Skip to main content

Application of AI in Logistics – Transforming the industry to bridge Supply Chain gaps

featured image
Posted on Dec 16, 2020
by Dev Kumbhare ( Sr. Manager Business Development)

Application of AI in Logistics – Transforming the industry to bridge Supply Chain gaps

COVID-19 had adversely affected the lives of common people and the logistics industry is hit hard owing to the lockdowns and restrictions on easy movement of goods. Organizations throughout the globe are evaluating the potential of Artificial Intelligence (AI) in logistics and determining how it can be best applied to transform the industry to bridge the gaps in their supply chains.

There are pioneers like Amazon who have been using AI since 2018 ‘to push out one-hour deliveries’, reference article and with its Prime Now service, which delivers household basics within hours, the company uses artificial intelligence to make decisions and perform tasks that typically require human intelligence. There is still a lot of scope and opportunities as AI will play a significant role to save time, reduce costs, increase productivity and accuracy with cognitive automation. Here are a few ways how AI is transforming the logistics industry and making it easy to do business in these challenging times -

  1. AI is profitable for fleet management- Due to IoT and AI, self-driving vehicles bring changes to the supply chain and help reduce expenses in logistics. The capabilities of AI are seriously ramping up company efficiencies in the areas of predicting demand and planning network in an optimized manner. Unmanned, remote-controlled ships are becoming more of a reality. Especially with the health threats of 2020, using robots to man the supply chain entirely makes sense to many business leaders.
  2. AI for delivery route optimization- In real time, data from a variety of sources including information pertaining to shipment, traffic patterns, GPS data, and weather can be used for route optimization, which can significantly impact fuel, personnel, and other overhead costs.
  3. Predictive Analytics ensuring On-time and In-Full Delivery- Real-time predictive logistics analytics ensure that fleets arrive on time, goods are received and moved on time so that shipments are delivered to customers when they want it. Sensor-enabled assets or IoT devices embedded in trucks, trains or ships feed data like engine performance and speed and send it to the carriers who can model and predict the estimated arrival times and engine failures. For example, telematics data captured from a vehicle can reveal its speed, position, condition and time left to reach the destination.
  4. More robots in Warehouse environment- With social distancing norms in place, organizations are limiting the number of workers in a warehouse. The supply chain is starting to make greater use of robotics in the warehouse environment. Using AI, robots can track and locate the inventory. The robots can then move the inventory through the warehouse in order to make the process more efficient for other workers. These machines work through deep learning algorithms that can help them make autonomous decisions related to their duties within the warehouse. With the assistance of robots, other workers now have more time to do higher-value tasks because the time-consuming duties they usually had to perform are now automated.
  5. Pickup optimization- AI together with IoT can help optimizing the pickup of orders. Trucks are selected for pickup based on the type of load to be carried. AI learns historical patterns and allows carriers to make decisions precisely. Based on types of goods to be transferred, an AI-based model predicts the right truck for picking up goods.

To conclude, rapid technological development in the fields of Big data, algorithmic development, connectivity, cloud computing and processing power have made the performance, accessibility, and costs of AI more favourable than ever before. While business leaders scramble to bridge the gaps in their supply chains laid bare by COVID-19, AI has stepped in as a potential solution for many of these issues. Although, adopting AI, specifically robots, into the workplace could lead to more layoffs, it’s up to business leaders to assess whether the human costs of adopting AI into their supply chain is worth it.

Category: Data Analytics, RPA & AI

Share :