With an ontology in manufacturing, can large models be implemented? | Intelligent Manufacturing Observation
2026-09-02 08:00Products & Apps🔥 28.9 heat score
1sources
1days unfolding
28.9heat score
5mentions
SummaryAI generated
On September 2, 2026, Xianchizhi released the Industrial Ontology Intelligent Platform. This platform aims to connect production line logic with data relationships through pre-set ontology knowledge, addressing challenges such as difficulties in implementing large models in manufacturing, complex operations, and data fragmentation. Using the analysis of abnormal machine startup rates in fiber drawing as an example, the platform uses an Agent system to assist in identifying the root causes of problems and generating traceable inspection task chains, achieving human-machine collaboration. The company is currently shifting from manual construction to automated accumulation, solidifying industry knowledge into a corpus foundation. CTO Li Fan stated that as a dynamic knowledge graph, the ontology enables the work mode of FDE to shift from project-based customization to platform-based accumulation, reducing software development占比 to 30%-40%. In the first half of the year, the company’s “AI+ manufacturing” business revenue accounted for 81.5%, achieving profitability after the semi-annual adjustment for the first time. IDC data shows that it ranks first in China in terms of industrial large model application market share.
Innovative Intelligence has released the Industrial Ontology Intelligent Body Platform, aiming to connect production line logic with data relationships through pre-set ontology knowledge, thereby addressing challenges such as difficulties in implementing large models in manufacturing, complex operations, and data fragmentation. Taking the analysis of abnormal machine start-up rates using fiberglass filaments as an example, this system uses an Agent system to assist skilled workers in identifying the root causes of problems and generating traceable inspection task chains, achieving human-machine collaboration. Innovative Intelligence began ontology research and development in the second half of last year and is currently shifting from manual construction to automated accumulation, solidifying industry knowledge into a corpus foundation. CTO Li Fan stated that as a dynamic knowledge graph, the ontology enables the FDE working mode to shift from project-based customization to platform-based accumulation, reducing software development costs by 30%-40%. In the first half of the year, the company’s “AI+ manufacturing” business revenue accounted for 81.5%, achieving profitability after the first semi-annual adjustment, and IDC data shows that it ranks first in China in terms of industrial large model application market share.