It’s no secret that manufacturers have been aggressively pursuing digital transformation to compete and win in the marketplace. In 2018, manufacturers will ramp up this transformation to embrace new technologies that have the potential to change the supply chain landscape.
One area poised to get “smarter” is the industrial Internet of Things (IoT), as smart manufacturing will drive manufacturers to new heights. The IoT has made it possible for manufacturers to better monitor, collect and analyze data, and many manufacturers have introduced smart manufacturing concepts and technologies to a plant or even a single production zone. Most manufacturers, however, have not yet fully scaled smart manufacturing technologies globally.
Let’s take a look at the ways that the IoT can streamline the entire supply chain—from the warehouse to the final destination.
Shipping in 2018
In 2018, companies will augment their ability to understand the condition of a product as it’s in-transit, instead of having to rely on testing upon arrival. This level of transparency will enable companies to verify product condition during the entire trip from beginning to end.
Sensors can be placed in several sites, including attached to the container or even the product itself, which allows supply chain managers to monitor several sites at once in real-time. For example, when shipping produce, it is essential to keep the product at a certain temperature throughout the supply chain, so by installing sensors on the container of fruit or vegetables, both the seller and buyer can ensure the load maintains a proper temperature while in transit. Compared to the cost of replacing spoiled produce, the cost of a sensor can be relatively inexpensive.
Data in Transit
With all this information streaming from products during transit, who can access the data? In the instance of produce, it should be both the shipper and the receiver. This two-party visibility means that both the shipper and receiver can check the data at the same time, keeping both parties accountable; there is very little room for any discrepancies when the data is synced, providing another level of confidence throughout the supply chain.
Beyond temperature, other variables that supply chain managers should track include vibration and impact while en route as well as the location at any given time. Today’s data analytics platforms are smart enough to only perform data collection actions as needed (i.e., when triggered by a pre-set rule or regulation), so instead of providing massive amounts of data that are difficult to sort through and make sense of, an intelligent data platform can send an alert only when a problem is identified, lowering data transmission costs. This setup also removes any doubt regarding tampering with monitoring and also ensures communication can continue in areas where there aren’t always stable networks.
Another area where we are seeing the connected IoT positively impact logistics is telematics. Telematics provide decision-makers the ability to more accurately calculate the estimated time of arrival with a high degree of certainty. These calculations can synchronize multiple assets and multiple pieces of supply chain function more effectively.
Along the Rail
In the traditional supply chain, a truck brings the product to the train, the train carries it a distance, and then a truck picks it up to deliver the last mile. Even today, rail is a large component of our national logistics infrastructure because it’s far more fuel-efficient and therefore cost-effective for long-distance shipping. When using the rail to deliver products, however, there is a greater variance in arrival times, which can cause ripple effects throughout the supply chain.
However, through the IoT, companies can automate tracking and ensure synchronization of trucks and a timely arrival of shipped goods by tracking train shipments through telematics. This allows trucking companies to plan more strategically, reducing downtime and improving efficiencies.
The Last Mile
Although the entire supply chain is important to track to ensure a timely arrival, the last mile is essential. Estimated time of arrival (ETA) synchronization can provide great certainty for arrival times. This helps trucking companies place the right trucks in the right areas at the right times to avoid back-ups in the loading areas and ensures that other resources like fuel and hourly employee time are not wasted. The system will update arrival times and adapt to changes in real-time, providing instructions for how the team at the trucking company should proceed accordingly.
The process of arrival starts with clearing the shipment through security, scheduling dock door placement with certainty, and then optimizing door opening and arrival times based on accurate arrival data. This sequence, when optimized with sensors on the containers, helps companies turn their assets more rapidly. Additionally, if a backup is occurring at the warehouse, the system can notify drivers of when they should arrive—delaying them if necessary—instead of adding to the chaos on-site.
At the warehouse level, the IoT will allow for automated vehicles to assist human workers in offloading and moving the products throughout the facility safely and efficiently. This human-robot collaboration is already taking place: leading companies now understand the value of automating certain dirty, dangerous and repetitive jobs. As IoT systems become more sophisticated, we can expect to see more robots working with people to move items along the supply chain.
Across the logistics landscape, enterprises will derive very clear ROI as they continue to experiment with and develop best practices for the industrial Internet of Things. By freeing up manual resources, ensuring transparency between buyer and seller, and ensuring accurate delivery timing throughout, the IoT will help today’s most innovative companies compete in 2018.
Sean Riley is global manufacturing and supply chain solutions director at Software AG, a solution provider that enables enterprises to integrate, connect and manage IoT components as well as analyze data and predict future events based on artificial intelligence.