The demand for products continues to increase in today’s society, and to meet this demandcompanies are searching for new ways to improve the performance of their workers.Therefore, there is a constant push to develop and implement new technological solutionswithin the Industry 4.0 approach. The aim of this study is to research the different pathwaysone could take when implementing these technological solutions and what challenges itwould entail, with a focus on Artificial Intelligence (AI). This is done in collaboration withSaab Surveillance within their production division, who wishes to increase theirperformance within their white-collar environment. In this study, performance is defined andmeasured through productivity. The main indicators of productivity will, therefore, be timededicated to a task as well as the potential to improve the quality of a task. The result of thisstudy is presented with a roadmap framework where seven key areas, i.e., work processes,were discovered that could benefit from AI applications. These areas were uncovered byconducting a contextual inquiry and semi-structured interviews, and were then matched withrelevant AI applications. The discovered key areas are categorized based on a cost-benefitanalysis, with the scale of; low, medium, and high. The roadmap illustrates in which areas itcould be most beneficial to implement the suggested AI applications. Using this study, Saaband other companies can make more informed decisions on the pathways for adopting newtechnological solutions that will improve the performance of their white-collar workers.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:uu-531147 |
| Date | January 2024 |
| Creators | Boström, Gustav, Parker, Thomas |
| Publisher | Uppsala universitet, Avdelningen Vi3 |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | UPTEC STS, 1650-8319 ; 24023 |
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