The Oracle Fusion Cloud Maintenance 25D release, part of the broader Oracle Cloud SCM
quarterly update, was deployed to non-production environments and to production
environments. This release introduces AI-driven enhancements, improved reporting
capabilities, and streamlined workflows to boost efficiency in asset management, work order
processing, and diagnostics. Key focus areas include conversational AI agents for faster task
execution and expanded analytics for better decision-making.
Key New Features and Enhancements
- Maintenance Work Order Builder AI Agent
A new conversational AI agent template enables users to create, update, or retrieve
maintenance work orders via natural language interactions, bypassing traditional UI navigation.
Users can specify details like asset number, work order type, subtype, priority, description, and
planned start date when creating orders (with or without operations). For retrieval, input a
single work order number to get full details (e.g., status, dates, operations) or filter lists by
criteria such as date range, asset, or status for a structured summary.
Benefits: Reduces time spent on manual data entry and screen navigation, improves reliability
for fragmented inputs, and supports proactive monitoring of work order activity. This
empowers maintenance teams to handle routine tasks more efficiently, minimizing errors and
accelerating response times.
Setup/Usage Notes: The agent is available immediately upon release; no additional opt-in
required. Test in non-production to ensure integration with existing workflows.
Impact: High—ideal for field technicians or planners dealing with high-volume work orders. - New OTBI Attributes for Enhanced Reporting and Analysis
Oracle Transactional Business Intelligence (OTBI) now includes new attributes for real-time,
self-service reporting directly from Fusion Cloud Maintenance. Key additions: Asset Route
Hierarchy ID, Code, Name, Description, End Date, Completion, and Skip Allowed.
Benefits: Facilitates deeper insights into maintenance routes and hierarchies, enabling better
trend analysis, compliance tracking, and operational optimization. Supports custom dashboards
for visualizing asset performance and route completion rates.
Setup/Usage Notes: Attributes are auto-available in OTBI subjects; users may need to refresh
reports or add them to existing queries. Recommend validating report accuracy post-upgrade.
Impact: Medium—enhances data-driven decisions without custom development.
- AI Agents for Equipment Maintenance and Diagnostics
New embedded AI agents assist with equipment diagnostics, predictive maintenance alerts, and
exception handling in work orders. These integrate with broader SCM AI capabilities, providing
recommendations based on historical data and real-time sensor inputs (if connected).
Benefits: Speeds up issue resolution, reduces downtime through proactive diagnostics, and
automates routine checks. Complements the Work Order Builder by handling specialized
maintenance scenarios.
Setup/Usage Notes: Agents are opt-in via the AI Configuration task in Setup and Maintenance.
Requires Redwood UI for full functionality; ensure IoT or sensor data feeds are configured if
applicable.
Impact: High—particularly valuable for asset-intensive industries like manufacturing or energy.
EnchantApps Oracle Cloud experts can help you with your 25D Upgrade and testing. We are here to ensure that Oracle Cloud quarterly updates do not impact your business processes. Contact us for more details.