Plant machinery is costly and can last decades, which means manufacturers often cannot afford to keep up with the breakneck speed of technology. For many processing manufacturers, replacing working machinery with new equipment designed with smart technology simply doesn’t make financial sense. Bridging the gap are Internet of Things (IoT) providers that use gateways to efficiently and affordably connect legacy equipment to the cloud, delivering robust cutting-edge insights while also allowing processing manufacturers to get the full life value out of costly equipment.

The technology varies from provider to provider, but generally IoT platforms connect motors and machinery to the cloud via circuits that collect data from small sensors. The sensors can record a wide array of metrics from vibrations to moisture to temperature, etc. Using the cloud, the data is then sent to a desktop or mobile device for easy access and analysis by company operators.

IoT is not just another trend liable to pass when the next big thing arrives. Rather, the technology makes previously unavailable data accessible, allowing manufacturers to have a holistic view of how their machinery is performing, which results in better control of their systems, decreased downtime and increased efficiencies of energy, materials and manpower. Diagnostic data can be extracted from any part of the process, leading to more accurate predictions and informed actions; plant managers no longer have to guess at the right course of action. With such benefits, it is no wonder the manufacturing sector is predicted to invest nearly $190 billion in the IoT in 2018 alone, more than any other industry.

Machinery breakdowns can cause massive revenue loss, which is why predictive maintenance is perhaps the biggest impetus behind processing manufacturers’ dive into IoT. Research by IoT Analytics says that investment into predictive maintenance technology will reach $10.9 billion by 2020, up from $2.2 billion in 2017. Companies that make the investment are seeing returns, with efficiency gains of around 30 percent.

A plant engineering company, for instance, implemented an IoT platform to measure the temperature, vibrations and rpm of plant machinery motors. With these predictive metrics, plant operators know immediately any time an anomaly occurs and can get ahead of the problem before it causes a costly plant shutdown.

Bringing manufacturing into 2018

For processing manufacturers wanting to take advantage of IoT technology, it is important to know that most companies start small, integrating one use case and adding on over time rather than connecting the entire process at once.

Additionally, when it comes to legacy machinery, getting connected to the cloud doesn’t require hiring a tech team or building an entire system in-house. Many IoT platforms are scalable, so it is just as easy to connect one sensor as it is to connect 100. Many also operate under a “platform as a service” model, which means integration is cost-effective and quickly delivers customized data to manufacturers.

Before integrating with an IoT platform, manufacturers need to consider a few factors:

  1. Where are the problem spots in the process? Before manufacturers can decide on the most valuable use case to test out IoT technology, they need to narrow in on the desired outcomes. A smart place to start is looking at what step in the process failures, slowdowns or downtime tends to occur. Additional areas that might be good candidates for an IoT upgrade include steps that cause an increased safety risk or that consume energy resources. Finally, consider parts of the process that require manual labor that could be automated. For instance, utility companies use IoT platforms to track pole movement. The sensors immediately notify operators when unusual movement is detected or a pole goes down, so the problem can be immediately pinpointed and corrected. This drastically cuts down on the manual checks required to maintain the integrity of the power grid.2.
  2. How do IoT platforms differ? IoT platforms vary in the level of customization they offer, as well as their flexibility, pricing structure and how the data is analyzed and accessed. Manufacturers should look for a platform that provides end-to-end installation and service, encompassing everything from the sensor to the delivery of data.
  3. How will the data be stored, analyzed and delivered? The amount of data communicated is another important consideration. For instance, if every data point is delivered to the mobile or desktop app, plant decision-makers will drown in thousands of data points and likely won’t be able to translate the data into actionable insights. Look for a platform that can learn the “normal” state of whatever is being monitored and report only the exception occurrences. Security needs to be considered as well — edge computing stores data on the sensor’s circuit itself, rather than downloading it to a single database, decreasing the likelihood of a systemwide data loss. Edge computing also makes IoT more feasible economically, because sending vast volumes of data to the cloud and paying for its storage would be outrageously expensive and also would gobble up the circuit and sensor’s battery life.
  4. What processes need to be developed to ensure the data gets used? All the data in the world is no good to a company if smart processes aren’t in place to make sure the data is accessed and understood. Plant manufacturers need to determine who will be responsible for receiving or checking data and who will be making decisions based on the insights.
  5. How will IoT’s benefits be tracked? To justify additional use cases for IoT integration, plant manufacturers need to track the benefits derived from the technology. Depending on what IoT is measuring, operators should have benchmark numbers in place to compare the status before and after integration.

Perhaps no industry evolves as quickly as technology, but that doesn’t mean processing manufacturers have to suffer through long machinery lifespans before reaping the latest technology benefits. By integrating with an IoT platform that uses gateways to turn legacy objects “smart,” manufacturers can begin discovering and correcting inefficiencies, preventing mistakes and increasing their bottom lines.

 

Guy Weitzman, the CEO and co-founder of Atomation, served for eight years in intelligence operations and technology with one of the Israeli Army’s intelligence units. Prior to founding Atomation, Weitzman spent time in R&D and operations roles for internet, mobile and cellular companies. He also managed M&A and investment deals for Mail.RU, an international internet company. Overall, he has more than 12 years of experience in product, operations and business development in technology, internet and mobile fields. Weitzman can be contacted at guy@atomation.net.