Chung-Hsin Electric to Ship GIS Equipment to Semiconductor Giant in Q4, Expands into AI Data Center Projects

Chung-Hsin Electric Chairman Chiang Fu-nien announced a double-digit growth target for this year. GIS equipment has been certified by a major semiconductor manufacturer, with shipments starting in Q4. The company is also entering the AI data center turnkey engineering market, with a backlog exceeding NT$40 billion and visibility through 2031.
businessNQ 53/100出典:PR Times

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  • 📰 Published: May 25, 2026 at 13:14
  • 🔍 Collected: May 25, 2026 at 13:31 (16 min after Published)
  • 🤖 AI Analyzed: May 31, 2026 at 20:37 (151h 5m after Collected)
Heavy electrical manufacturer Chung-Hsin Electric's Chairman, Chiang Fu-nien, stated on the 25th that the company expects double-digit growth this year. AI computing power and the green energy transition are driving growth. The company's GIS heavy electrical equipment has received certification from a major semiconductor manufacturer and will begin shipping to new domestic plants in the fourth quarter. Additionally, Chung-Hsin Electric is entering the turnkey engineering and construction sector for AI data centers this year. During the shareholders' meeting in Taoyuan, Chiang addressed questions from minority shareholders. Regarding the heavy electrical business, Chiang noted that Taipower's infrastructure policies and rising renewable energy usage are increasing demands on grid systems, which is reflected in the company's performance. The current backlog exceeds NT$40 billion, with some orders visible through 2031, and a new order target of NT$20-25 billion. Regarding overseas expansion, the company remains focused on the Taiwan market but is considering overseas production capacity, starting with the Japanese market in the second half of the year. The hydrogen energy business is also entering a critical year, with green power sales services planned for the second half.

FAQ

What are the strengths of Chung-Hsin Electric?

GIS equipment for power infrastructure and turnkey engineering capabilities for AI data centers.