Artificial intelligence (AI) holds the potential to revolutionize various industries, including temperature-controlled warehouses. AI is increasingly being integrated into logistics and supply chain management, offering numerous benefits such as operational optimization, cost reduction, and enhanced customer satisfaction.
Labor Shortages and Worker Efficiency
AI is expected to address labor shortages and improve worker efficiency and safety. Kaushik Sarda, Senior Director of Supply Chain Solutions at Americold, believes AI will enhance on-floor operations by streamlining scheduling activities and optimizing work processes. Computer vision technology, powered by machine learning, is also anticipated to enhance safety measures.
Bobby Kareer, Senior Director of Software Engineering at United States Cold Storage, suggests that software systems offering directed task management can enhance efficiency and reduce labor requirements in warehouses. These systems, ranging from business process automation to more sophisticated models using historical data, can improve throughput while minimizing labor.
Catherine Lambert, Communication, Employer Branding & Government Affairs Strategist at Congebec, highlights that while the AI they are using may not directly address labor shortages, it will enhance worker efficiency. For instance, AI can provide comprehensive data and analysis for maintenance, leading to better energy efficiency and improved facility management. However, the use of AI may require employees with AI-related knowledge.
Inventory Management
AI can significantly improve inventory management by leveraging advanced algorithms to predict future demand and optimize stocking levels. This can lead to more efficient inventory management and reduce the risk of stockouts and overstocking.
Kareer emphasizes that as a third-party logistics provider (3PL), they have insights into customer products, which can help in providing actionable insights to customers for optimizing their order shapes and inventory levels. This can reduce waste and improve operating costs during receiving and shipping processes.
Sarda notes that predictive analysis and demand pattern analysis, along with correlation to external factors like weather and economy, will enhance inventory management. AI can simulate multiple strategy scenarios and their impact on inventory, enabling executives to make better business decisions. At a tactical level, managing inventory within a warehouse will become easier with cycle count programs and dock cameras for identifying over, short, and damaged (OS&D) items. This will lead to a significant reduction in inventory shrinkage.
Smarter Transportation
AI is expected to optimize transportation by improving routing capabilities and predicting on-time arrivals. This will help warehouse operations better plan resources and reduce greenhouse gas emissions by considering shorter trips to closer locations.
Lambert suggests that AI could optimize transportation by analyzing orders for a given customer or offering options for shared load delivery across multiple customers. Improved algorithms and machine learning techniques can suggest more sophisticated options for order fulfillment in a cost-effective manner.
Predictive Maintenance
Combining AI with IoT sensors will enable the analysis of machinery failure points in advance to prevent mechanical failures. This will help in scheduling maintenance activities and managing labor shortages of maintenance experts. AI can also assist in inventory management of spare parts, directly impacting the bottom line.
Lambert highlights that AI helps in managing a fleet of equipment used in facilities more effectively and productively. Optimizing fleet management can reduce maintenance on overused equipment and improve energy efficiency, leading to more effective preventative maintenance of buildings.
ROI and Accessibility
AI is expected to improve warehouse operations by automating tasks, optimizing inventory management, reducing labor costs, improving delivery times, and reducing equipment maintenance costs. With advanced algorithms and automation technologies, AI can analyze data, make predictions, and provide recommendations that help companies make informed decisions.
Sarda emphasizes that AI offers a definite return on investment (ROI) when deployed properly with large training datasets and the right application. From data mining to robotic process automation, AI's payback in all things inside operations, as well as back-end activities, should be very attractive in the coming years. When AI is built into greenfield projects, the chances of success will be higher.
Lambert points out that publicly accessible AI is also accessible to smaller companies. With cloud computing becoming a more accessible service, companies don't have to invest huge amounts of money in infrastructure to get started. Additionally, with an external consultant network available, companies do not have to invest in internal resources.
Pressing Needs and Future Outcomes
Lambert believes that the most pressing need for AI in the warehouse is the optimization of forklift movement to manage time and movement within the warehouse. She also sees AI for production lines as the next big thing, enabling better preparation for production and just-in-time food production.
In the future, Lambert believes the biggest impact of AI on supply chains will be the need to integrate AI into the workflow and to optimize transportation. AI could be used to manage orders and plan transportation more closely, leading to transportation to closer locations and reduced greenhouse gas emissions. Lambert adds that AI should be a top priority for human resource departments. It is a tremendous tool that can be used specifically in HR departments to develop organizational structures, job descriptions, and the like. However, she warns that there is a risk of sharing confidential information, and companies need to remain vigilant and careful with the potential sharing of confidential information.
Sarda believes that the most pressing need for AI is the enhancement of computer vision guiding systems, such as OS&D prevention or productivity of automated guidance vehicles. He also sees AI driving ESG initiatives like carbon-neutral warehouses as the next big thing in temperature-controlled warehouses. The biggest impact of AI on supply chains in the future, according to Sarda, is that it will allow executives to model multiple scenarios to test strategies against real-world challenges. It will help organizations in many ways, from increasing forecast accuracy to inventory management, controlling costs in operations by increasing efficiencies to automating backend functions.
Kareer suggests that the supply chain is largely a set of independently managed links in the chain of custody from the farm to the table. Each link in the chain is trying to optimize its processes, independently leveraging the subset of data it has access to. He believes that if the industry can come together to share data, even greater benefits could be seen from AI.
By leveraging the power of AI, cold storage companies can stay ahead of the competition and provide better experiences for their customers.
