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What Role Does AI Play In Warehouse Management?

Posted by Alanna Friedberg on Nov 7, 2023 10:00:00 AM

ai warehouse management

Today’s fast-paced business landscape makes efficient warehouse management more critical than ever. Companies looking to remain competitive can’t afford to get bogged down in traditional manual processes. They’re often error-prone and slow, leading to a lot of wasted time, money, and resources.  

Leveraging the power of artificial intelligence (AI) in warehouse management transforms operations. It helps businesses optimize their processes, enhance productivity, and boost efficiency. Let’s look at other ways using AI in warehouse management gives companies an edge. 


1. Inventory Management

Software like Dynamics 365 has AI capabilities that use advanced algorithms to gain real-time insights into current inventory levels. That helps warehouses maintain optimal stock levels, preventing too much or insufficient stock. AI can also analyze historical sales and seasonal trends data to provide more accurate demand forecasts. That allows warehouses to plan inventory levels more effectively.

Another AI capability businesses can leverage is automating stock maintenance. Companies can keep carrying costs low while always having enough inventory to meet customer demand. AI can generate purchase orders or restocking requests when items get low to prevent stockouts.

Other inventory management areas where companies can benefit from AI for warehouse management include:

  • Batch and lot tracking — Businesses can use AI to track the expiration dates and lot numbers of perishable or serialized goods. That ensures that older goods ship first, which reduces waste and the risk of sending customers expired items.

  • Order accuracy — Improve accuracy with AI by using the technology to match order requests with picked inventory. That reduces the potential of customers getting the wrong product or number of items shipped.

  • Supplier performance tracking — Use AI to review information about supplier performance, like lead times and delivery accuracy. Businesses can use the data to make decisions about current supplier relationships.

2. Demand Forecasting

AI uses data collected from sales data like order history and seasonality to find patterns that humans might not detect. Machine learning (ML) techniques, including linear regression and neural networks, make that possible. Once the models identify recurring trends, they can make more accurate forecasts for future demand.

Another benefit to using AI for warehouse management is the ability to look at multiple factors simultaneously when making forecasts, including:

  • Weather data

  • Marketing campaigns

  • Social media sentiment

In addition, AI can automatically update demand forecasts as systems receive new information. That type of responsiveness ensures accuracy in forecasts when unexpected events occur, or companies launch new promotions.

3. Order Picking Optimization

AI helps improve routes by looking at the layout of a warehouse, including product location and order-picking tasks. It uses the information collected to map out the most efficient picking routes. That minimizes how far workers must travel, boosting productivity, allowing for quicker order fulfillment, and cutting labor costs.

Another benefit AI provides to warehouses is constantly looking at product demand and adjusting where items get placed. Items picked more frequently get placed in a more easily accessible location, keeping order pickers from traveling a long way to find things on shelves.     

Other ways that AI makes order picking easier for workers is by

  • Identifying orders with overlapping items and grouping them for batch picking

  • Placing orders in waves based on factors like priority, order size, and location

  • Guiding pick-to-light and put-to-light order pickers to a location using visual cues

4. Predictive Maintenance

Using AI-powered sensors and IoT devices allows warehouses to continuously monitor the condition and performance of warehouse equipment. They can detect issues in conveyor belts, forklifts, and automated sorting systems. Businesses can also leverage predictive models to determine when a piece of machinery might fail. The models use historical maintenance records, environmental factors, and equipment performance to decide when to repair a piece of machinery.

AI uses equipment performance data to determine failure patterns. That helps AI provide early warnings to company owners and forecasts when equipment breakdowns might occur. In addition to predicting equipment failures, AI provides recommendations on how to prevent them from occurring. That way, businesses can schedule maintenance actions that save them money.

5. Quality Control

Company data engineers can train AI algorithms to locate defects like dents, scratches, discolorations, and misalignments. After finding a defect, the system can flag an item to inspect it further and remove it from the product line if necessary. AI can assign quality grades based on a product’s condition, which helps warehouses decide how to handle an item, including reworking it or discarding the product entirely.

Operators and quality control personnel can receive real-time feedback from AI about defects. That allows them to take corrective action before producing more defective products. AI models can adapt to figure out how to distinguish harmless irregularities from genuine defects, reducing the number of false alarms generated, which saves time and resources. The precision at which AI examines products makes it more accurate, lowering the risk of human error.

6. Warehouse Layout Optimization

AI can generate simulation models that let companies test warehouse layout configurations virtually. They show how changing a layout in specific ways affects key performance indicators (KPIs) like labor efficiency and storage capacity.

AI looks at demand fluctuations and uses that information to adjust product placement. It also runs algorithms to determine where to place products based on weight, size, demand, and proximity to similar items, lowering the need for excessive replenishment.  

Another way AI makes warehouse layouts more efficient is by optimizing picking paths to lower travel time for human workers and maximize order fulfillment speed. In addition, companies can use AI to look at how well different warehouse layout designs scale to help accommodate future growth and product volume changes.

Optimize Your Warehouse Operations With IES

Internet eBusiness Solutions (IES) helps organizations modernize their warehouse operations by assisting them to find technology solutions that fit their work environment. Learn more about how we can help by contacting an IES representative.

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