Manufacturing Predictive Maintenance

The Manufacturing Predictive Maintenance solution is used for collecting and parsing device data, pre-processing edge computing resources, and performing data modeling and analysis on the cloud. It facilitates transformation of manufacturing enterprises from selling products to selling services.
Solution Advantages
  • Fast Access

    Huawei industrial gateways and IoT platform resolve the issues of coexistence of new and old equipment, various interface protocols, and difficult connection.

  • Edge Intelligence

    Edge computing, as an extension of HUAWEI CLOUD capabilities, delivers cloud capabilities to network edges and allows for real-time processing, analysis, and decision-making capabilities of equipment.

  • Data Insight

    HUAWEI CLOUD provides E2E data processing capabilities such as data integration, real-time processing, data storage, analysis and calculation, and mining, and pre-integrates models and algorithms in predictive maintenance scenarios.

  • Wide Cooperation

    HUAWIE CLOUD is pre-integrated with modules and equipment from mainstream IoT vendors to facilitate extensive cooperation.

Business Challenges
  • Complex Access

    A large number of heterogeneous bus connections exist in industrial machinery for a long time, and industrial Ethernet networks of multiple standards coexist. It is an urgent issue to resolve for ensuring compatibility and high reliability of heterogeneous connections.

  • Lack of Intelligence

    Without a lightweight computing framework, industrial equipment at the edge of a network cannot respond to service requests in real time, perform data aggregation, filtering, and prediction, or achieve full coordination with the cloud.

  • Lack of Insight

    Traditional manufacturing enterprises are familiar with equipment mechanisms and typical fault modes. However, they lack professional data scientists as well as the capability of using data analysis or AI tools to process massive data.

  • Difficulty in Development

    Manufacturing enterprises have limited IT capabilities, but IoT technologies are widely used in new application development. Due to limited capabilities in developing and enabling device-cloud collaboration, customers cannot fully focus on service innovation.

Typical Scenarios
  • Quick Access

  • Device-Cloud Synergy

  • Data Analysis & Modeling

  • Industry Partners

Quick Access

Connects to industrial gateways, adapts to complex industrial scenarios, and quickly connects to industrial equipment.

  1. Huawei AR series industrial gateways provide industrial-grade interface capabilities (such as industrial Ethernet and RS485) and adapt to harsh environments (wide temperature range, water-proof, and dust-proof), which effectively resolves issues caused by coexistence of new and old equipment, various interfaces and protocols, and difficult connection on the production site.

  2. Huawei AR series industrial gateways are pre-integrated with HUAWEI CLOUD IoT platform and Big Data services.

  3. Related Services

    IoT Platform

    Data Ingestion Service

    Cloud Stream Service

Device-Cloud Synergy

Meets customers' requirements for remote control, data processing, analysis, decision-making, and intelligence of edge computing resources, and provides a complete edge computing framework for users.

  1. Device-Cloud Synergy

    Edge computing focuses on edge equipment and intermediate nodes between gateways and clouds, extending HUAWEI CLOUD capabilities.

  2. Lightweight Framework

    The lightweight edge computing framework is used to deliver cloud services to network edges and implement local protocol parsing, real-time analysis, and decision-making.

  3. Remote Management

    Remote control over massive edge equipment based on HUAWEI CLOUD

Data Analysis & Modeling

Unifies the reference architecture of industrial Big Data and preconfigures typical model algorithms to help customers quickly build data analysis capabilities in predictive maintenance scenarios.

  1. Unified Architecture

    Constructs full-process capabilities such as data ingestion, storage, analysis, mining, and visualization in the industry IoT scenario.

  2. Preconfigured Typical Algorithms

    Supports professional prediction algorithms, pre-integrates typical algorithms in the industry domain, such as decision tree, classification, clustering, regression, and exception detection algorithms, supports flexible export of training models, and loads them to rule engines to implement real-time alarm reporting.

  3. Related Services

    Data Ingestion Service

    Cloud Stream Service

    CloudTable Service

    MapReduce Service

    Machine Learning Service

    Data Lake Insight

Industry Partners

Works together with industry-leading solution providers of equipment in different industrial sectors.

  1. Predictive maintenance helps improve the response speed and O&M efficiency for key equipment in typical industries, and minimize the impact of unexpected downtime on production activities. Predictive maintenance is applicable to typical industries, including elevators, engineering machinery, new-energy equipment, and robots. Huawei has extensive cooperation with industry-leading solution providers in related fields, and can quickly replicate predictive maintenance solutions to the manufacturing industry.

  2. Related Services

    Elastic Cloud Server

    Cloud Container Engine

    Elastic Load Balance

    Distributed Message Service

Solution Architectures

Predictive Maintenance Solution

Prediction maintenance requires a series of functionalities such as edge computing, IoT platform, and Big Data, and extends edge computing service of HUAWEI CLOUD to the edge of the network. Huawei cooperates with industry partners to accelerate prediction maintenance of typical equipment in various industries.

Highlights

  • One-stop cloud services
  • Collaboration between edge and cloud
  • Industrial data modeling
  • Cooperation with industry partners
Recommended Services
  • IoT Platform
    A large amount of equipment can be connected to the IoT platform to implement data collection and command delivery between the equipment and platform, enabling efficient and visualized equipment management.
  • CloudTable Service
    CloudTable allows random read/write access in milliseconds and applies to storage and query of sensors' time series data.
  • Machine Learning Service
    Machine Learning Service (MLS) enables users to quickly discover data rules, build a prediction model, and deploy the prediction analysis solution.

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