부산대학교 도서관

For many companies and institutions, the supply chain model for reliability & maintainability (R&M) of systems can either act as their competitive advantage or weakest link. Big data and analytics play an instrumental role within the supply chain, especially for companies using R&M principles, where these practices were born and matured. The automotive industry has led many initiatives to increase the adoption of such supply chain architectures within their vehicle ecosystems allowing big data and analytics to play the driving role to insure the performance of the vehicles. The automotive industry continues to use these practices to deal with disruptions within autonomous driving, self-healing efficient batteries, robotics, insurance risk assessments, and exceptional customer experiences. Whether it be automotive manufacturers, dealers, drivers, or insurance companies, R&M have had positive results. Today, however, another technology is surfacing fast, changing the face of R&M standard practices and applications. Artificial Intelligence (AI) is impacting and changing the entire automotive industry ecosystem. While advancements in chipsets, edge technology, 5 th generation mobile network (5G), Internet of Things (IoT) and cloud have been acting as enablers, data and AI is at the heart of R&M future advances. As per VynZ Research, Global Artificial Intelligence (AI) Market for Automotive and Transportation Industry is Set to Reach USD 45.1 billion by 2024, Observing a CAGR of 17.7% during 2019–2024 [1].In this paper, we will share the impact of AI & trust on the auto industries R&M programs, broken down across four pillars: in-vehicle experience, connected vehicles, auto manufacturing, and autonomous vehicle with examples, and use-cases.