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LEAD's AI-Powered PHM System Wins Prestigious BRICS Innovation Award

1. LEADACE PHM System won Second Prize in AI at BRICS Industrial Innovation Contest. 2. LEAD's system can predict failures 7-15 days in advance, enhancing operational efficiency. 3. Major battery makers endorsed the system, achieving significant reductions in failure rates. 4. Technology integration reduces production downtime and lowers maintenance costs markedly. 5. LEAD seeks to expand into BRICS countries, aiming for sustainable industrial development.

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Why Bullish?

The recognition and endorsement of the LEADACE PHM system may highlight effective innovations in the sector. Previous advancements in similar technologies led to spikes in stock valuations for peers.

How important is it?

The success of LEADACE PHM could lead to competitive advantages in predictive maintenance, aligning with PHM's operational strategies. This innovation directly correlates with enhanced efficiencies in the lithium-ion battery sector.

Why Long Term?

Sustained interest and partnerships from major battery makers can drive continuous revenue growth. Comparatively, firms with steady tech adoption have shown long-term stock appreciation over years.

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WUXI, China, Sept. 30, 2025 (GLOBE NEWSWIRE) -- Lead Intelligent Equipment Co., Ltd. (LEAD) proudly announced that the LEADACE Predictive Maintenance (PHM) System, an intelligent maintenance system based on a multimodal large model, has won the Second Prize in the artificial intelligence (AI) category of the BRICS Industrial Innovation Contest 2025. “This award is a new starting point as we accelerate innovation and global expansion, helping BRICS countries build a more inclusive, green, and sustainable industrial future,” said Wang Yanqing, Chairman of LEAD. Jointly organized by the BRICS Partnership on New Industrial Revolution Innovation Center and China’s Ministry of Industry and Information Technology, the contest drew 1,396 global entries across 5 tracks, including AI, Green Industry, Low-Altitude Equipment, Energy Electronics, and Industrial Design. LEAD emerged as the only Chinese lithium-ion battery cell equipment enterprise to win in the AI track, recognized for its technological innovation, real-world impact, and industrial scalability. As the global lithium-ion battery industry moves toward TWh-scale manufacturing, even minor anomalies can lead to significant financial losses and safety risks. Traditional “after-failure” or scheduled maintenance approaches can no longer meet customer demands. But the LEADACE PHM System directly addresses this challenge through: Physics–AI Integration: Embeds electric motor thermodynamics, bearing dynamics and other physical models into AI training for traceable, trustworthy fault diagnosis.Digital Twin Modeling: Builds high-precision, standardized digital twins of the most used power components for cross-industry reuse, lowering cost and deployment time.Closed-Loop Automation: Thinks in a “predict-diagnose-decide” path while continuously learning to form a lasting digital knowledge base, supporting the system to predict failures 7–15 days in advance and increasing accuracy by more than 25 percent compared with conventional methods. Chairman Wang believes AI and digital twins are redefining manufacturing of the future. To this day, the system has been deployed on hundreds of high-speed cell winding and stacking machines. On one single production line, the LEADACE has successfully helped a top battery maker achieve: 35% reduction in failure frequency30% cut in total downtimeContinuous monitoring of 2000+ key componentsAnnual savings exceeding RMB 10 million With a compelling ROI and scalable business model, the system has garnered endorsement from top tier battery makers, securing strategic cooperation agreements covering 3 core production lines with more than 150 key machines. Media Contacts Website: https://www.leadintelligent.com/en/ Email: pr@leadintelligent.com A photo accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/7935ff8b-1c0e-4eaa-b0bb-feccc754c3b9

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