The future of AI-enabled supply chains: lessons from Tesla’s battery production and Toyota’s lean manufacturing
Yang, Jing (A.A. 2024/2025) The future of AI-enabled supply chains: lessons from Tesla’s battery production and Toyota’s lean manufacturing. Tesi di Laurea in International operations and global supply chain, Luiss Guido Carli, relatore Lorenza Morandini, pp. 32. [Master's Degree Thesis]
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Abstract/Index
Background of AI in automotive manufacturing supply chains. Problem statement & research motivation. Literature review. Evolution of AI in automotive supply chains. Lean manufacturing: beyond Toyota. Ethical and operational challenges of AI. Hybrid models: bridging AI and lean. Gaps in existing research. Theoretical framework. Methodology. Research design and philosophical approach. Data collection strategy. Case study analysis framework. AI-powered supply chain optimization models. Benchmarking metrics. Tesla’s AI-driven supply chain. AI-powered robotics in gigafactories. Predictive analytics in inventory and logistics. Sustainability through AI: battery recycling and energy optimization. Workforce transformation and ethical challenges. Scalability and regional challenges. Future trends: autonomous logistics and AI-driven R&D. critical analysis: AI’s trade-offs. Toyota’s lean manufacturing–balancing tradition and innovation. The Toyota production system (TPS): Core principles. Lean manufacturing in crisis: lessons from Covid-19. Sustainability and the circular economy. Digital transformation: lean meets industry 4.0. Comparative analysis: lean vs. AI-driven models. Ethical and cultural dimensions. Future trends: lean 4.0 and beyond. The future of AI-enabled supply chains. AI-powered smart factories and industry 4.0. Sustainability through AI and circular economy models. Ethical and regulatory landscapes. Human-AI synergy in future workforces. Enhancing supply chain resilience with AI. Emerging technologies and their implications. Strategic recommendations for manufacturers.
References
Bibliografia: pp. 30-31.
| Thesis Type: | Master's Degree Thesis |
|---|---|
| Institution: | Luiss Guido Carli |
| Degree Program: | Master's Degree Programs > Master's Degree Program in Data Science e Management (LM-91) |
| Chair: | International operations and global supply chain |
| Thesis Supervisor: | Morandini, Lorenza |
| Thesis Co-Supervisor: | Antonelli, Ginevra Assia |
| Academic Year: | 2024/2025 |
| Session: | Summer |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 24 Oct 2025 13:40 |
| Last Modified: | 24 Oct 2025 13:40 |
| URI: | https://tesi.luiss.it/id/eprint/43554 |
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