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Yard operations are not unlike the electricity running all kinds of appliances and gadgets in your house, at least in one respect. Most people think nothing of them when they’re working properly, giving their attention to other matters. But if a tree takes down a power line on your block – or, say, poor gate management leads to a backlog – their importance is suddenly front and center.

While a prolonged power outage across a sizable area can certainly do more widespread harm, a knotted-up yard operation has many upstream and downstream effects on an organization’s supply chain. Raw materials or parts don’t show up at a manufacturing plant, and production is slowed or halted altogether. Orders are shipped out a day late or two, and angry customers can soon become ex-customers.

Some common challenges include a slow gate approval process, mismanaged dock assignments, and poor visibility into yard assets. They all stem from an inability to share real-time data with shipping and receiving, warehouse, and transportation teams.

Innovative AI systems have emerged as a game-changer, solving complex yard operations challenges. They can improve supply chain performance, as the yard is no longer the operations choke point and enemy of efficiency.

The Complexity of Yard Operations

Consider, for example, a busy 250,000-square-foot e-commerce fulfillment center with a throughput of 5,000 outbound orders per day, utilizing its own transportation assets plus third-party carriers. This amount of activity is generating hundreds of truck trips per day, both into and out of the facility.

The yard operations team has to orchestrate the movement of incoming trucks to available bays, dock loading, and unloading, and optimize asset use (trucks, trailers, and chassis). The use of 3P carriers adds a degree of variability to scheduling, capacity, and operations.

All aspects of people, processes, and technology are in play. Data needs to be shared between yard operations, fulfillment, and transportation teams. Managers match production to available trucking capacity (internal and external), determine yard asset needs, and project inbound/outbound volume. This helps ensure a smooth logistics flow, minimizing delays and maintaining order throughput. But fluctuations in demand and transportation capacity can increase complexity yet again.

Without the ability to access real-time data, things can break down quickly. Thanks to manual processing, inbound trucks are held up at the gate, causing delays of up to 20 minutes per vehicle. This affects overall efficiency across operations, pushing up costs.

Without real-time visibility, mismatches in loading dock availability can lead to significant 2-4 hour delays per truck. Drivers are unable to find or access their assigned spots due to existing occupancy or congestion. Dropped trailers can’t be located quickly. This can delay outbound shipments, inbound freight takes longer to process, and inventory management is affected. Costs are increased as yard workers hunt down trucks and trailers; ultimately, customers are disappointed when deliveries arrive late.

AI to the Rescue for Yard Operations

Yard management system (YMS) technology has been in place for about 30 years, and it has proven a huge boost to operational efficiency. It tracks yard assets and inbound and outbound shipments, schedules bay use, and handles gate access control. However, only about 7% of companies were using a YMS as of 2022, and of those in place, most do not have a real-time view of all yard assets and inbound/outbound logistics.

Next-generation yard operations technology leverages the power of artificial intelligence (AI), allowing previously unattainable performance gains to be realized. Load planning and shipment sequencing is enhanced by analytics on vehicle capacity, delivery schedules, and transportation constraints. Improved visibility into transportation schedules, routes, and available capacity drives better synchronization of yard operations with inbound/outbound logistics.

Predictive Analytics Powers Inbound Scheduling

AI systems drive an overall improvement in “yard vision,” analyzing historical data to predict peak times and optimize scheduling and routing. This reduces yard congestion and helps both fulfillment and transportation teams stay on plan.

Automated Dock Assignment

Enhanced visibility into dock availability, inbound flow, and yard traffic means dock assignments can be updated and revised on the fly, based on shipment priorities, product dimensions, and other special requirements.

Real-Time Tracking and Visibility

By accessing data feeds from existing equipment such as security cameras, AI-based yard operations systems provide precise updates on vehicle locations and the status and timing of inbound cargo for inventory purposes.

Practical Considerations for Implementing AI in Yard Operations

Some prerequisites include ensuring the proper digital infrastructure is in place, such as wireless coverage; ensuring accurate, structured, and accessible data for analysis; getting stakeholder buy-in; and training yard staff on system usage. This will help ensure smooth adoption and maximize the capabilities.

AI Opening Up New Vistas of Yard Efficiency

Given the complexity of yard operations for retail, manufacturing, and other industries, legacy systems, and especially manual processes, won’t get the job done in 2024. Not only greater visibility but enhanced agility and efficiency are key success factors.

EAIGLE, a pioneer in AI-driven systems for gate, yard, and loading dock operations, is on the innovative edge of logistics technology. An enhancement rather than a replacement of a traditional YMS, EAIGLE uses advanced optical character recognition and feeds from existing security cameras to automate and optimize yard operations from the gate to the loading dock. To learn how EAIGLE can drive significant improvement to your operational KPIs, request a demo today.