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Assist in the digital transformation of the automotive industry
MatriXFactory
Assist in the digital transformation of the automotive industry
Automakers use digital and intelligent means to comprehensively digitize research and development, manufacturing, marketing, and supply chains
Upgrade and transform into a data-driven technology platform company, thereby achieving business model innovation
Core demands
Establish a standardized, centralized, and interoperable data platform to achieve algorithm models for motor health prediction analysis, robot health prediction analysis, vehicle accuracy trend analysis, stamping automatic scheduling, and online monitoring of oil products.
95%
Realize comprehensive collection of manufacturing process data with a networking rate exceeding
1s
Various types of data with over a million fields and collection time below
40Kpi
Lay a solid foundation for subsequent upgrades
Edge computing framework of stamping, welding, painting and final assembly workshops
The edge computing system in this project is composed of edge computing software platform, edge computing data center that can be distributed and deployed, edge computing workstation, edge computing intelligent terminal and other software and hardware systems. The system should be able to handle massive heterogeneous real-time data reception, processing, parsing, storage, calculation, forwarding, and other functions. At the same time, it should be able to support secondary development of low code applications and analysis functions on the platform.
01 Ultra high frequency and massive remote edge data a...
It is not allowed to transmit data layer by layer through PLC. It should be calculated and preprocessed at the edge computing intelligent workstation, and then send the results of analysis and calculation to the APP deployed in the inter level edge data. At the same time, it can also interact with all the applications planned in this project and the da...
02 Ultra high frequency and massive remote edge data a...
It is not allowed to transmit data layer by layer through PLC. It should be calculated and preprocessed at the edge computing intelligent workstation, and then send the results of analysis and calculation to the APP deployed in the inter level edge data. At the same time, it can also interact with all the applications planned in this project and the da...
03 Ultra high frequency and massive remote edge data a...
It is not allowed to transmit data layer by layer through PLC. It should be calculated and preprocessed at the edge computing intelligent workstation, and then send the results of analysis and calculation to the APP deployed in the inter level edge data. At the same time, it can also interact with all the applications planned in this project and the da...
01 Ultra high frequency and massive remote edge data a...
It is not allowed to transmit data layer by layer through PLC. It should be calculated and preprocessed at the edge computing intelligent workstation, and then send the results of analysis and calculation to the APP deployed in the inter level edge data. At the same time, it can also interact with all the applications planned in this project and the da...
02 Ultra high frequency and massive remote edge data a...
It is not allowed to transmit data layer by layer through PLC. It should be calculated and preprocessed at the edge computing intelligent workstation, and then send the results of analysis and calculation to the APP deployed in the inter level edge data. At the same time, it can also interact with all the applications planned in this project and the da...
03 Ultra high frequency and massive remote edge data a...
It is not allowed to transmit data layer by layer through PLC. It should be calculated and preprocessed at the edge computing intelligent workstation, and then send the results of analysis and calculation to the APP deployed in the inter level edge data. At the same time, it can also interact with all the applications planned in this project and the da...
01 Ultra high frequency and massive remote edge data a...
It is not allowed to transmit data layer by layer through PLC. It should be calculated and preprocessed at the edge computing intelligent workstation, and then send the results of analysis and calculation to the APP deployed in the inter level edge data. At the same time, it can also interact with all the applications planned in this project and the da...
02 Ultra high frequency and massive remote edge data a...
It is not allowed to transmit data layer by layer through PLC. It should be calculated and preprocessed at the edge computing intelligent workstation, and then send the results of analysis and calculation to the APP deployed in the inter level edge data. At the same time, it can also interact with all the applications planned in this project and the da...
03 Ultra high frequency and massive remote edge data a...
It is not allowed to transmit data layer by layer through PLC. It should be calculated and preprocessed at the edge computing intelligent workstation, and then send the results of analysis and calculation to the APP deployed in the inter level edge data. At the same time, it can also interact with all the applications planned in this project and the da...

Stamping, welding, painting, and final assembly
Edge computing effect of four workshops
The edge computing system in this project consists of edge computing software platform, edge computing data center that can be distributed and deployed, edge computing workstation, edge computing intelligent terminal and other software and hardware systems. The system should be able to handle massive heterogeneous real-time data reception, processing, parsing, storage, calculation, forwarding, and other functions. At the same time, it should be able to support secondary development of low code applications and analysis functions on the platform.
95%
Realize comprehensive collection of manufacturing process data with a networking rate exceeding
1s
Various types of data with over a million fields and collection time below
40Kpi
Monitor 40 production KPI indicators, laying a solid foundation for subsequent upgrades
800+
Optimize the process with 100+items and 8 major modules, 48 functions and 800+function points (5 modules in the same row)
4
4 decision models for equipment maintenance dispatch, anomaly tracing, fault resolution plan push, spare parts inventory warning, etc. (1 in the same row)
5
5 algorithm models including motor health prediction analysis, robot health prediction analysis, body accuracy trend analysis, stamping automatic production scheduling, and online monitoring of oil products (2 in the same row)
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