Solution Overview

This solution uses a combination of sensor and PLC data to monitor for and predict production cycle failures. Combining Cisco Kinetic Edge management with Cisco IR800 series IoT Gateways, Panduit sensor technology and Microsoft Azure Cloud based IoT Middleware, & Analytics this solution is able to process event’s locally and enforce local workflows if needs be, whilst giving a global view of the production and output using advanced analytics and machine learning to predict machine failure.


Customer Challenges

  • Pressure from customers and the business to increase productivity and output.
  • Very expensive to the business in the event of unplanned downtime.
  • Wide and varied mix of different production line machinery meaning a wide variety of protocols to manage and data formats to work with.
  • Need to improve OEE (Overall Equipment Effectiveness) values across the business.

Features and Benefits

• Streamline data extraction from controllers, machines, sensors, and connected devices to make data usable.
• Optimize data computing to filter and transform it, apply business rules and perform distributed micro-processing from edge to endpoint
• Control data movement programmatically to the right applications at the right time, and enforce governance policies for secure, reliable delivery



Cisco Kinetic provides simple, automated, secure data interactions to ensure you get the most out of your IoT data, and use it to optimize your business:


• Reduce test time and calibration – Establish and record machine calibration data points to predict test results and calibration parameters.
• Improve quality – Reduce the cost of producing scrap (bad parts) by identifying the root cause for scrap and self-optimizing the assembly line.
• Lower energy costs – Proactively monitor energy consumption to identify areas for cost reduction and view resource consumption by process.
• Increase yield – Develop benchmark analysis across lines and plants to improve first-pass yield and pinpoint causes of performance bottlenecks
such as OEE or cycle time.
• Perform predictive maintenance – Analyze machine health to identify top causes of failure, and predict component failures to avoid unscheduled machine downtime.

  • Type of Asset
    Plant Machinery, Production Line
  • Purpose
    Equipment Monitoring, OEE Optimization, Predictive Maintenance
  • Connectivity
    Wired, WiFi, Cellular
  • Used Sensors
    Vibration, Temperature, Accelerometer
  • Protocol Integration
    Industrial Ethernet, ModBus, Profinet, Ethercat, IO-Link

EMEA, North America