Decision Science Optimization

5 Decision Science Applications in High-Volume Logistics

Richard Schrade
President, Co-Founder

As the rise in eCommerce sales continues to drive growth in warehouse and shipping logistics, those businesses face more pressure. Success depends on being able to consistently increase the efficiency of trailer unloading and loading, fulfillment processes, and package sorts. 

At Automation Intelligence, we have worked with a number of industry leading logistics clients to configure  AI-based decision science tools that enable them to improve efficiency and reduce costs through better orchestration. Our decision science tools listen to your assets and provide outputs that enable siloed systems to operate together at peak efficiency. 

Our tools focus on the inside operations of a facility and communicate with both data systems and human operators. These tools can unlock 15% or more capacity for a logistics facility through better orchestration of existing systems. 

Here are a few common logistics applications for our decision science tools:

1. Inbound trailer sequencing

Almost every operation starts with volume coming into the building. The decision of where, when, and how fast to unload a trailer has downstream effects on the material handling system, AGVs or forklift traffic, and storage/accumulation availability. Our tools provide guidance to inbound yard management systems and operations while considering the capacity of doors, human capital, contents of inbound trailers, downstream capacity, and downstream demands of such volume.

2. Resource allocation

Whether automated or manual, each operation in a logistics facility plays a role in turning inputs into outputs. Our tools allow decision makers to right-size their labor needs by putting the right people at the right place at the right time. To do so, we consider things like demonstrated performance and rates, as well as the capability of all the resources.

3. Order sequencing & assignment

Order fulfillment facilities have commitments to their downstream customers. It's common for orders to have a commitment time to ensure their customers get what they need when they need it. Our tools consider all the steps and resources available to complete orders and yield a sequence which maximizes flow while satisfying commitments.

4. Routing

Logistics facilities often have a complex flow network to get volume through the system. Optimal routing includes considering the capacity of travel pathways and what goes where and when. AGVs for example make use of common traffic aisles to get from A to B. Our tools consider these constraints when orchestrating the system.

5. Scheduling

A critical piece of decision science is the fourth dimension: time. As our tools seek to maximize flow, we consider how long each step will take and what resources may be required. For example, consider a fleet of AGVs responsible for replenishing a multi-level pick module. Our tools will preemptively dispatch AGVs for SKUs which we know will soon be depleted, and do so in such a way that we do not create traffic jams or bottlenecks.

When combined, these tools can maximize efficiency for your logistics business

It's important that all these are done together. Seeking to maximize the throughput in one step in the process may come at the expense of others. Each step should serve to maximize the output of the entire system; not just one area.

Automation Intelligence develops a decision science configuration for each unique client

Each facility and client is different. A first step in adopting decision science is getting a deep understanding of the process and what defines success. Orchestration is the key. Our tools are configured to match our client's specific layout and operations and once configured scale easily across the network. 

If you’re interested in learning more about the applications of decision science for your business, please reach out to us and we’ll schedule a time to talk in more detail.


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