School of Mechanical and Industrial Engineering

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Browsing School of Mechanical and Industrial Engineering by Subject "Additive manufacturing"

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    Adoption of Additive Manufacturing for Auto Parts Production: Case of Bishoftu Automotive and Manufacturing Industry
    (Addis Ababa University, 2023-10) Sultan Asefa; Ameha Mulugeta (PhD)
    This study investigates the adoption of additive manufacturing in the Bishoftu Automotive Industry in Ethiopia. The study applies an integrated framework of Diffusion of Innovation (DOI) and Technology-Organization-Environment (TOE). This study also used combined data from primary and secondary sources using quantitative and qualitative methodologies to allow for the exploration of the factors and constraints influencing the decision to adopt additive manufacturing. Additionally, the research undertakes a thorough literature analysis of Adoption theories such as DOI, TOE, and factors affecting additive manufacturing adoption. Five point Likert scale was the method used to collect the useful information for this study. The questionnaire was distributed to managers, engineers, and technicians in the Bishoftu Automotive and Manufacturing Industry. Subsequently, the collected data was subjected to analysis through the application of descriptive statistics and partial least squares structural equation modeling (PLS-SEM) utilizing SPSS version 27 and SmartPLS version 4.0.9.6 software. The study outcomes revealed that several critical determinants significantly impact the adoption of additive manufacturing (AM) in the automotive sector. These determinants encompass relative advantage, compatibility, complexity, trialability, observability, technology-related factors, and organizational as well as environmental factors The results of this study enhance our understanding of the adoption of additive manufacturing and provide valuable practical guidance for decision-makers within the Bishoftu Automotive Industry. Drawing from these findings, recommendations have been formulated to facilitate the effective integration of AM in the automotive sector. Additionally, this study identifies potential areas for future research in this field.