Data consumption isn’t just growing—it’s exploding at a rate that boggles the mind. Analysts predict that global data consumption could catapult from 74 zettabytes in 2021 to a staggering 149 zettabytes in 2024. While it’s tempting to chalk this up to our Netflix binges and endless TikTok scrolling, that’s merely scratching the surface. Behind the scenes, entire ecosystems of machines and automated processes are churning out metric tons of data, especially in industries like manufacturing, supply chain, and logistics.
But with the arrival of Industry 4.0 and the proliferation of smart manufacturing, our galaxies of data are becoming boundless universe. Unfortunately, most manufacturers are plagued by a shortage or real data as most equipment is either analog or legacy while many processes are still manual resulting is 50-75% blind spots.
As Industry 4.0 barrels forward, ushering in smart factories and advanced automation, the data we’re generating has ballooned into something that resembles an infinite universe. Yet, even in this ocean of information, a perplexing problem persists: too many manufacturers are grappling with a dearth of meaningful, actionable data. Much of their equipment languishes in outdated or completely analog states, while many operational processes remain shackled to manual methods. This translates to massive blind spots—anywhere from 50-75% of their operations lurk in the shadows, invisible in real-time.
The Value IIoT Data Brings To Manufacturing Decision-Making
The rise of the industrial Internet of Things (IIoT) hasn’t favored manufacturers. About 31 billion IoT devices floating around the world today are each pumping out more than their fair share of data. And why? Because margins are tighter, turn-around is more urgent, and competition is fiercer than ever. Data transparency at every level of the supply chain is necessary for contemporary logistics and production decisions as well as ensuring AI initiatives are successful.
According to the consulting group Kearney, supply chain inefficiencies cost businesses $800 billion. Plant and supply chain managers need greater operational visibility and access to data to remove friction and wasted man-hours. IIoT sensors placed on tools and parts create operational visibility and insights with a Digital Twin that improves performance and reduces downtime due to unscheduled maintenance or replacements. Alerts of impending mechanical failures can even preempt lost batches of materials due to these unforeseen events.
Digital asset tracking provides pinpoint location data on assets worldwide, creating greater accountability, collaboration, and a more customer-centric business model. Shelf sensors can detect low stock and trigger a re-order. Connected warehouses use autonomous robotic carts to collect goods for shipping. Damaged goods can be tracked and traced to increase accountability.
Telematics devices are planted on vehicles to track speed, location, acceleration, maintenance, and time on the road. Even time spent idling is captured to curtail emissions. Whole fleets are tracked so businesses, and even consumers, can see where materials and goods are in real-time.
Meanwhile, poor coordination among supply chain partners costs the U.S. food industry $30 billion annually. The food and beverage industry uses predictive maintenance powered by IIoT in the supply chain to improve quality and efficiency to meet regulatory demands without compromising safety. Hazard analysis can be performed in real-time to mitigate potentially catastrophic events. And those vehicles tracked by telematics also probably include sensors that track temperature, CO2 levels, humidity, and more — all critical factors in avoiding spoiled products and recalls and the damaged reputation that comes with them.
Connect the Unconnected
Ultimately, the goal is to connect the unconnected. Continuous and contextualized visibility into blind spots is the cornerstone of any successful digital transformation initiative, whether you’re in manufacturing or any other industry. IIoT solutions, like asset tracking and digital twins, allow companies to optimize operations, reduce costs, and operate more sustainably.
By embracing these technologies, manufacturers can improve yields, enhance profitability, and increase compliance with ever-evolving regulations. Simultaneously, they can minimize waste, decrease maintenance costs, and shrink their energy consumption footprint.
At the end of the day, it’s about using data to work smarter, not harder. Manufacturers who invest in IIoT today will not only gain a competitive edge—they’ll future-proof their operations in a world that’s increasingly driven by data.
If you’re grappling with data issues or trying to figure out where your blind spots lie, let’s have a conversation. Our team of experts is ready to help you navigate the complexities of digital transformation and ensure that your AI initiatives are built on a solid foundation of reliable, actionable data.
Continuous and contextualized visibility into current blind spots is the foundation of every commercial and classified area manufacturing digital transformation initiative. By implementing an IIoT asset tracking and digital twin solution you can improve yield, profitability, and compliance while decreasing waste, maintenance, and energy consumption.
Let’s discuss your data issues and understand where your manufacturing blind spots put you at the most risk. Our experts are ready to answer all of your questions and help you get a handle on your digital transformation processes and AI initiatives.