Industrial IoT – Challenges, Risks & Pitfalls

Companies are benefiting big-time by adopting the Industrial Internet of Things (IIoT) technologies. They gain better intelligence, more informed decision-making, increased productivity, improved asset management, and more.

But as with most things, those rewards come with some major pitfalls. After all, you’re looking at increasing the complexity of a system. These devices often monitor and interact with sensitive or critical systems, such as those that maintain smart grids, nuclear plants, safety controllers, and production lines that make hundreds of thousands of dollars in under an hour.

In this article, we’ll look at some of the biggest industrial IoT challenges, risks, and pitfalls that business leaders who choose to implement IIoT could experience.

What are the Risks Associated with Industrial IoT?

Here’s the thing about IIoT: it’s a high risk, high reward endeavor.

But, what exactly are the risks associated with IIoT?

IIoT comes with some unique pitfalls due to its cyber-physical connection. In other words, when something goes wrong in the digital world, the consequences can play out in the real world.

For example, improper integrations–think faulty algorithms or miscalculations–could cause damage to your facility, end-product, or raw materials. Devices might overheat, explode, or malfunction in a way that damages products, equipment, or even injures your workers.

Also, adding more network-connected devices to your environment increases your attack surface. This creates more opportunities for cybercriminals to hack the system–whether as an act of sabotage, an attempt to collect ransom, or a political attack. Sometimes, hackers even gain access to machinery by chance.

However, keeping hackers out of your smart factory system isn’t the only thing you need to worry about. Connectivity, visibility, the skills gap, and ensuring that legacy equipment works with integrated devices all present unique challenges that could make or break an organization’s transformation efforts.

In these next few sections, let’s go over some of the top IIoT challenges.

Challenges with Industrial IoT Integration

Here are some of the primary industrial IoT challenges organizations need to be aware of:

High-Investment Cost

One of the more obvious industrial IoT challenges is the high cost of adoption. Sure, one of the main promises of IoT is that it stands to decrease costs through better asset management, access to business intelligence, and productivity gains.

However, it’s hard for organizations to justify the cost when A: they’re not entirely sure what kind of ROI to expect, and B: they don’t have experience implementing connected systems.

According to Microsoft’s 2019 IoT Signals report, 29% of organizations reported that a lack of resources was one of the top reasons for holding off on IoT adoption.

Secure Data Storage & Management

IoT devices generate a TON of data. A 2018 white paper by IDC estimates that by 2025, there will be 160 zettabytes of data generated globally (10x as much as the world was generating at the time of the report), in part due to increased adoption of industrial-grade IoT devices.

The issue here is, this massive amount of data must be processed extremely fast to detect patterns in real-time.

Given the level of security that IIoT technologies demand, organizations must come up with a plan for streamlining data monitoring, management, and storage, allowing for fast response times to incoming threats. This means organizations must plan for secure, short-term storage solutions (like edge computing), as well as a long-term solution (cloud or data centers) for long-term storage.

Additionally, real-time insights are essential for realizing cost-savings and preventing downtime. For example, an organization might use sensors to monitor the performance of key equipment. In this case, the system should be able to detect wear-and-tear as it happens, enabling users to repair issues before they lead to disruptions in production, which could cost the organization lost time and money.

It’s also worth noting that introducing all of these new sensors, devices, and software may also introduce different types of data that an organization isn’t yet equipped to handle.

For example, a manufacturing company may use an enterprise resource planning (ERP) or material requirements planning (MRP) system that uses a relational database to keep track of inventory, raw materials, SKUs, pricing, and incoming orders.

The problem is, IoT sensors may generate heterogeneous data, which is managed through non-relational databases. And for companies to get the most out of a connected system, ERP data, customer records, and IoT insights need to come together in one, connected view.

Another key IIoT challenge is that even if an organization is able to implement all of the right sensors, software, and equipment, its ROI can only be realized if the organization has both the right tools and expertise in place.

Connectivity Outages

One of the key things that enterprises need to consider ahead of undergoing the big IIoT transformation is that there’s this need for constant, uninterrupted connectivity.

The challenge is, even if you’re just talking about uninterrupted internet uptime, achieving 100% availability is almost impossible. Whether that’s because of maintenance or something else, at some point or another, the connection may be lost.

As such, organizations will need to find a suitable vendor for meeting connectivity requirements to avoid downtime. Unfortunately, requirements vary by industry. According to research by McKinsey, organizations need to consider range, number of locations (i.e., connectivity between multiple job sites/factories), and power consumption. For example, you might look toward cellular connectivity if your system needs a lot of bandwidth, while a low-power long-range solution might be your best bet for monitoring assets for years at a time.

With IIoT, outages introduce several risk factors that go well beyond the annoyance of a temporary WiFi outage. When sensors are being used to detect hazards such as gas leaks, an outage could really be a life or death situation. Smart grid outages can wipe out power for an entire community.

Blending Legacy and IIoT Infrastructure

The more complex your IIoT system, the greater the chances are that your IT admins and OT engineers have the visibility, access, and control over every single moving piece in the ecosystem.

As organizations deploy IIoT devices on legacy equipment and various devices made by different companies, it becomes incredibly challenging for employees to monitor and control the end-to-end operation.

As it stands, there’s no set of standards for how organizations should process data between various devices and machines. There’s no standard for how to ensure interoperability or secure a system that includes equipment that was never meant to be “smart” in the first place.

While IT pros can work with operations teams and leadership to apply the same standards they’ve long used to ensure hardware security and function, it’s not a simple process–especially since no two systems look the same.

Tips for Bringing the IIoT Into Your Manufacturing Business

Organizations must have the following in place to be considered 100% IIoT-enabled:

• Machinery that is equipped with sensors and software capable of collecting and organizing data.
• Robust cloud or edge computing systems that can store and process data in real-time.
• Advanced analytics systems that allow teams to extract and analyze data from connected systems, allowing them to make decisions about internal operations, supply chain optimization, asset management, and so on.
• Employees with a deep knowledge of how to put insights into action to ensure productivity and uptime.

That’s a tall order, especially when you look at manufacturing, utilities, or logistics companies that historically haven’t led the charge when it comes to adopting the latest technologies.

As such, we’d recommend the following tips to ensure smooth adoption and combat the industrial IoT challenges outlined above:

• Get the right experts on your side. Whether you decide to work with a third-party service provider, hire new employees, upskill your team, or all of the above, you’ll need to ensure that you have IT experts to implement proper security measures, data scientists to extract the right insights and operations staff that know how to work with connected systems.
• Set proper controls. Having the right controls in place can help manufacturing teams avoid the kinds of mistakes that result in safety issues, property damage, and incoming security threats.
• Integrate data properly. Organizations need to figure out how they’ll integrate new IoT data within their current architecture. For example, how will IIoT-generated data fit with current storage and data management systems like enterprise resource platforms (ERPs), databases, communications systems, etc.?

From there, they’ll also need to think about how to connect data collected from legacy devices with new technologies. Ultimately, the goal is to ensure that all of these technologies work seamlessly together to paint a unified picture of the business’ health.

Selecting the Right Partner To Help With IIoT Integration

With IIoT integration, there’s a lot that can go wrong. You’re bringing the physical and digital world together–combining sensors and advanced analytics with legacy equipment that was built for another time.

Cyberthreats loom large, as does a lack of standardization, and the challenge of not only gathering and storing data but putting it to good use.