By: Emily Newton, Tech and Industrial journalist, and Editor-in-Chief , Revolutionized.
Risk management, as a whole, is about regularly analyzing, identifying, and reacting to potential risk factors throughout the life of an operation. It’s ultimately about proactive management and solutions. Want to guess how you can drive proactive and preemptive systems?
If your answer is through the deployment of smart and connected technologies — like the kind established under Industry 4.0 — then you’re already one step ahead.
What Does This Have to Do with Industry 4.0?
Industry 4.0 is a digital revolution for the manufacturing and commercial industries. It calls for the use of smart technologies, including IoT sensors, to generate contextual data to inform and drive future action. But it’s how that data is used that defines this new generation of operations.
The contextual data doesn’t just enable proactive responses. It also empowers automation and efficiency to boost output, reduce operating costs, and improve the entire supply chain. By its very nature, it deals with the concept of risk management.
In other words, when manufacturers and commercial entities adopt Industry 4.0 technologies and solutions, they are by extension also adopting more complex yet effective risk management solutions. However, let’s make it clear that just because you are taking on something like that, it doesn’t necessarily mean you’re going to put it to good use.
Why Risk Management Is Crucial to Industry 4.0
A massive influx of smarter and more actionable data doesn’t mean much if you’re not leveraging the insights it provides. If it’s all just flowing constantly into the machine, driving automation and reactive systems — with little to no oversight — risks are increased exponentially.
A paper on emerging risk management in Industry 4.0 explains it best: “Industry 4.0 enables real-time planning of production plans as well as dynamic self-optimization. The productive model based on Industry 4.0, in addition to improving processes in terms of efficiency and quality, can help improve safety as well as sustainability and the industry image.”
“However, industrial processes configured for advanced manufacturing processes and technologies can increase levels of complexity of production processes and introduce high dynamism into processes, creating the so-called smart working environments.”
What’s more, the data being collected, processed, analyzed, and leveraged can contain highly sensitive details about an operation, including trade secrets. While that data may be necessary to keep the operation going, it can also bring down an entire organization if it falls into the wrong hands. This introduces a whole new layer to risk management requirements.
Applying the Data to Risk Management
The Industrial Internet of Things (IIoT) and similar technologies are becoming more prevalent in the manufacturing and commercial industries, and it’s for the better.
They are helping to transform legacy operations through the kind of contextual data we’ve already discussed. They also pose many new challenges and present new opportunities for failure all across the supply chain, not just within manufacturing facilities and plants. This is a huge problem, and it’s going to get worse before it gets better.
Fortunately, there are programs in place to help organize and improve risk management strategies, even with the rollout of Industry 4.0. ISO 27001, for instance, proposes an information security management standard for effectively managing related risks and appropriately dealing with cyber-threats.
As more data is generated and handled, it’s only natural that new vulnerabilities will appear, as well as many potential vectors of attack. Organizations will have to address these challenges and come up with new ways to protect their operations, digital assets, and sensitive information.
But it’s not all about the security of the data. Beyond cyber risks, it’s also essential that the available information is being properly utilized.
Industrial analytics can enable systems like self-diagnosis for manufacturing gear, identify efficiency bottlenecks, improve supply chain communication collaboration, and so much more. It shows just how critical Industry 4.0, and its related technologies are to the future of manufacturing and the industrial world.
Some of these data points, such as equipment self-diagnosis, lower risks merely by empowering new opportunities. If you know the performance of a machine and can compare those statistics with historical data, you can accurately identify when equipment might fail, malfunction, or die completely.
This significantly lowers risk by allowing for proactive solutions, which is the key to risk management. In that scenario, maintenance crews can repair or service the equipment in advance to prevent downtime. Or, if you know the hardware is going to fail altogether, you can order and have a replacement at the ready.
This brings up an important distinction, and it’s that Industry 4.0 data is flowing, processed, and available in real-time. Because these solutions are always-on and constantly reporting information, manufacturers can react at unprecedented speeds. Again, this contributes to a more proactive approach, as opposed to reactive, which is crucial to successful risk management programs.
Industry 4.0 Tricks of the Trade: A New Normal
While many have hailed Industry 4.0 as a revolution, and rightly so, it’s not all that different from previous operational generations. The most significant difference is that you’re taking the digital insights and applying them to future actions and events. Most importantly, it’s about doing that as an automated and smarter process to boost efficiency, output, and reliability.
Initially, that lowers risk by eliminating some of the operational challenges you might see without Industry 4.0 in place. At the same time, it also increases risk in other areas, namely in IT and cybersecurity.
That makes it clear that Industry 4.0, as beneficial as it may be, still comes with a unique set of challenges and complications, which we all must acknowledge and react to. We must prepare, plan, and react to ensure risks new and old are accounted for. What is that, if not the general foundation for risk management?
