Huawei Cloud Manufacturing Nanjing, China Translated from Chinese

Nanjing Iron and Steel

Enterprise Knowledge Search · Real-time Analytics

Nanjing Iron and Steel had rich plant data and high-value optimization opportunities, but data sharing, model adaptation to steel processes, and fragmented scenario development made it hard to scale AI across the business.

20 intelligent applications in production
30% labor productivity improvement
6.55 million kWh of additional generation in 2024
coke cost reduced by 5-10 yuan per ton

Reported impact

Business outcome

Nanjing Iron and Steel created a reusable AI factory base that improved energy use, labor productivity, steel-quality outcomes, and decision speed across the steel value chain.

  • Cost Reduction
  • Productivity Improvement
  • Risk Reduction

Solution

Nanjing Iron and Steel used Huawei Cloud Stack to launch a hybrid large-model factory environment and move AI from pilots into 20 applications across R&D, manufacturing, service, and management. The stack combines large-model and solver capabilities with industrial mechanisms, prediction models, optimization models, domain knowledge, and enterprise data. In production, the platform runs peak-valley power dispatch optimization, coke-blend recommendation, and rolling-force prediction; in R&D it analyzes composition and process data to forecast low-temperature steel performance and adjust parameters online; in quality it uses vision models for metallographic and macrostructure grading; and in office operations it blends knowledge bases with data engines for smart Q&A and traceable analysis. This architecture turns scattered steel data into a reusable AI decision layer that supports modeling, inference, and human workflows across the plant instead of one-off analytics projects.

Data flow

Steelmaking, power, quality, and business data is processed on Huawei Cloud Stack, where large-model and optimization services build forecasting and recommendation models. Those models then feed dispatch, R&D, blending, quality, and Q&A applications back into plant and office workflows for online decision support.

Solution architecture

6 components · 2 layers
  1. Compute
    • Huawei Cloud Stack Provides the hybrid-cloud compute base for plant-wide AI development and deployment.
    • large model and solver capabilities Supply the shared reasoning and optimization foundation used across steel scenarios.
  2. Serving
    • smart peak-valley optimization dispatch system Optimizes power-generation scheduling in real time from plant operating conditions.
    • AI coal blending system Calculates optimal coke-blend ratios with multi-objective optimization algorithms.
    • rolling-force AI prediction engine Predicts rolling-force behavior with expert knowledge and data augmentation across steel grades.
    • double-model intelligent Q&A Combines a knowledge base and data engine to answer questions and provide traceable analysis.

Architecture clues

  • The deployment is described as a Huawei Cloud Stack large-model hybrid cloud.
  • The knowledge layer explicitly fuses a knowledge base with a data engine for Q&A and traceability.
  • The program spans R&D, manufacturing, service, and management scenarios.
  • The stack combines industrial mechanisms, prediction models, optimization models, and domain knowledge.

Evidence from the source

"In the peak-valley power scenario, the large-model and solver system added 6.55 million kWh of generation in 2024 and increased benefit 4.24 times. (original: 基于华为云Stack提供的大模型和求解器能力... 2024年增加发电655万度电,峰谷发电效益增加4.24倍。)"
"Nanjing Iron and Steel has already put 20 intelligent application scenarios into production on Huawei Cloud Stack's large-model hybrid cloud, creating an AI super factory. (original: 南钢基于华为云Stack大模型混合云,已完成面向研发设计、生产制造、营销服务、经营管理等四大业务方向20个智能场景应用的上线,实现从"经验炼钢"到"科技炼钢",打造...AI超级工厂。)"
"The AI coal-blending system cuts planning time from 1-2 days to 1-2 minutes and reduces coke cost by 5-10 yuan per ton. (original: AI配煤系统采用智慧配煤算法... 效率从1-2天压缩至1-2分钟。数据驱动下,吨焦成本降低5-10元。)"
"The low-temperature steel R&D model combines industrial mechanisms, prediction models, and optimization models to improve product qualification by more than 1.5%. (original: 借助华为云Stack大模型混合云,南钢通过工业机理、预测模型、寻优模型的深度结合... 将产品性能合格率提升了1.5%以上。)"
"The smart Q&A layer combines a knowledge base and data engine to deliver precise answers and traceable analysis for roles across the business. (original: 南钢通过"双模智能"融合知识库与数据引擎,在阳光智问、设备智通等场景实现了精准问答和可视化溯源分析。)"
Transparency Evidence & methodology 100/100 reference value · 81% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value100/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact25/25
    6 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence81%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    5 direct source quotes retained.
  • Date provenance0/10
    The publication date has no documented provenance.
  • Source transparency10/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity10/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. Huawei Cloud

    华为云Stack-南京钢铁-华为云

    First-party
    https://www.huaweicloud.com/cases/ng.html
    Source type
    Vendor-published customer story
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes

Date evidence

  • First archived Mar 11, 2026 · Internet Archive · Independent First Wayback Machine capture; confirms the page existed by this date, not when it was published.
    Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.