The widespread use of computers and automation (considered the third industrial revolution following electricity-powered assembly lines and mass production, and, prior to that, machines running on water and steam power) gave way to the fourth industrial revolution. Industry 4.0, as it is known, is now building on that technology wave by enhancing machines, computers and automation with smart and autonomous systems.

Today’s manufacturing requires speed, accuracy, agility and responsiveness throughout the manufacturing process. From prototyping, development and production to logistics and supply, machines must do far more than churn out widgets. In the current global economy, they must communicate with each other; adapt to changing circumstances; collect, track and analyze data; and alert people or other machines when a problem (or potential problem) is encountered. The ability to maximize operational effectiveness and improve production quality requires sophisticated remote monitoring.

Figure 1. Data is at the heart of Industry 4.0 and is a crucial part of the development, implementation and advancement of the smart factories, connected machines, intelligent robots and even the autonomous vehicles and drones that keep cutting-edge industry rolling.

Data is at the heart of Industry 4.0 and is a crucial part of the development, implementation and advancement of the smart factories, connected machines, intelligent robots and even the autonomous vehicles and drones that keep cutting-edge industry rolling.

Remote monitoring offers numerous advantages in the implementation of Industry 4.0 and handling big data. The i-Alert system, which is an industrial internet of things (IIoT) cloud-based asset intelligence platform, uses Bluetooth-enabled sensors placed on or near critical assets such as fans, pumps and motors, for continuous monitoring of key data. Personnel can safely and securely access the necessary information via a smartphone app without coming in contact with dangerous machinery. Information can also be accessed from equipment in distant or difficult to reach locations. Multiple sensors within range can be monitored simultaneously. Data from all assets can be managed from a central location and shared, giving manufacturing engineers real-time data about machine operations, maintenance and history.

Predictive maintenance is another way Industry 4.0 uses remote monitoring. Just as companies need healthy employees, manufacturers need healthy machines. Downtime due to equipment failure is costly and time-consuming. Waiting for something to break prior to fixing or replacing it is not a viable option. Scheduled maintenance can prevent failures but may do so at the cost of taking machines offline unnecessarily.

Technology that allows machines to monitor their own health, gather and analyze the data needed to maintain and improve efficiency, and send alerts before the need for maintenance or repair becomes critical solves the problems associated with previous maintenance strategies.

Even slight changes in vibration, temperature, pressure or run time can indicate a maintenance need. Automated systems and connected machines use sensors to monitor data regarding these factors and any changes that occur. The data is used to diagnose potential problems and initiate the appropriate alerts so that maintenance, repairs or adjustments can be completed quickly and seamlessly. Remote monitoring for predictive maintenance allows personnel to monitor multiple machines at once, upload and share information, and most importantly, facilitate repairs so that time-consuming, expensive breakdowns, as well as unnecessary shutdowns, are avoided.

All of this monitoring technology creates huge amounts of data that need to be analyzed. Businesses that make the most of that data will be better able to respond to market changes, capitalize on opportunities and remain competitive.