Artificial intelligence (AI) has demonstrated its limitless possibilities, use cases, and potential to help maximize efficiency in many industries and areas.
The adoption of AI in the logistics sector was a bit slower than in other sectors, however, it is rapidly gaining momentum.
In logistics, AI is revolutionizing the way warehouses and distribution centers operate, allowing companies to improve efficiency, reduce costs, and increase profits. In this article, we provide the high-impact AI use cases in warehousing today.
1. Inventory management using drones
AI can greatly assist with stock counting by drones. Drones equipped with cameras and image recognition technology can quickly and accurately scan barcodes on items within a warehouse which allows one to identify and register inventory items with a high degree of accuracy.
Additionally, the drones can also be programmed to detect and report any discrepancies or missing items within the warehouse by comparing the scanned barcodes with the inventory database. This feature can provide real-time inventory data and help to identify any potential issues with inventory management.
2. Predictive maintenance
AI can be used to predict when equipment, such as conveyor belts, material handling equipment, forklift, HVAC systems, and sensors, will need maintenance, reducing downtime and improving efficiency. By analyzing data from equipment, AI can foresee when maintenance will be needed, allowing managers to schedule maintenance before a failure occurs.
3. Quality control
AI can be used to inspect goods for defects using AI-powered visual inspections, ensuring that only high-quality products are shipped to customers. By using machine learning AI algorithms analyze images of goods, allowing warehouse operators to take the damaged goods out of the order fulfillment flow, reducing the risk of customer complaints or returns. AI is like the ultimate quality control inspector in the warehouse, never gets tired and never makes a mistake.
4. Real-time tracking
AI-powered systems can be used to track the location and status of goods in real-time, providing visibility and improving supply chain efficiency.
The systems can use technologies such as radio frequency ID (RFID) tags, GPS, and sensors to track the movement of goods throughout the supply chain. The data collected from these devices can be analyzed in real-time using AI algorithms to provide visibility into inventory levels, shipping schedules, and delivery times. This information can be used to reduce transportation costs and improve delivery times.
5. Packing
Packing is a labor-intensive task that is essential to the operation of a warehouse. With its ability to analyze vast amounts of data and identify patterns, AI-powered software, such as cartonization software, can be used to assist packing operations to pack items in according to your carrier rates, taking advantage of the counter-intuitive packaging configurations. By doing so you can increase efficiency, reduce errors and handling time, and slash shipping costs by up to 40%.
Packing items in a box can be counterintuitive because it involves balancing multiple factors such as the size and shape of the items, their weight, and their fragility. Balancing these factors can be difficult and time-consuming, and it can be easy to overlook important details that can affect the overall cost of packaging.
AI, however, uses data to create a 3D model of the box and the items, and then the algorithm can use this model to determine the most efficient and cost-effective way to pack the items.
6. Invoice control
One of the key benefits of using AI in invoice control is that it can be paired with a dimensioning system, running on machine vision algorithms, to automate the invoice process. By analyzing data on invoice information, AI algorithms can automatically match invoices to purchase orders, verify prices and quantities, and identify any discrepancies. This can help to reduce the time and effort required to process invoices and ensure that payments are made on time.
Another benefit of using AI with a dimensioning system in invoice control is that it can help to improve the accuracy of master data. By analyzing SKU or pallet dimensions, AI-powered software can identify the size and weight of packages and notify on missing information, incorrect dimensional data, or incorrect shipping costs ensuring that invoices are accurate.
7. Pick path optimization
AI can be used to optimize routes outside of the warehouse and picking paths within a warehouse, reducing travel time, and increasing efficiency. By analyzing data from a warehouse, AI can help managers make more informed decisions about how to route goods and find the fastest way to navigate the warehouse in order to pick products quickly, accurately, and efficiently.
8. Capacity planning
AI can help with capacity planning for the workforce and vehicles in logistics by using historical data and machine learning algorithms to predict resource requirements. This includes forecasting the number of orders that will need to be fulfilled, the number of employees or vehicles required to meet that demand, and identifying any potential bottlenecks in the system.
One of AI’s capacity planning use cases is shift scheduling. By analyzing past data on employee availability and workload, AI models can generate optimized schedules that ensure an adequate number of employees are available to meet demand.
For vehicle capacity planning, AI can be used to foresee the number of orders that will need to be fulfilled and the number of vehicles and type of vehicles (based on loading meter availability, different weight capacity, cooled, non-cooled) required to meet that demand.
9. Demand planning
AI is the magic wand for warehouse demand planning.
The advantage of AI is that it takes historical and current data to predict the demand for products. By analyzing past sales data and identifying patterns, AI-powered software can predict how much of a certain product will be needed in the future.
Additionally, AI can also help to identify and predict potential demand fluctuations caused by external factors such as holidays and promotional events and make more informed decisions about how much inventory to keep on hand, reducing the risk of stockouts or overstocking.
10. Slotting
Warehouse slotting lot of the time can be seen as a never-ending puzzle game, but the solution can be less overwhelming and easier than you think. Enter AI.
Warehouse slotting is a complex task that requires a delicate balance of efficiency and layout. AI can simulate different warehouse configurations to determine the best layout for a given set of products. It considers historical data on product movement, to identify patterns that can be used to optimize product placement. This can include factors such as product size, weight, turnover rate, SKU velocity, and seasonality to increase distribution centers' pick density and overall order fulfillment productivity.
AI can also use self-learning techniques to improve warehouse slotting by analyzing data on item placement, usage, and demand patterns. One example of this is using AI to detect the correlation between items. For example, when a keyboard is ordered, it is statistically likely that a computer mouse will also be ordered. By using AI algorithms to detect this correlation, the system can group items that are frequently ordered together, such as keyboard and mouse, and place them in close proximity to each other within the warehouse.
Conclusions
While it's true that AI is a rapidly evolving field and some of the more advanced use cases may not be within reach for most companies such as advanced robotics or automated self-warehouse slotting, there are many solutions that can be implemented quickly and easily to provide real benefits for warehouse operations.
Therefore, companies should not be discouraged by the futuristic and unattainable use cases of AI in warehousing operations, but instead, focus on identifying and implementing solutions that can provide real benefits today.
AI can play a vital role in improving warehouse operations, and companies that take advantage of this technology will be better positioned to stay competitive in the future.
At Optioryx, we utilize AI in our operations to decrease transportation expenses and aid in reaching your sustainability goals. If you're curious about our approach, we would be happy to get in touch with you and discuss more!