Fluid Gas Handling

Condition Monitoring for Today’s Metal Fab Industry

Condition Monitoring for Today’s Metal Fab Industry - metal working machine - SensoNODE - Quick Coupling Division Parker Hannifin As today’s metal forming plants become more complex, detecting and identifying issues with all of the moving parts is becoming increasingly important, though time-consuming. Traditional manual data collection processes, even when employed skillfully, can eat up several labor hours and be subject to recording errors.

Typical mills that have hundreds of machines can require thousands of individual measurements taken each month. Under typical conditions, this can consume about one to two man-weeks of measurement effort, and another man-week to analyze that data, eating up high percentages of recurring operating/labor costs.

Cut the manual monitoring leash

Wireless condition monitoring systems rooted in the Industrial Internet of Things (IIoT) reduce labor costs by allowing plant personnel within range of IIoT-enabled sensors to instantly access condition levels with their mobile device. Sensors placed at several points throughout a process allows users to gather information for multiple conditions simultaneously:


Most metal forming assets are hydraulically or pneumatically driven, so ensuring the right amount of pressure is being applied protects against failure or overload of assets, including:

  • Roll formers
  • Punch, stamp, and turret presses
  • Cutting, bending, and assembling machines
  • High-flow water lines


Monitoring in-line and ambient temperatures of any metal forming asset is necessary to ensure consistent adherence to strict tolerances to avoid overheating and asset overwork.


High humidity levels can cause corrosion and rust in both equipment and your final product. Tracking ambient and in-line humidity levels in your plant help you make the necessary adjustments to keep them within acceptable levels.

Condition Monitoring for Today's Metal Fab Industry - image of ipad with sensor on machinery - Parker Hannifin SensoNODEWireless condition monitoring also helps reduce maintenance costs by making accurate record-taking easier, allowing workers to chart them more often. Condition monitoring for predictive maintenance lets operators see which assets aren’t performing at optimal levels, helping them to:

  • Identify and address issues before they escalate to serious problems.
  • Make better decisions about maintenance activity.
  • Optimize assets for more efficient and effective performance.

Keeping assets at optimum working conditions helps to reduce unplanned downtime, scrap and rework.

Parker’s solution

Parker’s SensoNODE™ Blue sensors and SCOUT™ mobile software create a wireless condition monitoring for predictive maintenance solution that is accurate, reliable, and easy to use.

SensoNODE sensors are lightweight and durable, making them ideal for placement just about anywhere on the production line. Using Bluetooth technology, they wirelessly transmit data to SCOUT™ mobile software on a mobile device, allowing plant managers, maintenance, and operators to record the data they need. This helps to:

  • Improve labor efficiency
  • Keep workers out of potentially dangerous situations
  • Perform diagnostics without shutting down production


Condition Monitoring for the Metal Forming and Fabrication Industry - cover photoView our condition monitoring bulletin and visit our website for more on how Parker’s condition monitoring solutions can help strengthen your bottom line.












Additional related content on condition monitoring and preventative maintenance:

Scrap Happens – Save Money by Reducing Rework

Preventive Maintenance vs. Predictive Maintenance

Effective Predictive Maintenance of Rotary Machines

Efficiency is King In a Technological World

Condition Monitoring in Injection Molding

Streamline Your Condition Monitoring Process

Size Matters: Small, Wireless Sensors Make Diagnostic Efforts Easier for Mobile Equipment

Improve Solar Panel Maintenance and Condition Monitoring Efficiency

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