Digital Twin Plant
JIC Digital Twin Builds Virtual Manufacturing Plants
JIC Digital Twin Plant can construct virtual manufacturing platform for physical plants to realize total-factor management on production, which will realize comprehensive and detailed management, reduce downtime of production line and improve production efficiency.
Real-Virtual Mapping
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Real-Virtual Mapping
Digital Twin for plants can construct virtual manufacturing platform for physical plants to realize the total-factor management on production by the way of virtual-real fusion.
The Building of Digital Twin Plant
The virtual twin plant can reflect information related to the production of actual plants, total-factor structures of the production lines and equipments in real time. The different states and productivity information of production lines can be perceived via different colors, and the states in different positions of plants can be seen in the form of dynamic roaming to create a transparent total-factor plant.
Transparent Data Kanban
In addition to model of product line, Digital Twin Plant can present data that clients care about in the form of transparent data Kanban. Administrators can conduct real-time observation on production data they want to know, including production schedule, with / without information of fault alarming, material consumption, productivity information, and performance assessment and other information.
Online Collaboration
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Online Collaboration
Digital Twin Plant creates online collaboration scenario, realizes remote access in different places, unifies data scene management and remote collaborative decision making to reduce communication cost, to improve enterprises' management level and to provide enterprise competitiveness.
Remote Access
Different persons can log in and make remote access when getting permissions, not confined in LAN.
Unified Data Scene
Employees with the same authorization in the group can view the unified scenes. Online collaboration by multiple persons is available to reduce communication costs.
Collaborative Management and Decision Making
Collaborative management platform is built and online decision-making mechanism is established to improve management level of enterprises and efficiency of decision making.
Full-Stack Management
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Full-Stack Management
Digital Twin Plant can realize full-stack management, including managements on personnel, devices, materials, tech, conditions and so on to realize online collaboration on total factor and whole process of plants.
Personnel Management
The realization of work scheduling and management for personnel can be related to production performance and quality tracking system to form association between products and personnel.
Device Management
Digital Twin for plants can realize total factor management on devices, including device state, current production progress and general efficiency of devices.
Material Management
Digital Twin for plants can break WMS or material management system to realize management on inventory of materials and to ensure material supply in the plants.
Tech Management
Digital Twin for plants realizes the simulation of tech, batch control, unified management on tech information in the process of production.
Environmental Monitoring
Environmental monitoring can ensure that changes in environmental conditions do not affect factors of production, including on-site temperature, humidity, noise interference, vibration and the degree of pollution and so on.
Analysis on Scenarios
Digital Twin for plants can build different twin scenarios for different users, and production information that clients are concerned with can be analyzed in different situations.
Production Optimization
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Production Optimization
Production efficiency can be optimized by analyzing the relation of key factors, including the quality of products, costs, energy consumption, efficiency, yielding rate, etc, with tech and parameters of devices.
Quality Management
Digital Twin plants can realize the digitalized information integration of manufacturing materials, manufacturing process and manufacturing results according to tech and procedure. It is not only the description and records for manufacturing state, but also realizes the tracking to sources of quality problem to find out main factors affecting product quality and to improve product quality.
Efficiency Optimization
The simulation and test on productivity of enterprises can be realized via Digital Twin Plant. The simulation and optimization on production process can be conducted to reduce the costs and to raise efficiency. The cycle of production and development of products can be greatly shortened to ensure products matched with consumers' experience and value to go into markets. Innovation on business model of enterprises can be realized by combining production with sales.
Process Tracing
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Process Tracing
Based on information fusion of Digital Twin Plant, the tracing of production process, quality and batch can be achieved, and the planning and transparency of supply chain can be optimized.
Tracing on Quality
Total-factor production process including personnel, machines, materials, rules, environment is integrated in the Digital Twin plants, and the tracing on reasons can be achieved when quality problems happen.
Tracing on Production Process
Every production process can be traced via Digital Twin for plants to check the time of process and standardization to know the deviation.
Tracing on Materials
Digital Twin plant can trace the source of materials, especially when quality problem occurs, the information of materials can be traced and assessment on impact of materials will be made.
Tracing on Formula
Data of formula in early stage and related information of products can be recorded in the Digital Twin plants. The tracing of formula can be conducted according to products.
Tracing on Batch
Batch control of raw material, semi-finished products, WIP can be conducted via batch management system to minimize the loss.
Tracing on Workers
Workers' operation in the link of production is connected with products to realize the tracing on workers, and to find out whether it is caused by workers.