Machines on the plant floor will soon actively identify problems, determine a course of action, execute, and measure those results—all without human interaction. It’s not the Jetsons—it’s the Industrial Internet of Things (IIoT), and it’s already beginning to reshape manufacturing. Though many manufacturers are just starting to explore the implications of IIoT, the Internet of Things (IoT) has been generating buzz for years and already represents a booming market opportunity.
The Internet of Things refers to a network of physical objects equipped with sensors that collect data and “communicate” that data to other machines (or back to humans) instantaneously. Built on cloud computing, this machine-to-machine interaction is set to make everything in our lives “smart,” from thermostats that set themselves to refrigerators that re-order our milk.
One McKinsey report estimates that IoT will have a potential economic impact of up to $6.2 trillion by 2025. With numbers like those, many manufacturers are embracing the transition to IIoT as a natural next step in the innovation lifecycle. A recent study by PwC found that 34% of manufacturers believe it is “extremely critical” that US manufacturers adopt an Internet of Things strategy in their operations.
As those manufacturers ahead of the Industry 4.0 curve are already seeing, IIoT has important applications on plant and distribution
center floors. Connected to either the cloud or in-house servers and equipped with unique IP addresses, manufacturing equipment in the modern factory is collecting data about when a machine is in use and how it is working, among many other potential applications. The result? Manufacturers now have more raw data than ever before, and sometimes more than they know what to do with.
Increasingly, manufacturers are using big data and advanced analytics to scrutinize the massive amounts of data being collected by their smart machines. These evaluations are yielding valuable insights into plant workflows, including predicting maintenance needs before equipment breaks and tracking parts as they move through the supply chain.
By remotely monitoring product performance, companies are able to prevent unplanned maintenance and parts loss, dramatically reducing downtime and enhancing productivity. They’re then able to pass these insights onto their customers, improving customer service and even-some studies suggest-creating new revenue streams. In surveying more than 1,400 C-suite decision makers, Accenture found that the vast majority (84 percent) believe their organizations have the capability to create new, service-based income streams from the IIoT. Similarly, PwC predicts that manufacturers will continue to unlock new “product-as-service” models based on their ability to gather big data and provide their customers with actionable recommendations for improvement based on their findings.
Ahead of many other machines on the factory floor, VGVs themselves are sensors that accurately and consistently capture performance data. Employing vision technology, VGVs gather thousands of important data points per second, and provide insights into distance traveled, total errors, obstruction hours, follow hours, motion hours, powered hours, and rescue hours.
Arguably as important as collecting these data points is conveying them to the end-user (in this case, plant managers) in a way that is both comprehensive and intuitive, whether through fleet data reports or easy-to-use dashboards. Importantly, this allows the plant manager to identify inefficiencies and potential problems before they affect throughput productivity.
Increasingly, companies like Seegrid that are invested in IIoT will continue to release dynamic metrics to improve enterprise-wide global operations. In the future, VGVs will use big data to not only identify problems, but to execute a solution, and measure the results–all without human interaction.
Widespread adoption of IIoT will take time, but innovative manufacturers are already investing in data analytics, and they’re seeing improvements in improved productivity, downtime, and even new revenue streams. Manufacturing is at a crossroads, and the companies that understand and embrace the power of big data will be the ones to thrive in the future of manufacturing.
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