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Digital Transformation
  • Full-stack
  • Comprehensive
  • Win-win
Cooperation Mode
  • Enterprise
    Integration of both products Business upgrade
  • Industry
    Industry standardization Providing solutions
  • Business
    Focusing on application Fast delivery
  • Project
    Meeting customer needs Customized solution
Difficulty
Rapid realization of business value is the difficulty of digital top-level design. Pre-deployment, business transformation, data accumulation, research and analysis are all major projects that require long-term planning.
Formulating the transformation design is the beginning and the core: to ensure that the transformation goals are effectively implemented and implementable; at the same time, to ensure the sustainable development of the transformation.
By comprehensively evaluating the current situation of the enterprise, analyzing business needs, and benchmarking industry practices, we can discover the business value of transformation and identify breakthroughs in transformation.
Design
Organization
Business architecture Application architecture
Management data Business data
Data design
Breaking Down Data Silos
Limitations in decision-making across departments and business units
Business fragmentation and data "silos"
Building data correlation and accumulation to provide more effective basis for decision-making
Establishing end-to-end data linkage to drive business innovation
Building Process Architecture and Process Reengineering. Building the architecture of the enterprise digital transformation process involves horizontal integration of processes across various business departments, and vertical decomposition from business domains, business modules, core control points, down to the granularity of functions and data directories, providing effective benchmarks and references for practical implementation of digital transformation.
Vertical Hierarchy Horizontal Hierarchy
Business Application Architecture Design Design and adapt application architecture based on the requirements of change management, integrating business flows and data flows, and building efficient and agile collaborative mechanisms. The characteristics of digitization-linkages and aggregations-help enterprises break down information "silos" and enhance the overall efficiency of system.
Data Governance Data governance and enterprise digital transformation are mutually reinforcing. The adjustment of business models has raised the requirements for data accuracy, timeliness, security, and other aspects. The attitude of enterprises towards data should shift from reactive to proactive.
  • 1
    Metadata Management
    Including metadata collection, lineage analysis, impact analysis, etc.
  • 2
    Data standard management
    Establishing data management standards and defining management responsibilities and roles
  • 3
    Standard Quality Management
    Establishing data quality management rules and quality inspection standards
  • 4
    Data Integration Management
    Building data integration relationship diagrams and data flow diagrams for data processing, data transformation, and data aggregation
  • 5
    Data Asset Management
    Establishing enterprise data asset repository and providing data asset services
  • 6
    Data Security Management
    Establishing data management permissions and defining desensitized data and encrypted data
  • 7
    Data lifecycle management
    Establishing data lifecycle history management mechanism
  • 8
    Master Data Management (MDM)
    Establishing Master Data Management catalog, and Implementating management mechanisms for data request, review, publication, modification, etc.
  • 9
    Data Model
    Improving the rational distribution and utilization of data
  • 10
    Data Distribution and Storage
    Establising system and data distribution rules and managing master data and reference data
Digital Preventive Maintenance
Concept
The concept is to provide professional, fast, and standardized preventive maintenance services to enterprises through skilled professionals, advanced software products, and powerful maintenance tools, aiming to achieve equipment failure prediction, and improve equipment stability and availability.
Advantages
  • Systematic algorithms
    Professional experience In-depth analysis and evaluation Professional assessment standards
  • Professional tools
    Maintenance software and service platforms Multi-dimensional fast and professional tools
  • Comprehensive range of product types
    Industrial networks and bus systems Mature remote maintenance products
  • Optimized maintenance time
    Professional products shorten execution time Reducing maintenance time and improving efficiency
User Experience
 1.Reduce unplanned downtime: Detect equipment issues early and extend equipment lifespan 2.Maintain data to make it clear and transparent: Comprehensive understanding of equipment status through digital maintenance methods 3.Reduce downtime in maintenance: Significantly shortened equipment maintenance time 4.Increase equipment productivity: Improve equipment efficiency, reduce maintenance costs
IT Infrastructure of Smart Manufacturing
Application
Big Data Analysis
Supply Chain Collaboration
Production Collaboration
Data Processing
Factory Virtualization
Data Center & Cloud
M2M & Fog Computing
Software-Defined Smart Factory Infrastructure
Factory Wireless
Factory Security
Factory Automation Network