- سعودي عربية
Industrial Big data Application for production process Life cycle
Challenges Lying in Industrial Enterprises
- No timely display of production information;
- Failures of a real-time monitor for production process and facilities;
- Difficulty of accurate calculation of human cost;
- High maintenance and administration fees for equipment;
- Increasingly further requirements of automation degree of production process and equipment;
- Products quality traceability system yet to be established.
Through model analysis and algorithm prediction, industrial big data application platform for production process life cycle is to conduct the unified access, storage and analysis of the existing PLM system data, CAPP, ERP, MES, Lean production pull sys-tem and other data, detect the relationship between the data, optimize the enterprise's supply chain and production process, improve product yield,and enhance business efficiency.
- Production data integration
- Supply chain analysis and optimization
- Equipment health management
- Optimization of production process
- Smart production
- Workshop digital visualization
- Product lifecycle modeling
- Product knowledge base
- The comprehensive business value and ability enhancement brought by this platform mainly focus on the intelligent upgrading ranging from equipment, production lines to enterprise decision-making.
- In the process of equipment manufacturing, digital precision control and then accurate statistics become available for each part of production through the automatic control system based on big data.
- According to data predication and management, the process design, production, logistics, sales and after-sales have offered an access for all-in-one intelligent control of assembly line to its whole manufacturing procedures.
- Predications and business decisions, ranging from the product assembly line to the product positioning and decision-making as well as from market research to product competitive positioning, can be reached through the intelligent platform. And all these efforts have led to automatic decision-making among enterprises in an objective way and to further the progress of smart factories.
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