Lenovo Drives the Future of Manufacturing with Sustainable, Human-centric Innovation

As the global technology powerhouse, Lenovo recognizes the diverse challenges manufacturers face today: labor shortage, regulatory compliance, sustainability requirements, human-machine collaboration, and the dual demands of productivity and quality enhancement. Most crucially, maintaining sustainable business growth is essential for manufacturers of all sizes. To address these needs, Lenovo offers highly customizable manufacturing solutions. By leveraging its extensive manufacturing experience, robust supply chain network, and industry expertise, it aims to provide accessible, affordable, and reliable solutions tailored to manufacturers.

Lenovo’s key offerings include advanced AI-driven and automation technologies that enhance productivity, quality, and sustainability. Asset Tracking systems use real-time locating technology to automatically track and record the location of movement and objects with typical sub-meter positioning accuracy. Pick Assist Autonomous Mobile Robots (AMRs) employ “order to person” human–robot collaboration to eliminate the need for manual route planning, warehouse design and human intervention.

Automated Storage and Retrieval Systems deliver flexibility and scalability in stereo warehouses and combine different kinds of robotics with AI algorithms for precise and agile pallet movement. Warehouse Execution Systems (WES) coordinate and optimize material handling in real time, integrating automation from multiple brands into a unified platform.

Lenovo Industrial Computer Vision applies AI to detect, measure, and assess quality across production lines. Supply Chain Intelligence enhances end-to-end visibility, reducing decision-making time by 60%, cutting manufacturing and logistics costs by 20%, and contributing to a 4.8% revenue increase. Lenovo ESG Navigator automates over 250,000 data points to generate sustainability dashboards for 228 KPIs, while Robotic Inspection solutions provide continuous, automated asset monitoring using intelligent sensors, computer vision, and edge computing.