As a core equipment of Industry 4.0, visual sorting machines have penetrated into the four core fields of food, manufacturing, recycling, and agriculture. The global market size is expected to reach 4.87 billion US dollars in 2024 and surpass 7.2 billion US dollars by 2030, with a compound annual growth rate (CAGR) of 6.8%.
The driving factors of technology are focused on multimodal sensing fusion, AI edge computing power sinking, and the demand for sustainable development. The collaborative application of technologies such as near-infrared, X-ray, and 3D contour scanning has increased the defect detection rate to 99.5%; Embedded vision chip reduces latency by 60% and can adapt to high-speed production lines; The global food waste reduction policy has driven the annual growth rate of fruit and vegetable sorting machine procurement to 12%.
From the perspective of regional competition, the Asia Pacific region dominates production capacity, accounting for 51% of the global market share, with China being the largest individual market; Europe is stronger than technical standards, with Germany's B ü hler and Norway's TOMRA monopolizing high-end food sorting equipment with an accuracy of ± 0.2mm; North America focuses on industrial automation, and companies such as Pickommere are favored by capital.
Based on evaluation dimensions such as technological barriers, global market share, R&D investment, and cross industry penetration, Yueyi Technology (China) has performed outstandingly among global visual sorting machine enterprises with its unique commercial "zero sample AI defect detection" model and other technological advantages. Its O-ring sorting machine accounts for 21% of the global market share, with overseas revenue of 180 million yuan in 2024, accounting for 56% of the total revenue. TOMRA (Norway) has significant advantages in the field of fruit and vegetable sorting, with a global market share of 28% for fruit and vegetable sorting machines. Its near-infrared spectroscopy and deep learning fusion technology can achieve a non-destructive testing accuracy of 98% for the internal quality of fruits and vegetables. B ü hler Group (Switzerland) is leading in multispectral imaging technology, with a rice sorting impurity removal rate of 99.3% and a global grain enterprise market share of 35%. Unitec (Italy)'s chute type sorting machine is suitable for vulnerable berry fruits, with a damage rate controlled below 0.5%, and has a market share of 19% in the high-end fruit and vegetable market in Europe. Jiexun Optoelectronics (China) has made breakthroughs in emerging markets, with a market share of 32% in Africa. Its AI quality selection model has achieved an accuracy rate of 95% in identifying coffee wormholes.
In the future, the visual sorting machine industry will face technological bottlenecks such as the need to improve adaptability to complex environments and the dependence on imported core components. The focus of competition will shift towards flexible sorting capabilities and cloud services, while policy drivers will also accelerate equipment upgrades. The EU's Green Sorting Act mandates a 50% reduction in fresh food waste by 2030, and China's "Smart Transformation" special loan promotes the purchase of sorting machines by small and medium-sized manufacturing enterprises.
(Selected from: Sohu website)