PMA has been recognized for AI innovation in manufacturing after receiving the “AI Innovation Practice Pioneer Enterprise” recognition at the AI + Manufacturing Thematic Conference of the 2026 World Manufacturing Convention in Hefei.
The conference brought together manufacturing companies, industry experts and technology providers to discuss how AI and digital systems are being used in production and manufacturing management.
For PMA, the recognition reflects digitalization work that is already being applied across our manufacturing operations.
Digital tools in production
PMA continues to use digital systems and automated equipment in production and management.
Current applications include ERP and MES systems, automated inspection, production-data management, intelligent manufacturing equipment and AI-assisted production.
These systems help production teams record process information, monitor manufacturing activities and improve traceability across different stages of production.
Supporting graphene heating manufacturing
PMA develops and manufactures graphene heating films and thermal-management products for a range of applications.
For these products, stable manufacturing depends on more than the heating material itself. Equipment settings, production processes, inspection results and manufacturing records also need to be managed consistently.
Digital manufacturing gives our teams clearer access to production information and makes it easier to trace key process data during manufacturing and quality control.
From digital systems to daily manufacturing
The purpose of digitalization is not simply to add more software or AI tools.
For PMA, these systems are useful when they support practical manufacturing work: clearer production records, more consistent processes, better inspection management and easier traceability.
ERP and MES systems also help connect information from different parts of the manufacturing process, allowing production and management teams to work with more consistent data.
PMA will continue exploring how AI, production data, manufacturing equipment and management systems can work together more effectively in graphene heating and thermal-management manufacturing.
