Alper Tayfur Deleware 9H AGO

I built a predictive maintenance workflow in Awish for one of my manufacturing clients. The client had machine telemetry, production data, and maintenance history spread across different systems. The problem wasn’t collecting the data—it was spotting failure risk early enough to act. I built a custom Awish workflow that continuously checks machine telemetry and production signals in Snowflake alongside asset, meter, and maintenance history from MaintainX. When it detects abnormal performance or increasing failure risk, it identifies the affected equipment, estimates the likely operational impact, and prepares a recommended maintenance action. Nothing is scheduled automatically at that point. The recommendation first goes to the maintenance manager in Microsoft Teams for approval. Once approved, Awish creates and assigns the work order in MaintainX, then keeps tracking and updating its status until the maintenance is completed. The useful part is that the system does not wait for a machine to fail before maintenance starts, but it also does not let AI make the maintenance decision on its own. The analysis is automated, while the actual intervention still requires human approval. Step-by-step: 1. I described the maintenance process I wanted in the Awish chat. 2. Awish planned the workflow and selected Snowflake, MaintainX, and Microsoft Teams for the required steps. 3. I connected the client’s accounts and approved the automation plan. 4. Awish continuously analyzed production and telemetry data in Snowflake together with MaintainX asset, meter, and maintenance history. 5. When it detected abnormal behavior or increasing failure risk, it identified the affected equipment and estimated the likely operational impact. 6. It prepared a recommended maintenance action and sent it to the maintenance manager in Microsoft Teams. 7. Once the manager approved the recommendation, Awish created and assigned the work order in MaintainX. 8. The workflow continued tracking the work order and updating its status until the maintenance was completed. Trigger → Analyze → Approval → Action Machine signals → Failure-risk analysis → Teams approval → MaintainX work order