. Then, to collect data and reach conclusions, two methodologies were used: an online questionnaire and interviews. After analyzing the outputs of the online questionnaire, it was concluded that Artificial Intelligence has benefits and trust indicators that positively influence its implementation in stock and warehouse management. Regarding the interviews, these reveal that Artificial Intelligence is beginning to be recognized for its advantages, but it is still seen as a large investment, especially for small industrial companies. However, the applications that are taking place are considered by AI experts as beneficial, being machine learning, robotics and computer vision technologies that can enhance the productivity of the logistics operations addressed in this investigation.