Do you want to use AI to improve your reactive maintenance? 

We are accepting nominations for a proof of concept program (POC) for proactive maintenance to take place from 6/1/2021 to 8/6/2021.  

This POC is to validate using AI for proactive maintenance, which identifies the causes of asset breakdowns and corrects them before problems occur with maintenance activities. 

The POC will research ways to identify asset maintenance patterns and analyze their root causes using statistical analysis and AI. For example, identifying that there is an unusually high number of work order requests for a particular product and work type, such as cleaning for solar panels; and finding the contributing factors such as the work is done for a specific account, or at a specific location, or by a certain provider; or the panels are provided by the same supplier or belong to a particular batch, etc. Quality managers can use such analysis to understand the root causes and take corrective actions such as changing the service provider, adjusting maintenance schedules, or recalling a defective product.

POC customers will learn an approach for proactive maintenance. This work can also potentially lead to a predictive maintenance project in the future. 

When: The POC runs from 6/1 to 8/6.  

Who: 

• POC candidates must be Salesforce Field Service customers who have a rich set of quality and clean data around work orders and work types
• POC candidates can move fast in getting data and participate in a focused manner in June and July
• Preferably the POC candidates have already participated in prior SFS Einstein pilot

How: Message me on the trailblazer community OR email me at amanes@salesforce.com

What: SFS Proactive Maintenance Einstein POC Overview

So sign up ASAP and don’t miss this rare opportunity to learn more about using AI for proactive maintenance to improve your maintenance operation