[REPORT]
Artificial Intelligence in Logistics: 6 applications
The digital revolution of the Supply Chain is the most important change in the industry and remains a major challenge for many transport players. In a highly competitive market, an efficient and flexible Supply Chain is a major asset. Companies are therefore looking for tools to optimize their processes and help them make decisions to improve their operational efficiency, customer satisfaction and reduce economic and environmental costs. New technologies, and in particular Artificial Intelligence, play a key role in this ambitious challenge. According to Gartner, by 2024, 50% of Supply Chain companies will invest in technologies supporting Artificial Intelligence (AI) and advanced analytics capabilities [1].
What is the difference between RPA and AI?
First of all, it is important to distinguish RPA (Robotic Process Automation) from AI (Artificial Intelligence).
RPA is a technology that enables the automation of some mechanical and repetitive tasks based on given instructions. Artificial Intelligence relies on technologies such as operational research for process optimization (tours, inventory, etc.) and reinforcement learning for the autonomous movement of vehicles (robots, cars, etc.).
AI is capable of analyzing and linking data in an attempt to mimic the way a human thinks and acts. Unlike RPA, AI is able to improve its own predictions and performance by using Machine Learning and Deep Learning techniques.
Artificial Intelligence can thus :
- Improve existing RPA by automating tasks that were not previously automated,
- Assist humans in their decision making.
How can Artificial Intelligence help logistics and what are the advantages?
84% of Supply Chain Managers consider the lack of visibility on their Supply Chain as their main concern [2]. They would like to have a clear overview of the entire Supply Chain so they can act in case of unexpected events.
The Supply Chain includes different stages that can be complex to manage, including the last mile. The use of Artificial Intelligence technology can optimize each of these steps.
Inventory automation
There can be many different components in a warehouse and it is easy to lose track of them. Knowing the exact location of each item allows teams to work faster and more efficiently. The accuracy of an inventory is very limited in time, an inventory is already inaccurate the next day. Therefore, it is necessary to automate this task to have an updated overview every day.
L’Oréal, for example, has implemented Hardis Group’s Eyesee drone system:
How?
A drone fitted with an on-board camera, passes by the shelves of each section to carry out the inventories. Thanks to AI video processing, the drone can read barcodes and recognize empty spaces.
What are the benefits?
- Lower error rate
- Less expensive
- Faster
- Greater safety for employees who no longer work at heights
- No need to stop the warehouse for days
- Can be done every night or weekend
Smart inventory management
Inventory management is a complex issue and managing the right stock in the right place at the right time can be a real headache. Artificial Intelligence can assist humans in the implementation of a better inventory management.
How?
From historical data, orders and current stocks, an AI predicts the needs for the whole network and recommends optimized decisions (purchase, transfer, etc.). It will identify which products are selling the fastest or slowest and create a more accurate inventory accordingly. This allows for inventory adjustments to avoid shortages and limit overstocks. AI will also be able to predict consumer buying intentions based on different elements such as weather, events, time of day, etc. This is very useful to anticipate the right stocks that will be available at the right time and thus reduce delivery time to the customer who will be happier.
What are the benefits?
- Better purchasing performance
- Better stock availability
- Lower transportation costs
- Lower inventory value
Engie turned to Vekia to optimize its stocks:
Engie performs about 14 000 interventions per day (maintenance, heating/air conditioning repair…) and has 1 million references on its IT system. To provide a perfect service, technicians should always have the appropriate spare part in their inventory. To achieve this goal, Engie asked Vekia to optimize the stocks managed by the 230 agencies and to automate the orders from the warehouses. The algorithm, applying Machine Learning techniques, gets the data from the agencies, calculates the remaining stocks and makes order proposals for each management point.
Order picking automation
To facilitate the work of order pickers and even to completely automate it, Artificial Intelligence allows huge time savings and productivity improvements.
How?
Based on the orders, a swarm of robots moves in the racks to collect the goods and forward them to the operator. The AI guides the robots and optimizes their movements in the warehouse.
What are the benefits?
- Improved picking productivity
- Improved picking time
- Improved OPEX picking cost
- Lower error rate
- Improved working conditions for operators
Cdiscount uses Exotec’s solution for order picking:
Exotec has designed a robotic system to optimize order picking. Thanks to its fleets of hundreds of robots, that can move in three directions, Exotec not only helps to reorganize warehouses, but also to optimize logistics flows. These robots can move on the ground but also at height by climbing on storage racks, which has allowed Cdiscount to increase its storage capacity fivefold. Productivity is three to four times greater than if done by manually.
