SAP PM Predictive Maintenance & AI Process Automation
A ready-to-show SAP-style cockpit for energy / industrial maintenance teams: equipment health,
SAP PM-like notifications, AI-assisted prioritization, human review, order creation and integration observability.
Equipments
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SAP PM technical assets
Open Notifications
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Planner workload
High / Urgent Risk
–
Needs review
Orders Created
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Automation output
AI Observability
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Logged AI calls
Maintenance Notification Worklist
SAP-style worklist with priority, risk and status
| Notification | Equipment | Issue | Status | Priority | Risk |
|---|---|---|---|---|---|
Loading notifications… | |||||
Object Page: Notification Detail
Select a row, then execute AI/process actions
Select a maintenance notification
Practical Business Use Cases & Demo Results
What a SAP user can understand in 2 minutes
1. Prioritize SAP PM notifications
Planner opens new notifications and lets the cockpit classify risk using issue text, equipment criticality and sensor signals.
Visible result: status changes from New to Classified, priority/risk/category are filled and an AI observability record is created.
2. Human review before execution
AI recommendations are not blindly applied. A workflow task is created for planner or maintenance lead review.
Visible result: recommendation record + workflow task with due date and assignee. This supports auditability and compliance.
3. Create maintenance order
After review, the cockpit creates a maintenance-order-like record and logs an integration event to a mock SAP PM target.
Visible result: order count increases, notification status becomes OrderCreated, integration monitor shows a sent event.
Integration Monitor
Integration Suite / Event Mesh-style operational view
Loading integration events…
AI Observability
Prompt, fallback, latency and token estimate records
Loading AI requests…
Backend
SAP CAP Node.js, SQLite, clean service layer
API
OData V4 entities and unbound actions
SAP pattern
BTP side-by-side extension for SAP PM / EAM scenarios
AI pattern
Mock GenAI service, fallback, human-in-the-loop and observability
Why practical
A maintenance planner can see which asset is risky, why AI recommended action, whether a human reviewed it, and whether an integration event reached the target system.