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Artificial Intelligence (AI) is always a practical failure. This is because, by the time that it is successfully applied, it is always called something else. Examples include Google searches, voice recognition and that car navigation "app" on your mobile phone.
And so it is in manufacturing, where some practical applications of AI methods include:
* Dynamically rescheduling production operations as new orders arrive and problems arise on the production floor.
* Assisting materials and production managers with deciding what materials to order and what to make and when.
* Warning material handlers and production workers if they are about to pick or use wrong or defective materials for a job.
* Alerting managers when there are production or materials supply issues they need to pay attention to, such as production jobs running too long or materials needing replenishing.
* Preventing barcode labeling mistakes by automatically selecting and generating the correct label based on such factors as customer, part, container and destination.
The practical use of AI methods makes Manufacturing Execution Systems (MES), Work-in-Process (WIP) tracking and Warehouse Management Systems (WMS) quicker to implement and much simpler to use, but these are never called AI systems as this is "scary" to most people in manufacturing.
Most users of these systems don't realize they are using AI. All they know is that that the system is enabling them to simply capture and view the needed production and inventory tracking data in real-time. And, in return, it is providing them with guidance as to what to do next and warnings when problems are about to arise.
As with mobile phone "apps"...