Real time summary data

Real time data collection is mainly divided into data collection and display on the control platform,

Set: production line equipment data, model data, production progress data, quality data, logistics data, NC program, etc. are transmitted to the data center in real time through automatic collection, barcode scanning collection, terminal input collection, etc.

Mainly used in:

1) Summary data of key indicators, multi category and multi-level

Gather the physical and information fusion data of all elements / businesses / processes in the workshop, and establish an index system with efficiency, quality and risk as the main dimensions.

2) Data presentation multi terminal multi dimension

Business Kanban, digital virtual simulation workshop, video monitoring and other information can be viewed through PC and mobile terminal.

3) Virtual and real interactive feedback, 3D scene linkage

Driven by the twin data of the workshop, the real-time monitoring, process optimization and remote control of the whole product processing process are realized.

4.2 intelligent problem finding

Intelligent problem finding is mainly divided into explicit problem discovery and implicit problem mining in the control platform. Explicit problem discovery can be realized through clear state perception in the production process, including real-time perception of equipment working conditions, production beat, process reality, material information, personnel operation, energy consumption change, product quality and safety environment in the workshop production process. Hidden problem mining is based on three-dimensional simulation. It is mainly based on the digital twin intelligent workshop. Through the application of big data and production system model, the multi-level index connection response mechanism established can timely simulate the production situation, and realize process difference feedback and historical link tracing with the help of virtual and real comparison.