Predictive Maintenance: Zero to Deployment in Manufacturing

[This article was first published on python – Hi! I am Nagdev, and kindly contributed to python-bloggers]. (You can report issue about the content on this page here)
Want to share your content on python-bloggers? click here.

Predictive maintenance has been seen as a holy grail for cost cutting manufacturing. There are various steps involved in just feasibility study such as problem identification, sensor installation, signal processing, feature extraction and analysis, and finally modeling. Once a reliable and robust model is developed, the model has to be deployed to a manufacturing environment.

Various tools are being used for modeling and deployment such as R, Python, Docker, Kubernetes, JSON, PostgreSQL etc and will be discussing the process and deployment flow in this session.

I will be presenting “Predictive Maintenance: Zero to Deployment in Manufacturing” at ODSC East through virtual conference. The registrations are still open for this conference.

Nagdev-Amruthnath,-PhD_east_2020

To leave a comment for the author, please follow the link and comment on their blog: python – Hi! I am Nagdev.

Want to share your content on python-bloggers? click here.