Applications of AI for Predictive Maintenance
Contact IT Dojo for current pricing, available dates, and a custom quote tailored to your team or organization.
Course Duration
1 Day
Audience
Employees of federal, state and local governments; and businesses working with the government.
Prerequisites
Familiarity with machine learning concepts and basic Python experience recommended.
Course Description
In this workshop, participants learn how to identify anomalies and failures in time-series data, estimate the remaining useful life of the corresponding equipment or parts, and map detected anomalies to specific failure conditions. The techniques covered apply directly to predictive maintenance programs across manufacturing, facilities, fleet, and industrial equipment settings.
Learning Objectives
- Identify anomalies and failure patterns in time-series sensor data
- Apply techniques for estimating remaining useful life of equipment or parts
- Map detected anomalies to specific failure conditions
- Build and evaluate a basic predictive maintenance pipeline
Course Outline
1. Predictive Maintenance Fundamentals
- From reactive to predictive maintenance: the business case
- Working with time-series sensor data
- Common failure modes and how they show up in the data
2. Detecting Anomalies in Time-Series Data
- Techniques for identifying anomalies in sensor readings over time
- Handling noisy or incomplete sensor data
- Setting practical detection thresholds
3. Estimating Remaining Useful Life
- Approaches to estimating remaining useful life from sensor trends
- Mapping detected anomalies to specific failure conditions
- Evaluating model confidence and uncertainty
4. Hands-On Lab and Wrap-Up
- Building a predictive maintenance pipeline on sample sensor data
- Evaluating results against known failure events
- Final questions and key takeaways
Frequently Asked Questions
What does this course cover?
This workshop covers identifying anomalies and failures in time-series data, estimating remaining useful life, and mapping anomalies to failure conditions for predictive maintenance.
How long is this course?
Applications of AI for Predictive Maintenance is a one-day workshop, available as live remote online instruction or on-site at your facility.
Who should attend?
Data scientists, ML engineers, and reliability or maintenance engineers who want hands-on experience with AI-based predictive maintenance.
Does IT Dojo offer this training on-site at government or DoD facilities?
Yes. IT Dojo delivers this course on-site at government agencies, DoD commands, and contractor facilities, in addition to live online delivery.
How do I register for this course?
IT Dojo training is employer sponsored. Contact IT Dojo via the Request Training form or call 757-216-3656 to schedule this course for your team.