May 17, 2020

How AI can make supply chains more sustainable

Robert Boute
Joren Gijsbrechts
AI
Artificial intelligence
Robert Boute & Joren Gijsbrech...
4 min
Robert Boute, Professor of Operations & Supply Chain Management at Vlerick Business School, and Joren Gijsbrechts, PhD student at the Research Centre for Operations Management at KU Leuven, discuss how AI can enable supply chains to achieve sustainability
Robert Boute, Professor of Operations & Supply Chain Management at Vlerick Business School, and Joren Gijsbrechts, PhD student at the Research Centr...

Robert Boute, Professor of Operations & Supply Chain Management at Vlerick Business School, and Joren Gijsbrechts, PhD student at the Research Centre for Operations Management at KU Leuven, discusses how AI can enable supply chains to achieve sustainability.

The way in which companies organise logistics today is not sustainable. Supply chains are not always the most environmentally friendly and it is impossible for organisations to sustain a balancing act of the best possible speed, flexibility, cost and carbon footprint when it comes to the shipping and delivering of their goods. In an ideal world, organisations would be able to have a sustainable, cost-effective and efficient supply chain for their products – however, this is isn’t always feasible using the current available methods for shipping.

However, new technologies such as Big Data analytics and AI can help companies make a positive change, ensuring their supply chains run as efficiently and sustainably as possible. Utilising AI can have a dramatic effect on supply chains, helping organisations to benefit from the fastest, cheapest and most sustainable routes for shipping, and combining these seamlessly.

So, how can firms implement this? Well, it all focuses around organisations shifting to a sharing economy when it comes to their supply chains. Using AI, data and innovative algorithms can drastically improve the sustainability and efficiency of supply chains by enabling organisations to work together. In fact, there are three very specific areas in which these technologies can applied to create a smart, efficient logistics chain.

Collaborative shipping

Collaborative shipping, otherwise known as sharing shipping, refers to the shared use of shipping and transport methods between organisations. This is something that we have explored at Vlerick Business School and KU Leuven, by developing an algorithm to help organisations better identify opportunities to share their shipping data and collaborate with other transporting firms.

Using GPS data, this algorithm logs the collection and drop-off points of shipping organisations. The system remains aware of the state of the environment at all times, with regards to shipping, stocks, transport methods and the costs. By incorporating the sharing economy aspect into this, organisations can share details of their supply chain with other firms.

For example, if a truck is delivering goods and services to a specific location, by inputting this data into the algorithm, the system is aware of the amount of stock in the truck, where it is travelling to and the costs of this travel. If the truck is partially empty for instance, by using the algorithm organisations which are delivering to the same location or a location en route can share their delivery method, not only cutting costs but reducing pollution too – making their supply much more sustainable. This could also be the case for making effective use of trucks return trips with empty loads too. Using the AI algorithm and the data inputted into this, organisations can identify these empty returning trucks and use them for their own delivery purposes.

SEE ALSO: 

Synchromodality

Not all packages are equally as urgent to distribute. In fact, many have intentionally long delivery times and some packages can actually change in urgency after they have originally been shipped. Using the physical internet, organisations can adapt a synchromodality system, which involves combining a variety of transport methods in a sustainable way and taking into account the urgency of these deliveries, without comprising on the flexibility of the shipping.

Using a real-time data system, the transportation method of a delivery can be adapted whilst a shipment is en route, meaning that throughout its transportation the algorithm can select the most cost-effective and environmentally friendly supply chain in real-time, continuously shifting to the most efficient and sustainable delivery method possible. 

Deep reinforcement learning

Deep reinforcement learning is a specific element of machine learning and involves training an algorithm to make the best possible decisions. This is done through a trial and error process, where the robot is guided to the correct decision through positive feedback on its actions. By positively rewarding the robot, it will learn to narrow down its random actions, and only repeat those that have a good outcome for the organisation. 

Organisations using this deep reinforcement learning are able to train AI to make complex and positive supply chain decisions which involve a number of variables. In doing so, AI could determine the exact number of products to ship, when to ship it these and which mode of transport is best to use. This could also be used to train smart algorithms to support companies to collaboratively ship, use synchromodality and replenish an organisation’s inventory smartly, linking all of the aspects of AI together to create the most sustainable and efficient supply chain possible for the organisation.

Not only does integrating AI and new technologies to supply chains benefit the organisation, but from an environmental standpoint utilising these technologies can reduce pollution and the organisation’s carbon footprint, creating a much more sustainable supply chain and enabling a company to make a positive impact on many of the world’s pressing environmental issues.

