It is undeniable that AI & machine learning is revolutionizing several sectors, particularly supply chain and logistics.
Fremont, CA: Given the recent significant worldwide disruptions brought on by the pandemic, supply chains have witnessed an increased requirement for resilience. The industry has responded by implementing cutting-edge technology like artificial intelligence and machine learning to enhance its operations. AI is used at every stage of the supply chain to improve efficiency, mitigate the consequences of a global labor shortage, and provide smarter and safer ways to deliver goods to customers. AI is utilized in manufacturing, storage, and distribution, among other things.
It is undeniable that AI & machine learning is revolutionizing several sectors, particularly supply chain and logistics. The following scenarios demonstrate how decision-makers might arrive at a more effective and economical method of handling, storing, and transferring items.
Warehouse management
ML aids in warehouse management by expediting the flow of commodities into and out of the warehouse. Warehouse managers may effectively utilize the available warehouse space by using predictive models. Employees, such as product pickers, may work more efficiently and effectively when the warehouse is well-organized, which increases their capacity for order fulfillment. Having the right warehouse space offers other benefits beyond increasing employee productivity and simplifying order fulfillment. Due to warehouses’ greater storage capacity and efficient use of space, supply chain managers are able to purchase goods in bulk. Bulk purchases, which are less expensive, save costs and boost profit margins.
Fleet management, route optimization
To manage the fleet, make data-driven decisions based on information received from traffic, weather, and other external variables. Fleet managers may choose efficient routes to deliver their fleets to their destinations on time with the help of pertinent information and precise data insights. Fleet operators may alter routes in real-time by combining ML with information gathered by IoT devices and sensors onboard fleets. Making route selections based on current weather and road conditions enhances driver and vehicle safety. In addition, an adequately managed fleet will have positive downstream consequences such as improved customer service and overall productivity.
Production planning
On the demand side of planning, AI has proven applications. Companies in the supply chain are increasingly examining how AI might aid in optimizing their supply-side production planning. Most businesses employ planning and scheduling software containing a lot of data. Let’s face it; a person cannot effectively examine such enormous volumes of data. On the other hand, ML can swiftly and instantly assess this data.
