IoT-enabled infrastructure in factories produce mountains of data that managers can use to optimize plant operations. IoT technology and the sensors that generate most of this data are key building blocks for executing on the industry 4.0 vision of a smart factory. The proper analysis and visualization of this data, coupled with machine learning deployed in the cloud or at the edge, can help companies achieve higher degrees of productivity, flexibility, and innovation and compete more effectively.
The need to stitch together the tools required to support the entire workflow — from data prep to machine learning and MLOps (machine learning model operationalization management) — requires broad specialized knowledge and expertise, as well as significant upfront investment. Coupled with the need for data to pass between systems and tools, these factors introduce substantial amounts of risk into the implementation process.
We built Altair® SmartWorks™ Analytics specifically to address these challenges and enable data-driven decision making and AI-augmented automation. In this video, we demonstrate how to build an analytics pipeline, including deployment of MLOps models, in a smart factory environment.
Empower everyone to make augmented, data-driven decisions. See how with SmartWorks Analytics.
This video was produced using SmartWorks Analytics 2021.3.