Share article

Jul 31, 2021

RAIN RFID, IoT and AI are key to a proactive supply chain

Supplychain
Technology
RFID
IoT
Jill West, Vice President Stra...
4 min
RAIN RFID, IoT and AI are key to shifting supply chain’s technology adoption from reactive to proactive in the post-pandemic era

Across supply chains around the world, we have seen leading companies rely heavily on technologies like AI and IoT during the pandemic. These digital solutions have enabled businesses to accurately capture and ultimately use their own first-party data to drive efficiencies and protect increasingly fragile bottom lines.

However, what is less commonly known is the increasing role of RAIN RFID technology in supporting IoT solutions. By using RAIN RFID to capture item data and then feed that data into AI systems, businesses can identify inefficiencies within the supply chain and make informed decisions.

What is RAIN RFID?

In short, RAIN RFID is a powerful IoT technology that enables itemised data collection. By applying small, battery-free tags to items, organisations can identify, locate, and authenticate each of those items, scanning up to thousands of items simultaneously with a variety of devices, including hand-held, fixed and wearable readers.

RAIN RFID solutions dramatically improve the operational capabilities of an organisation by ensuring they have exactly the right items, in the right quantities, at the right locations, at the right time. During the pandemic, RAIN RFID solutions have been key to limiting disruptions in retail and manufacturing supply chains, most notably by increasing inventory and asset visibility and improving the management and flow of goods. 

Three ways RAIN RFID helps solve supply chain concerns

RAIN RFID is used to streamline processes, maintain real-time inventory, increase productivity, and help manage labour shortages. We see three key ways RAIN RFID helps solve supply chain concerns:

  1. Automate shipment verification: Today, significant labour is required for multiple, manual barcode scans during the shipment process. RAIN RFID tags can be read automatically without a direct line of sight, erasing the need for workers to pause, locate a barcode, and scan it. By using RAIN RFID, supply chain leaders can automate their shipment verification process and improve warehouse efficiencies by up to 25%.
  2. Deliver real-time visibility: Retail Systems Research says that 76% of supply chain survey respondents reported that real-time inventory visibility was their leading focus for improving performance. When supply chain managers lack information about the status of assets and shipments moving into and out of warehouses, confidence and productivity suffer. By using RAIN RFID, supply chain leaders gain real-time visibility into an item’s identity, usage, and location. With this information, they can quickly find inventory and assets, and reduce the cost of asset investments. 
  3. Improve order accuracy: Today, companies rely on redundant manual checks to verify that the right cartons are loaded onto the correct pallets. By using RAIN RFID, supply chain leaders can automate pallet build verification to streamline the process and increase order accuracy. In fact, a recent study by Auburn University found that RAIN RFID can help an organisation achieve up to 100% order accuracy, eliminating claims costs and unhappy customers.  

RAIN RFID can increase value of AI-powered analytics

In today’s AI-driven, rapid decision-making business environment, RAIN RFID is uniquely capable of making systems more effective. This is because it provides item identifiers for tracking and locating billions of items, from clothing to food, pharmaceuticals, tools, packages, pallets, and more.

It also works without line-of-sight, providing visibility into places and processes not previously available. The data provided by a RAIN RFID system can give AI-powered solutions the ability to see individual items throughout the supply chain, understand how the entire supply chain is functioning and identify which areas can be improved. 

As companies accelerate digital transformation, we expect to see a rise in interconnected data as investments into new technologies and IoT surge. But as the volume of real-time and accurate data about the movement of goods rises, so too do the demands on operations teams to make sound business decisions quickly and with confidence, often using AI-powered systems that thrive on improved data to make better decisions. 

As an example, over the past several years, Delta Airlines transformed its customer experience by investing in technology including real-time RAIN RFID bag tracking and automatic check-in via the Fly Delta mobile app. Delta is now leveraging this set of investments in their implementation of an AI-driven platform that analyses millions of operational data points, from luggage movement to aircraft positions to flight crew restrictions to airport conditions. This system simulates operating challenges and creates hypothetical scenarios that help Delta’s professionals make critical operational decisions that improve the overall customer experience.  

Looking forward

The need to drive digital transformation rapidly during the pandemic has made supply chain and logistics professionals increasingly tech savvy. As we prepare for a post-pandemic era, companies’ increased know-how and awareness of solutions like RAIN RFID, IoT and AI will play a key role in evolving the industry’s approach to solving supply chain issues from reactive to proactive, setting them up for future success.

Share article