Supply Chain Optimization

Digital twins are created using data derived from sensors (often IoT or IIoT) that are attached to or embedded in the original object. This data provides both structural and operational views of what happens to the object in real time, allowing engineers to monitor systems and model systems dynamics.

Overall Equipment Effectiveness: Performant and Scalable End-to-End Equipment Monitoring

Deploying and Maintaining Models on the Edge in Manufacturing

Perform demand forecasting at the part level rather than the aggregate level to minimize disruptions in your supply chain and increase sales. Manage material shortages and predict overplanning

Enabling Computer Vision Applications With the Data Lakehouse

Time series analysis of IOT data on Databricks using DLT and Tempo

Ship-to-Ship Transfer Identification using Geospatial Analytics

Walkthrough of how to scale out existing ML code and skillsets for IOT defect detection on Databricks