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Shanghai Electric Integrates Industrial AI into Heavy-Duty Gas Turbine Manufacturing and Lifecycle Services 10.11.2026, 07:05 Uhr von EQS News Jetzt kommentieren: 0

EQS-News: Shanghai Electric / Key word(s): Contract
Shanghai Electric Integrates Industrial AI into Heavy-Duty Gas Turbine Manufacturing and Lifecycle Services

10.11.2026 / 07:05 CET/CEST
The issuer is solely responsible for the content of this announcement.


AI supports key processes in the manufacture, operation and maintenance of high-end power equipment

SHANGHAI, Nov. 10, 2026 /PRNewswire/ -- As industrial artificial intelligence (AI) moves from pilot projects into core operations, manufacturers are increasingly focused on how it can deliver sustained value in production and long-term equipment performance. For heavy-duty gas turbines, described as a "crown jewel" of high-end equipment manufacturing, this involves both precision machining of complex components and reliable operation throughout their service lives.

Shanghai Electric Integrates Industrial AI into Heavy-Duty Gas Turbine Manufacturing and Lifecycle Services

In its heavy-duty gas turbine business, Shanghai Electric (SEHK: 02727, SSE: 601727) is combining equipment engineering expertise with production and operating data. Applications span flexible blade manufacturing, inspection and servicing, as well as intelligent operations and maintenance (O&M), reflecting the company's broader efforts to advance AI-enabled manufacturing.

Flexible Blade Manufacturing

Manufacturing critical components is an essential capability for gas turbine suppliers. Blade production involves different sizes, shapes and machining routes, requiring automated equipment to accommodate multiple blade types and process requirements. Shanghai Electric's flexible manufacturing line combines AI vision, digital twins, intelligent scheduling and robotics to support mixed-model blade production and automatic changeovers.

Using 3D vision and AI, the system identifies blade blanks in randomly stacked piles, then picks and positions them. Picking accuracy exceeds 99.99%. The line integrates production scheduling, manufacturing execution and quality management systems, linking loading, machining, inspection and final packing. It can switch between fully automated production and standalone machine operation, providing flexibility to support production continuity.

AI-Assisted Quality Inspection

Alongside production flexibility, quality assurance is another focus of Shanghai Electric's AI applications. Rotors are high-value, critical components in major power generation equipment, and weld quality directly affects their safe operation. To address the challenges of inspecting machined features on large components, the company has developed an AI-based visual inspection terminal that combines AI, robotic control and welding expertise. It provides real-time monitoring throughout welding operations to identify quality defects at an early stage.

The system's embodied AI architecture combines a collaborative robot with a custom end effector. The arm can extend and retract at the touch of a button and automatically adapt to the welding cycle. Using 5G connectivity, the system completes image analysis and returns inspection results within seconds. A data feedback loop links shop-floor observations, process optimization and quality traceability, turning practical manufacturing experience into digital knowledge that can be retained and reused.

Data-Driven Operations and Maintenance

The applications extend from manufacturing and quality inspection to long-term plant operation. Shanghai Electric's SIMPLE intelligent operation and maintenance platform draws on data from more than 60 turbine units, with over 1 million cumulative operating hours. It combines AI with knowledge of gas turbine operating principles to support real-time performance monitoring, dynamic optimization of operating performance and early warnings of potential faults.

Through cloud-edge coordination, the platform links design and operating data in a decision-support workflow covering monitoring, early warning, diagnosis and corrective action. This supports a shift from reactive repairs to proactive maintenance. Remote collaboration tools complement these capabilities, allowing experts to view live footage from plant sites and provide maintenance guidance through augmented reality annotations, supporting technical assistance across locations.

Shanghai Electric will continue to advance data integration across the gas turbine lifecycle, using feedback from manufacturing and operations to refine design, production and after-sales service. As it looks to international markets, Shanghai Electric will continue to validate and refine these capabilities in real-world projects. The company aims to meet power plants' needs for reliable operation, timely maintenance support and cost-effective operation over the long term, laying the foundation for the international expansion of its gas turbine business.

Shanghai-Electric-logo.jpg?id=OA3069176

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10.11.2026 CET/CEST Dissemination of a Corporate News, transmitted by EQS News - a service of EQS Group.
The issuer is solely responsible for the content of this announcement.

The EQS Distribution Services include Regulatory Announcements, Financial/Corporate News and Press Releases.
View original content: EQS News


2431312  10.11.2026 CET/CEST

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Dis­clai­mer: Die hier an­ge­bo­te­nen Bei­trä­ge die­nen aus­schließ­lich der In­for­ma­t­ion und stel­len kei­ne Kauf- bzw. Ver­kaufs­em­pfeh­lung­en dar. Sie sind we­der ex­pli­zit noch im­pli­zit als Zu­sich­er­ung ei­ner be­stim­mt­en Kurs­ent­wick­lung der ge­nan­nt­en Fi­nanz­in­stru­men­te oder als Handl­ungs­auf­for­der­ung zu ver­steh­en. Der Er­werb von Wert­pa­pier­en birgt Ri­si­ken, die zum To­tal­ver­lust des ein­ge­setz­ten Ka­pi­tals füh­ren kön­nen. Die In­for­ma­tion­en er­setz­en kei­ne, auf die in­di­vi­du­el­len Be­dür­fnis­se aus­ge­rich­te­te, fach­kun­di­ge An­la­ge­be­ra­tung. Ei­ne Haf­tung oder Ga­ran­tie für die Ak­tu­ali­tät, Rich­tig­keit, An­ge­mes­sen­heit und Vol­lständ­ig­keit der zur Ver­fü­gung ge­stel­lt­en In­for­ma­tion­en so­wie für Ver­mö­gens­schä­den wird we­der aus­drück­lich noch stil­lschwei­gend über­nom­men. Die Mar­kets In­side Me­dia GmbH hat auf die ver­öf­fent­lich­ten In­hal­te kei­ner­lei Ein­fluss und vor Ver­öf­fent­lich­ung der Bei­trä­ge kei­ne Ken­nt­nis über In­halt und Ge­gen­stand die­ser. Die Ver­öf­fent­lich­ung der na­ment­lich ge­kenn­zeich­net­en Bei­trä­ge er­folgt ei­gen­ver­ant­wort­lich durch Au­tor­en wie z.B. Gast­kom­men­ta­tor­en, Nach­richt­en­ag­en­tur­en, Un­ter­neh­men. In­fol­ge­des­sen kön­nen die In­hal­te der Bei­trä­ge auch nicht von An­la­ge­in­te­res­sen der Mar­kets In­side Me­dia GmbH und/oder sei­nen Mit­ar­bei­tern oder Or­ga­nen be­stim­mt sein. Die Gast­kom­men­ta­tor­en, Nach­rich­ten­ag­en­tur­en, Un­ter­neh­men ge­hör­en nicht der Re­dak­tion der Mar­kets In­side Me­dia GmbH an. Ihre Mei­nung­en spie­geln nicht not­wen­di­ger­wei­se die Mei­nung­en und Auf­fas­sung­en der Mar­kets In­side Me­dia GmbH und de­ren Mit­ar­bei­ter wie­der. Aus­führ­lich­er Dis­clai­mer