A.I. has been a growing presence in supply-chain management for years now. However, there are still some challenges to incorporating this technology successfully.
The Five Most Key Takeaways from This Blog Post
- Uses for A.I. in the supply chain go well beyond robotics, as there is a lot of investment in A.I. data analysis that leads to predictions about things on and off the conveyor belts.
- Inventory management can help with a wide variety of tasks in this category. This can help determine how to best optimize space in warehouses, stores, and other places where goods and raw materials find storage.
- Demand forecasting, which predicts how much demand there will be for a certain product, is one of the biggest applications for A.I. However, one of the caveats is that the longer the time frame of the forecast, the more unpredictable events there are in the time frame that could threaten the output’s overall accuracy.
- Predictive maintenance is another growing use for A.I. in manufacturing. This allows manufacturers to get predictions about the best time to do maintenance on a machine. Or, when a repair or replacement may be necessary in the coming future.
- Price-prediction software can help identify what are most likely to be the best days to purchase materials on. This can help shave off unnecessary overhead costs.
The Supply ChA.I.n
We live in a world where consumers wish for products to be made quickly yet cost as little as possible.
As such, the onus is on entities in the supply chains of the world to find ways to meet these goals.
Enter A.I., which can automate much of the actions on the manufacturing floor, so that more humans in the future will be playing the role of maintenance technician and foreman to A.I.
The robotic applications are certainly worth the attention, but many of the data-analysis applications are what are drawing the attention of movers and shakers in the supply chain.
Digital Twins
This right here is an A.I. application that did not get a Key Takeaway bullet in the section supra.
However, it is well worth learning about, because it fulfills the growing hunger among businesses for comprehensive data about the going-ons in an organization.
To get an idea of what a digital twin in the supply chain is, consisder the following example.
A computer models a manufacturing floor so that it creates a digital replica—a digital twin, if you will— of all of the machines on the floor.
The manufacturer installs sensors on the machines to gather data about the performance of each individual unit.
In the computer model, A.I. provides real-time updates to the digital twin, providing tabs on performance dips and spikes and the like.
This can allow for benefits such as the remote assessment of the functioning of a factory floor. Time is saved, and what’s more is that A.I. can quickly identify an issue that in the past would perhaps go unnoticed until a physical inspection. So, money can be saved as well, and productivity maintained at a consistent level.
This desire for comprehensive data is of course a strong driver of business decisions. A comprehensive data-painted portrait of operations helps managers feel that the controllables are under greater control.
Plus, there is a certain soothing, reassuring feeling of seeing a lot of data, isn’t there? The experience gives one the impression of informed decision-making, a safety in information that can inform better guesswork.
Delivering the Goods
Another application worth considering is route-mapping A.I. that can give stronger predictions than ever about potential traffic patterns and weather events.
What that could lead to is faster deliveries for consumers and safer, less time-intensive drives, sea voyages, and flights, for the transporters of goods in the supply chain.
Other Great GO AI Blog Posts
GO AI the blog offers a combination of information about, analysis of, and editorializing on A.I. technologies of interest to business owners, with especial focus on the impact this tech will have on commerce as a whole.
On a usual week, there are multiple GO AI blog posts going out. Here are some notable recent articles:
For Businesses and Other Organizations, What Makes a Successful Chatbot?
IBM Watson vs. ChatGPT vs. Gemini: How Will Each Affect Search Engines?
Using A.I. to Find Resources for Business Owners
How Would Restricting Open-Source A.I. Affect Business Owners?
The EU’s A.I. Act Has Become Law: The Implications for Business Owners (Especially American)
In addition to our GO AI blog, we also have a blog that offers important updates in the world of search engine optimization (SEO), with blog posts like “Google Ends Its Plan to End Third-Party Cookies”.
