In the rapidly evolving landscape of Industry 4.0, companies deal with cognitive shifts, where effective Knowledge Management becomes crucial. Within this dynamic context, dialog systems, known for their proficiency in engaging in human conversation, could offer potential support. Nevertheless, the current methodology involves manual coding and necessitates human intervention to formulate exhaustive questions and answers and orchestrate interactions. This procedural approach, aside from being time-intensive, faces drawbacks in terms of scalability. Therefore, this project aims to explore the transformative potential of replacing traditional written procedures with dynamic conversational scenarios for chatbots in the industrial maintenance setting. Thanks to NLP and machine learning techniques, the primary objective is to develop a chatbot capable of comprehending and responding to user technical inquiries in a more human-like and efficient manner.