Highlights
  • More than 20 independent machine types used to make industrial cable with no visibility into performance
  • Manual recording of setup configurations with no way to correlate parameters and results
  • Litmus Edge connected to all machines, as well as third party laser micrometers, enabling out-of-the-box access streaming real-time data
  • Quickly visualized data at the edge for immediate maintenance and operator use and integrated with Azure for site-level analytics
  • Achieved real-time visibility into quality and asset performance with a 10 percent reduction in costs

The cable manufacturing division of a global energy company manufactures armored cables for oil and gas equipment. With more than 20 different types of machines on the floor used throughout the cable manufacturing process, the customer was faced with a mix of modern and legacy PLCs, no centralized data collection, and zero visibility into real-time machine performance or part quality metrics.

A typal production run on one machine could last 8-12 hours to create a spool of cable. Each run was somewhat of a mystery to maintenance and plant managers – they had no data on when or why machines went down, what happened on each shift or actions taken by the operator. At the start of each run, operators were performing setup configurations on each machine such as temperature or tension and manually recording the setup on paper. With no way to monitor and store setup parameters or observe asset health, they could not determine ideal operating conditions or establish any correlation between machine behavior and resulting part quality to make improvements.

The company set out to modernize by adopting Industry 4.0 technologies with the goal to implement a closed-loop control system that would collect data from production machines and provide real-time feedback for process improvement. They chose the Litmus Edge Industrial IoT platform to connect, collect and standardize data from the CNC machines, then analyze the data and deliver it to both the cloud and back to the automated control system in real-time.

Litmus Edge captured all streaming CNC data, stored it at the edge in a SQL database and integrated it with Azure for site-level analytics. Litmus Edge provided analytics on all the customer’s key variables such as motor speed and temperature with simple, easy-to-access dashboards. They added high- and low-level alerts for quality and downstream integration with optical micrometer data to allow operators to make better decisions during production to improve quality.

With Litmus Edge in place, the customer achieved real-time visibility into the shop floor with the ability to check machine and production info from any device. Site-level data integrated to Azure allowed them to do advanced analytics on throughput and the correlation between settings and first pass quality. They compiled equipment efficiency metrics and used them to adjust manufacturing processes and create alerts for key maintenance team members, realizing an estimated 10 percent reduction in manufacturing costs thanks to adopting the Litmus Edge Industrial IoT platform for visibility into machine performance.