Impact of AI and Automation on Production Processes and Business Competitiveness in the Cycling Industry: A PRISMA Systematic Review
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- In a context where production is becoming more complex and personalized, and supply chains increasingly fragile, the cycling industry still relies heavily on manual processes and low digital integration. This thesis explores how automation and artificial intelligence (AI) can help modernize the sector and improve performance, while taking into account the reality of small manufacturers, limited resources, and product diversity. Based on a Systematic Literature Review (SLR) conducted using the PRISMA protocol, 42 recent scientific articles were analyzed. The study identifies the most relevant technologies (such as Digital Twins, predictive maintenance, and AI-driven quality control) and the conditions under which they can deliver real benefits: greater flexibility, improved quality, and faster responsiveness. It also draws lessons from other industries that are more advanced in this transformation. However, some challenges remain: costs, cybersecurity, lack of standardization, and resistance to change. This study insists on the need for a gradual and well-structured approach, focused on concrete use cases and adapted to small businesses. This thesis concludes with practical recommendations to guide a progressive and human-centered transition toward intelligent manufacturing in the cycling industry.