Published: 04 December 2018
Summary
Unforeseen asset downtime is a high operational risk to businesses, requiring deeper insights into asset health that IoT sensors and AI models alone are not able to deliver. Application leaders must apply this five-step process to increase the effectiveness of predictive maintenance.
Included in Full Research
- Step 1. Define the Problem and AI Predictive Maintenance Opportunities by Consulting With the Line of Business
- Step 2. Improve Organizational Culture and Appetite for AI as a Decision Maker
- Step 3. Plan for Deployment Infrastructure and Get Budgets Approved
- Step 4. Ensure Training Data Comes From Varied IoT or OT Data Sources
- Step 5. Build and Review the Predictive Maintenance ML Models