The logistical challenges faced by international automakers are myriad, thanks to the globalized nature of the supply chain. Parts, tools and materials come from all over the world and must be constantly tracked, resulting in a slow, labour-intensive process that takes its toll on the bottom line.
Today, as automakers seek to leverage artificial intelligence for their self-driving vehicles, so too do they look for ways to use AI in their logistics processes in an effort to streamline operations and reduce costs.
Case in point: MLaaS is currently being used by a leading automaker to manage assets used in its manufacturing process. Previously, the client employed an multi-step procurement process wherein purchasers, suppliers and procurement staff engaged in a time-consuming exchange that had changed little in decades. The result was a system that while accurate, was very slow and ripe for technological disruption.
With MLaaS the client is able to explore the possibility of introducing AI into this process. After some initial analysis, we identified a few areas in which AI could make significant improvement:
MLaaS built a model from a dataset of images of asset labels tools. With this MLaaS can automatically confirm the presence of a label in seconds through a web application. If the label is not visible, the asset does not make it to the next step in the supply chain
At the next stage in the supply chain, a manual verification is required to ensure that the asset label matches the asset shipped. This is a laborious process that requires cross-referencing the characters on the label to a database, and visually confirming that the label is on the correct asset.
Using MLaaS performs optical character recognition to verify the label information, and employs 3D imaging to verify that the tool in question is the correct one.
This is done in seconds, saving hours of labour and catching any errors or anomalies early.
The final stage of the supply chain process for procurement invovles classifying the physical asset. This is to ensure that the asset shipped is the asset that was ordered.
MLaaS performs tool classification quickly and accurately, alerting the client that they’ve got the correct asset, or that a mistake has been made somewhere along the way.
The introduction of MLaaS into the supply chain process can result in considerably shorter times from start to end. Errors are identified much more quickly, and far less time is spent manually checking databases or requiring additional staff for easily automatable tasks.
MLaaS provided the technology and talent required to achieve the client’s results rapidly, accurately and with considerable cost savings.