Abstract Intro: Conventional training methods are intended to teach and offer the most human way of teaching but is it the most effective and can another method improve or eliminate nonvalue adding activities. This master thesis tackles the difference between traditional training versus AR supported training, studying different aspects of training to see the advantages and disadvantages of the methods. The research questions were the following: RQ1: Is the learning process improved with or without AR supported technology? RQ2: What are the benefits of AR use in industry? RQ3: Will the investment of AR implementation in the learning process pay off? Method: To answer the research questions, a case study at a case company was conducted. The case study consisted of working with two companies, an external company for a theoretical answer based on experiences and an experimental study at the internal case company. In parallel to this case study a literature review was done to answer the research questions. Theory and Literature Review: Literature for the frame of reference was gathered to support the thesis and give the perspectives of the investigated area. The literature review sought to find answers to the research questions and the search was systematically formed to focus on data gathering to answer the questions. Analyses: The findings from this research shows that AR supported training is beneficial and has the potential to eliminate nonvalue adding activities. AR has many capabilities and research shows that AR in general has positive impact. Conclusion: AR-applied training has both advantages and disadvantages, but the potential of improvements is high. It is difficult to conclude if it is economical to invest in AR, with the advances the technology holds on to now since the outcome can depend on several factors from different parameters. However, AR does contribute to more effective learning and further benefits within the applied area. It has been proven to reduce the error rate and thus may increase the quality of the product.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:mdh-57619 |
Date | January 2022 |
Creators | Joseph Christian, Haranya, Mani, Sofia |
Publisher | Mälardalens universitet, Akademin för innovation, design och teknik |
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 |
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