How AI Is Used In Supply Chain Management

By U Cast Studios
August 8, 2022

How AI Is Used In Supply Chain Management
Image Courtesy Of Unite.AI

AI is transforming supply chain management with greater efficiency, visibility, and optimization. There are a number of ways that supply chain organizations can implement AI to experience these benefits, from smart simulations to automated quality control. Adopting AI will be key to evolving the supply chain and adapting to today’s supply chain challenges.

This article was written by Zac Amos and originally published by Unite.AI.

1. Optimization With AI Simulations

AI is great at analyzing data to predict outcomes. Supply chain businesses can use this capability to optimize their operations through AI simulations. The AI can assess a certain operations setup and pinpoint bottlenecks and potential issues.

In a simulation, there is much more flexibility for supply chain businesses to optimize their operations without causing real-world delays in the process. Google launched one such AI-based digital twin tool in 2021, which was designed to help supply chain businesses save money through optimization. These types of tools can be extremely effective for any link in the supply chain.

For instance, a warehouse manager could create a digital twin of his whole warehouse. He could then use an AI logistics simulation on that digital twin to experiment with different optimization strategies. This way, he is able to find the optimal logistics strategy for the warehouse without disrupting real-world operations.

2. Automated Inventory Management

Warehouses are crucial links in the supply chain. If a warehouse is running inefficiently or handling inventory inefficiently, it could cause serious ripple effects throughout the entire supply chain. AI can help warehouses automate their inventory management, saving both time and money.

For example, units could be equipped with IoT tags that keep track of the status of each item. If the items inside each unit are perishable, the IoT tracker will keep track of how close expiration dates are. The IoT tags can send data like this back to an AI hub that manages all of this inventory data. The AI can then alert warehouse managers when inventory units are nearing expiration or when inventory levels go above or below a certain threshold.

3. Supply Chain Cybersecurity

Cybersecurity has never been more important for supply chain organizations. In fact, in 2022, ransomware-as-a-service has emerged as a whole new underground market where hackers can buy ransomware to conduct rapid attacks on businesses. Big businesses aren’t the only members of the supply chain getting hit, either. One incident in 2022 impacted as many as 2000 individual small and medium-sized businesses.

Supply chain management needs effective, agile cybersecurity to stay ahead of these threats at every step in the chain. AI is a highly effective tool for accomplishing this due to its pattern recognition abilities.

For example, a warehouse could use AI to constantly monitor login activity on its servers. If the AI detects any suspicious or unauthorized login attempts, it can alert security personnel and even block the suspicious account.

4. AI Demand Forecasting

AI has a lot to offer manufacturers and retailers, as well. These businesses can use AI data analysis tools to get a precise idea of what supply and demand will look like in future quarters. AI algorithms can analyze numerous data sets, such as sales data and consumer trends, to predict how much of a certain product will be in demand.

Precise demand forecasting allows each link of the supply chain to reduce overall supply strain. If manufacturers know exactly how much of a certain material they will need, they don’t need to overburden raw materials suppliers by ordering excess.

The same goes for retailers who submit their orders to manufacturers. Ultimately, this could help reduce waste in the supply chain, as well.

5. Waste and Error Reduction

AI can be an extremely valuable tool for reducing material waste and improving overall quality control in the supply chain. This is largely due to the incredible capabilities of machine learning, which allows things like computer vision to learn how to automate otherwise complicated processes. Supply chain businesses can combine AI and IoT for rapid, accurate waste and error reduction.

For instance, a manufacturing company might want to automate quality control for their cardboard boxes. An AI-powered camera could be used to scan the boxes as they go through the assembly line, rapidly detecting any imperfections without creating a bottleneck.

Similarly, IoT devices could be used to collect data on how much raw material is being used in the manufacturing process. AI data analysis algorithms could use this data to identify where the most materials are being used and where materials are being wasted the most.

These insights allow businesses to use their raw materials more efficiently and reduce the overall strain on the supply chain.

6. Tracking Supply Chain Sustainability

Sustainability has become a major priority throughout the supply chain over recent years. On one hand, it is good for the environment and for the people who work in and support the supply chain.

Additionally, sustainability initiatives often focus on reducing waste, which is an important part of reducing strain on the supply chain, particularly for raw materials suppliers. AI can help businesses track the sustainability of their supply chains, increasing visibility.

One great example is route optimization using AI logistics algorithms. Businesses can reduce the carbon footprint of their supply chains by identifying the most efficient shipping routes to use, whether on land or sea.

Additionally, AI and IoT devices may even be able to help businesses keep an eye on sustainability among their partners and suppliers. AI algorithms can keep track of where all the components for a finished product come from throughout the supply chain. This would increase visibility and allow businesses to improve awareness of potential sustainability weak spots.

For instance, a supplier might be using harmful dyes in their manufacturing process. If a business is able to stay aware of this thanks to AI, they can choose a more sustainable supplier instead.

Building a Smarter Supply Chain With AI

AI will be instrumental in innovating supply chain processes to build a more efficient, sustainable supply chain in the future. Businesses in every link of the supply chain can implement AI to automate processes, improve their operations, strengthen their security, and make better use of raw materials. With the right tech on hand, any supply chain business can evolve to meet today’s challenges.

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