Driving Sustainability in Logistics: The Impact of AI-Powered Yard Management in California and Texas
The logistics and transportation industry faces significant sustainability challenges, particularly in the management of warehouse yards, where manual processes create bottlenecks, increase costs, and contribute to inefficiencies. The lack of technology in over 90% of these yards exacerbates these issues, leading to an estimated $146 billion in annual costs for the industry. Moreover, these inefficiencies contribute to excessive resource consumption, delays, and higher carbon footprints, conflicting with broader sustainability goals.
In response to these challenges, Ryder System, Inc., in partnership with Terminal Industries, has embarked on a pioneering initiative to digitize and automate yard operations using advanced technologies. The pilot program at Ryder’s e-commerce fulfillment center in California leverages Terminal’s AI-powered computer vision technology to accurately capture and analyze truck and trailer data, achieving an impressive 99% accuracy. This automation addresses the inefficiencies of manual recording processes, reducing bottlenecks, labor costs, and idle assets.
Machine learning is a crucial component of this initiative, continuously improving the system’s accuracy by learning from real-world data, which includes obscured identifiers and challenging environmental conditions. Additionally, mobile tablets equipped with this technology are being tested at Ryder’s facilities in Texas, further expanding the potential for efficient and sustainable operations.
This initiative directly impacts key Sustainable Development Goals (SDGs), particularly SDG 9 (Industry, Innovation, and Infrastructure), by driving innovation in supply chain operations. It also supports SDG 12 (Responsible Consumption and Production) by optimizing resource use and reducing waste, and SDG 8 (Decent Work and Economic Growth) by minimizing labor-intensive tasks and promoting economic efficiency. By harnessing AI, machine learning, and mobile technology, Ryder and Terminal are setting new standards for sustainable and efficient logistics operations.
Source: Morningstar
Technologies Used:
- AI-powered Computer Vision: Utilized to automatically index and analyze trucks and trailers, achieving high accuracy in capturing license plates and DOT numbers. It also helps to improve yard operations by providing precise vehicle data.
- Machine Learning: Enhances the AI system by learning from real-world data, improving accuracy in recognizing and processing various identifiers on vehicles under diverse conditions.
- Mobile Tablets: Used for auto-capturing inventory data at truck rental and maintenance facilities, enhancing real-time data collection and efficiency.
Companies Involved:
- Ryder System, Inc.: A leader in supply chain and transportation solutions, Ryder plays a crucial role in the initiative by integrating and testing the AI-powered technology in their warehouse yards and truck rental facilities.
- Terminal Industries: Specializes in AI platforms to digitize yard operations. Terminal provides the core technology that powers the automation and optimization of yard operations in this pilot program.
SDGs Impacted:
- SDG 9: Industry, Innovation, and Infrastructure: By digitizing yard operations, the initiative drives innovation and improves infrastructure, making supply chains more efficient.
- SDG 12: Responsible Consumption and Production: Enhancing operational efficiency reduces waste and resource consumption, promoting more responsible production processes.
- SDG 8: Decent Work and Economic Growth: The automation reduces labor-intensive manual processes, potentially improving job quality and fostering economic growth through more efficient supply chain operations.
Geographic Focus: United States
Sustainability Focus: Employee Sfety
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