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Exploring Retrieval-Augmented Generation (RAG) for AI Applications in the Manufacturing Industry
University West, Department of Engineering Science.
University West, Department of Engineering Science.
2025 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

In recent years, the use of generative AI has increased rapidly. Studies show that it can improve productivity of workers, but it can be difficult to know how and where to implement AI solutions. This thesis evaluates how a Retreival-Augmented Generation based system can improve productivity at KraftPowercon, a Swedish manufacturer of electric power-processing solutions. This study also explores what other possible uses of AI based systems that KraftPowercon might have through interviews with employees at the company. Results from tests show that a RAG based system can provide meaningful support for docomunt-intensive tasks and insights from employees confirms a interest in AI-assisted tools across departments with desire for system that streamline documentation access, support troubleshooting and reduce repetetive tasks

Place, publisher, year, edition, pages
2025. , p. 44
Keywords [en]
Retrieval-Augmented Generation, (RAG), AI Application, Manufacturing Industry
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:hv:diva-23727Local ID: EHD500OAI: oai:DiVA.org:hv-23727DiVA, id: diva2:1981497
Subject / course
Computer engineering
Educational program
Datateknik - högskoleingenjör
Supervisors
Examiners
Available from: 2025-07-22 Created: 2025-07-04 Last updated: 2025-09-30Bibliographically approved

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