Parcel sorting automation
Parcel flows, especially with the rise of e-commerce, are increasing and require optimized structures. AI is once again a valuable tool in the automation of this step of the Supply Chain.
How?
Based on a predefined sorting system, the robots automatically forward the packages to their destination area. The robots move on their own, quickly. Optical recognition allows for quick label scanning to identify products and their characteristics (weight, dimensions, geographic delivery area).
What are the benefits?
- Better sorting productivity
- Lower OPEX cost compared to human sorting
- Lower error rate
- Improved employee efficiency
STO Express uses robots to sort its parcels:
By scanning the package label, STO Express’ robots can move parcels to the right sorting area of the facility. They can process up to 18,000 packages per hour.
Using sorting robots improves efficiency, accuracy and safety during the sorting process and also reduces labor costs by 70%.
Logistics players are increasingly implementing automation and robotization into their processes. AI is involved throughout a product’s cycle: from receiving inventory, dispatch, picking and packing to shipping.
Transportation visibility
Tracking the flow of goods is essential for logistics professionals who are in charge of the proper delivery to the customer. As customers are increasingly demanding, they require more transparency on their product delivery. This visibility is also valuable for logistics operators who can react in case of delays and unforeseen events and proactively inform the customer.
How?
Using data on goods’ location around the world as well as transport conditions (weather, congestion, etc.), AI predicts the arrival of goods at their destination, providing a comprehensive overview.
What are the benefits?
- Better ETA estimation
- Improved proactivity
- Better delay forecasting
Wakeo, a platform specialized in transport visibility:
Wakeo can be interconnected with every IT solution on the market (ERP, TMS, WMS, etc.). The collaborative platform was designed to simplify international transport and improve Supply Chain visibility. To achieve this, the start-up uses Machine Learning and large-scale data processing to anticipate delays and thus make supplies and customer deliveries more reliable. Wakeo uses real-time tracking to anticipate delays, email and SMS alerts to warn different parties, and analytics to accurately track transport performance.
Delivery Route Optimization
The last step of the Supply Chain is the delivery to the end customer, which is the most complex and difficult to manage because of the many unexpected events that can occur. A traffic jam, a car accident, a road closure, a missing customer, specific delivery slots… the constraints can be endless and responding to them manually is not the best way. AI-based route optimization solutions will allow to create efficient routes in real time, taking into account field context, so that delivery drivers can provide a better service quality to customers.
How?
Using delivery point coordinates and different constraints (transit times, traffic conditions, etc.), powerful Operational Research algorithms optimize delivery route planning. This optimization will help anticipate delivery peaks, better distribute and optimize resources to reduce costs, but also to reduce driver stress and comply with their working hours.
AI, by applying Machine Learning techniques, collects the data and improves the performance of the next optimizations. For example, for the transport of parcels, AI can accurately identify delivery times based on the type of customer, the area to be delivered, the floor, the size and weight of the parcel.
What are the benefits?
- Fewer vehicles on the road
- Fewer kilometers traveled
- Lower costs and delivery times
- Better service quality and customer satisfaction
- Lower CO2 emissions
- Better working conditions for teams
Kardinal’s solution was designed to meet these challenges and to help logisticians make the right decisions so they can achieve more efficient tours.
Continuous route optimization solution
Conclusion
Artificial Intelligence is a powerful tool for logistics players as it can be used at any step of the Supply Chain: from creation to product delivery to the end customer. Its purpose is to perform mechanical and repetitive tasks as well as assist workers in their decision making, allowing them to concentrate on tasks with higher added value. Productivity is therefore increased thanks to cooperation between humans and machines. A study by McKinsey underlines that companies that have invested in AI applied to transport and logistics have increased their margins by more than 5% [3].
AI is transforming every industry, especially the logistics industry, where innovations are ongoing and will continue to evolve. Being part of this digital transformation will ensure the viability of your business.
Resources
- [1] Gartner, January 2021 : https://www.gartner.com/smarterwithgartner/gartner-predicts-the-future-of-supply-chain-technology/
- [2] IBM’s eBook, The Future is Here, November 2018
- [3] McKinsey Global Institute, Artificial Intelligence, the next digital frontier?, June 2017 : https://www.mckinsey.com/~/media/mckinsey/industries/advanced electronics/our insights/how artificial intelligence can deliver real value to companies/mgi-artificial-intelligence-discussion-paper.ash