Designed for production and manufacturing scenarios, the system supports equipment fault diagnosis and health management, product quality inspection, operation safety monitoring, and intelligent decision-making with such technologies as computer vision, natural language understanding, signal processing, and data analysis and mining, allowing enterprises to reduce cost and improve efficiency in digitalization and production.
Features and Advantages
深入行业的机器学习优化模型
面向工业垂直领域，利用机器学习算法经验，融合机理原理业务模型，为客户生产优化提供预测支撑
算子与算力调度的双引擎算法平台
大量行业模型+基础算子积累，可实现加速构建具有行业属性的算法模型，并投入使用
设备数据一站式接入解析与管理
覆盖多模态数据采集与治理，内置多元化流批计算模板，基于实时架构，提升数据处理时效性，提升业务敏捷性
融合的多模态知识库
利用知识图谱来进行知识结构管理，建立知识管理系统，将知识、数据、文件、数据源等映射起来
基于知识图谱的智能问答
将领域知识构建成知识图谱，通过关系推理，得到精准的答案。以图谱问答为核心，结合IRQA，实现智能问答
知识图谱的可视化展示
利用实体关系，将检索到的实体、关系以及相关实体全部通过图形化的方式展现出来，实现检索结果关系溯源
Product Structure
Various Business Scenarios for Digitalization Construction
工业模型构建与投产
满足模型的积累复用以及模型训练的基础算子与算力，通过一个统一的整合平台来提供，让效率更高
工业生产参数优化
通过大量数据的积累并结合机器学习算法，满足在保证预测稳定性与准确性的同时，提高生产的效能
基于语义的检索
基于语义的检索，实现故障案例精准定位以及维修方案的智能推荐
技术标准查询
以智能问答技术，通过移动端应用和语音交互，满足员工信息查询需求，提升工作效率
Related Case
The knowledge search speed is increased by 10 times, making it much easier to accumulate expert experience and product knowledge
Our solution reduces the cost of a single search for bearing specifications to help the customer make decisions faster. The association established between a large number of documents enhances the connectivity of the knowledge network, strengthening the service capabilities of the information platform and facilitating the implementation of digital and intelligent strategies.
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A better configuration of cement production parameters is realized to reduce the reliance on experiences.
For a traditional cement production control system, the production parameters affecting capacity, quality, cost and other metrics are defined only based on expert experiences. This results in inconsistency and inaccuracy of data. Intelligent O&M makes the configuration of production parameters more scientific and reasonable.
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O&M prediction and risk evaluation are conducted through intelligent data analysis to reduce the O&M cost of steel manufacturing;
When building a PHM model, as opposed to the conventional method, our solution allows the equipment to obtain offline data through intelligent data analysis, without the need to train the model offline before putting it into use. This improves the model updating and iteration efficiency, and makes the response to equipment updates faster.
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The O&M optimization and operation management system helps to quickly pinpoint problems and recommends the right maintenance solutions for fixing the problems.
Using our solution, a carmaker in the Fortune Top 500 list achieves faster troubleshooting in after-sales maintenance services, eliminating the heavy reliance on manual work in quality risk monitoring, maintenance suggestions, and problem feedback. With the volume of maintenance case data growing over time, maintenance case classification and problem identification are improved in terms of both quality and efficiency.
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