Infineon Case Studies How Edge Computing Enables Predictive Maintenance of Valves
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How Edge Computing Enables Predictive Maintenance of Valves

Infineon
How Edge Computing Enables Predictive Maintenance of Valves - Infineon Industrial IoT Case Study
Analytics & Modeling - Edge Analytics
Analytics & Modeling - Machine Learning
Platform as a Service (PaaS) - Edge Computing Platforms
Processors & Edge Intelligence - Embedded & Edge Computers
Semiconductors
Discrete Manufacturing
Edge Computing & Edge Intelligence
System Integration

Solution approach for monitoring production-critical ultrapure water valves with the aim of detecting possible failures at an early stage and better planning maintenance processes.

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A multinational semiconductor contract manufacturing and design company incorporated in the Cayman Islands and headquartered in Malta, New York.

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GlobalFoundries

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Edge AI sensor platform. Features:

  • Multicore: 9 RISC-V cluster cores
  • 4MB RAM & 1MB MRAM
  • Rich digital & analog interfaces
  • CAN-FD Core
  • Ethernet-TSN Core
  • High Security: TRNG, OTP, AES, Secure Boot…
  • Variety of supported Sensors
  • Customizable Package-on-Package Peripherals
  • Software SDK & Examples

Embedding AI in smart sensors.

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[Data Management - Connectivity Stability]

Application-independent, the solution prevents downtimes in production through AI-based early fault detection.

Edge AI - benefits and advantages:

  • Increase performance by reducing latency
  • Large number of data points can be measured
  • Evaluation even without the internet
  • No data transfer between shopfloors, countries etc. needed
  • Companies can expand their computing capacity through a combination of IoT devices and edge data centers
[Efficiency Improvement - Maintenance]

Thanks to the scalable edge computing solution, incipient defects are now detected at an early stage. Maintenance measures can be planned effectively. Monitoring of the valves is possible in real-time even if the WLAN connection is briefly interrupted and is visualized by means of a clear dashboard.

  • Maintenance processes can be planned in a demand-oriented and cost-efficient manner.
  • Data-based condition monitoring is possible in real-time.
  • Fail-safe operation of the production facilities.
  • Time & personnel expenditure in the maintenance process is reduced.
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