How the IIoT will help manufacturers in 2020

Dec. 23, 2019
Boosting productivity, cutting costs in the coming year.

By Sam Cece, Founder, President, & CEO of Swift Sensors

The IIoT will have a big impact on industrial productivity and cost savings in the year ahead. Already, 62% of the industrial-manufacturing sector is using IoT technology in operations, and that number is almost sure to rise in the coming months. That’s why it seems like everyone’s talking about the IIoT right now.

Swift Sensors' Sam Cece

However, not everyone is talking about it the same way.

Technology fans, analysts and the media often focus on IIoT devices’ technical specifications and capabilities, which are fascinating and exciting. However, the managers I talk with at plants around the country focus on how internet-connected sensors can solve the specific problems they face.

Based on those discussions about their goals, here’s how I think the IIoT will help manufacturers in 2020.

Predictive maintenance will reduce downtime

A lot of manufacturing plants have a major maintenance challenge: equipment that’s been in use for decades. When these aging compressors, condensers, conveyors and motors break, manufacturers often have to fabricate replacement parts on-site because no one stocks them anymore. When breakdowns happen without warning, line stoppages can last for days or weeks until new parts are made and installed.

Predictive maintenance (PdM) enabled by remote wireless sensors can alert managers whenever a machine is operating outside its normal parameters. By predicting failure well ahead of time, this IIoT application gives companies advance notice to start fabricating replacement parts. That can reduce unplanned shutdowns and increase uptime by up to 20%, according to Deloitte. Over time, as the sensor network collects more data for analysis, the predictions become more refined and precise, allowing for even better planning.

Sensors will support the transfer of worker knowledge

One way that factories without PdM try to stay ahead of equipment failures is by using the insights of their most experienced people. There’s a generation of factory workers who’ve been on the job for two or three decades. Some of these people know the equipment they work with so well that they can diagnose problems by sound.

Now many of those workers are reaching retirement age, and that poses a problem. How do you transfer sensory knowledge about individual pieces of equipment—insights that took years to develop—to new employees before that knowledge is lost? 

Wireless sensor data can help. For example, new hires can shadow senior workers to learn how they monitor and manage the equipment. During that time, the newer worker gets two sets of information about how the machines operate. The first is from the senior worker, who can diagnose equipment by changes in sound or vibration. The second is from the machine’s sensor data.

By correlating the sensor data with input from senior workers, new hires can see what the sensor readouts look like when equipment is working well and when there’s trouble brewing. This can help bridge the knowledge gap between soon-to-retire employees and newer team members, preventing breakdowns and reducing unplanned downtime.

Tracking assets will be easier and more cost effective

The ability to track asset locations with low-cost IIoT sensors will help food, pharmaceutical and other manufacturers who need to monitor products in transit. Tracking can also help plants safeguard valuable equipment. For example, an aerospace manufacturer uses remote wireless sensors to track the location of its specialized mobile presses that move between fabrication stations inside the factory.

Identifying areas for efficiency gains will be simpler

Triaxial-vibration sensors can monitor moving equipment for predictive maintenance. They can also show how much each piece of equipment is being utilized. One client was debating whether to purchase another costly piece of equipment, but with vibration sensors installed, they were able to see that equipment utilization varied widely between shifts. With that data, managers were able to work with shift leads to resolve the issue without a multimillion-dollar expenditure.

5G will add more IIoT capabilities—eventually

It may not happen in 2020, but once 5G is fully operational, edge computing will change the sensor-network game. When the 5G network is strong and comprehensive I think we’ll see a wave of new devices that deliver more precise tracking and clearer sensor readings over a larger network.

Customers will drive use case development

As powerful as IIoT technology is, it’s manufacturers who are driving new IIoT applications in plants. They’re the ones developing use cases for equipment utilization, knowledge transfer and more. Plant managers are the ones looking for ways to prolong the life of their existing equipment so they can postpone expensive replacement projects.

Wireless sensors help them achieve those goals first. Then the sensor network may enable an IIoT project.


By deploying a sensor network, managers get real time insight into their business. When they have sensor data to enable predictive maintenance or automate processes like hourly temperature readings, their initial problem is solved. They can do much more with the collected sensor data, and that usually happens when the QA team digs in and starts comparing and correlating data points. Now what started as a solution to one or two problems is an IIoT project—but it’s still primarily about getting insights that help manufacturers solve problems.

As more manufacturers install sensors and start collecting data, I expect to see plant managers develop new IIoT use cases based on their needs. That’s a trend that we should all be watching closely in 2020 and beyond.