It is a gross understatement to recognize that data consumption is exploding. Some analysts have shown data consumption going from 74 zettabytes in 2021 going to an estimated 149 zettabytes in 2024. It’s not all Netflix streams and TikTok videos either. Considering how much product is consumed by the global population, there are several metric tons of data being generated by the supply chain as well; machine automation makes sure of it.
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.
The Value IIoT Data Brings To Manufacturing Decision Making
The rise of the industrial internet of things (IIoT) hasn’t done manufacturers any favors. 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.
Supply chain inefficiencies cost businesses $800 billion according to the consulting group Kearney. 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 improve performance and reduce 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 anywhere in the world, 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 same vehicles tracked by telematics also probably include sensors that track temperature, CO2 levels, humidity, and more — all critical factors in avoiding spoiled product and recalls, and the damaged reputation that comes along with them.
Track The Untrackable
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 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.