Machine Health Is the Key to Fully Realizing Industry 4.0 — and Moving Beyond

Between the third and fourth industrial revolutions, the application of knowledge experienced a near-seismic change. Almost overnight, it felt like companies jumped from an analog world to a digitized realm. Thanks to digitalization, once-massive tasks could be executed with improved quality and unprecedented speed.


Introducing: AI

Now, manufacturing companies are experiencing another transition, moving past the static digitized world to one marked by artificial intelligence. AI collects and analyzes vast quantities of data beyond what people can process. While software works from human-programmed heuristics to solve problems, AI will speed the industry beyond these simple if/then scenarios. With AI, manufacturing workers can identify and untangle problems more easily and creatively and, as a result, work more autonomously.


Like any new technology, AI solutions face adoption and cultural challenges. Even with Industry 4.0 technology, manufacturers sometimes fail to adapt to the solutions available to them. Industry 4.0 solutions — including cloud computing, the Internet of Things, and computational intelligence — can't improve efficiency if manufacturers are complacent about leveraging them to solve their most pressing problems.


Enabling the Full Potential of Industry 4.0

Industrial manufacturers are facing challenges around reaching business goals that boost the bottom line, including reducing energy use for greater sustainability, empowering the workforce to innovate, and more effectively getting consumers what they need using minimal resources. These are problems that really can't be solved with only a huge amount of intelligence — but they can be approached successfully using AI.


Before Industry 4.0, you didn’t always know whether a change in one aspect of production would impact everything else down the line. With Industry 4.0, on the other hand, analytics can deliver previously unknowable insights. Maybe you want to increase your throughput. AI insights could help you see whether this would affect the quality of your product or grow energy usage, for example. Knowing this information as soon as possible would allow your team to offer innovative ideas to correct issues. In other words, Industry 4.0 technology affords you the opportunity to drive insights across multiple business objectives.


Start tracking the data, derive insights from the information, and then apply your learnings to the production process. It all comes down to framing products that manufacturers can use to adopt this process. This is the connection that the manufacturing sector is looking for: uniting processes and outcomes.


Is Machine Health Monitoring the Enabler of Industry 4.0?

Of all the technologies that can enable Industry 4.0, machine health monitoring software is the foundation. Machine health monitoring enables predictive maintenance by leveraging AI insights to alert manufacturers to not only when machines will break down, but also what can be done to minimize mechanical degradation. In fact, predictive maintenance software has the potential to define the outcomes needed for true Industry 4.0.


The data and insights derived from predictive maintenance platforms have improved cost and production predictions. Teams can still commence with routine maintenance, but they can also perform preemptive repairs, resulting in more consistent uptime and longer equipment life. Better-running machines use less energy and produce less waste, moving manufacturers closer to their ideal environmental outcomes.


These preventive maintenance platforms have also led to greater collaboration between operation and maintenance. Regular conversations are taking place around machine health and are being used to inform decisions, improve operations, and instill new levels of expertise on the manufacturing floor. Eliminating the wasteful routine of preventive maintenance creates more time to train workers on new capabilities.


More importantly, machine health monitoring insights provide leadership teams with a better idea of where to focus their attention when planning more innovative manufacturing initiatives — many of which can address problems beyond routine maintenance. Machine reliability is no longer a question, reducing downtime and opening up opportunities to enact process changes that can improve quality, yield, and efficiency.


It only stands to reason that more insights would lead to greater capabilities. Employees have the information necessary to solve problems by looking at multiple solutions that can improve the bottom line and minimize the environmental impact of operations.


The answer lies in proving Industry 4.0 technology and adopting the necessary methodologies to apply the insights to existing processes. Enhanced productivity and efficiency are one thing, but the real potential that these technologies hold is in establishing a next-level communication network within your company — such as a cloud-based system that gives everyone access to the same insights — which could prove to be a driver of a fully realized Industry 4.0 and onward toward the next revolution.

Artem Kroupenev is the VP of strategy at Augury, where he oversees product, market, innovation, and ecosystem strategy. He has over a decade of experience driving the adoption of disruptive technologies and has previously co-founded companies in the U.S., Israel, and West Africa.


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