PTC Orbit introduces a Maintenance Performance Dashboard that consolidates maintenance service performance data across an organization's entire install base. Users, such as reliability engineers or asset managers, can analyze maintenance effectiveness by asset groupings, including product, product line, region, or account. The dashboard presents key performance indicators (KPIs) through summary cards, interactive donut charts, and a geographic map visualization that groups asset data by state or country. An AI-powered natural language filter sits at the top of the dashboard; typing a plain-text query like Show me all assets in the MRI product family that belong to the United States automatically resolves the criteria, applies the corresponding filters, and refreshes every chart and KPI card on the page. Filter results appear as interactive pills with hover tooltips for quick review.

Organizations managing large, distributed fleets often lack a unified view of maintenance performance across regions, accounts, and product lines. Without a consolidated dashboard, users tasked with sustainability and optimization of the install base must manually aggregate data from multiple sources; a process that delays root cause analysis and introduces data inconsistencies. The Maintenance Performance Dashboard closes this visibility gap by correlating maintenance execution patterns with failure data and service costs in a single interface. AI-powered filtering removes friction from data exploration; a reliability engineer can reach the exact dataset in seconds instead of navigating multiple dropdown menus and manual filter configurations.

PTC Orbit delivers the Maintenance Performance Dashboard as a packaged feature that activates automatically after upgrade; no administrator setup is required. Dashboard data draws from the existing asset, work order, and maintenance plan objects. The AI-powered natural language filter component needs no separate enablement or configuration.

Opening the Maintenance Performance Dashboard surfaces maintenance KPIs across the install base. Summary cards display metrics such as the count of planned versus reactive maintenance work orders, mean time to repair, and the overall maintenance effectiveness score. The geographic map groups performance data by state or country; interactive charts break down these metrics over the selected time horizon.

Typing a natural language query in the AI prompt applies filters across all dashboard components simultaneously, and each resolved filter appears as an editable pill.

For more information, see Maintenance Performance Dashboard.

PTC Orbit expands Demand Forecasting to incorporate scheduled preventive maintenance alongside ML-based reactive service predictions. The PM Schedules only includes Time Based PM Schedules with an upfront schedule. When a planner creates a forecast, the platform runs two parallel processes: an ML model that analyzes historical work order patterns and a PM forecast engine that projects future work orders from existing PM schedules and their schedule rules. The PM engine evaluates schedule frequency, classifies entries as committed, already in the database, or prospective, projected from rule cadence, and applies each plan's work order creation rule to calculate the expected monthly work order count. Work hour estimates draw from historical service duration records linked to each schedule. The combined forecast merges both sources into a unified monthly projection of anticipated service demand across the install base.

Organizations relying solely on historical work order patterns for demand forecasting miss the planned maintenance dimension. Planners must manually cross-reference PM schedules against AI-generated projections to build a complete capacity plan, which introduces the risk of omissions and double-counting. Expanding demand forecasting with PM schedule data closes this gap by incorporating both planned and unplanned service demand into a single forecast. Staffing models, parts procurement, and budget forecasts reflect the full spectrum of anticipated service activity without manual reconciliation.

The PM forecasting engine activates automatically after upgrade; no separate enablement or configuration is required. The engine reads PM schedule data from platform database objects that are populated by the existing data synchronization pipeline. Administrators who have already configured PM schedule data ingestion through the Input Data Adapter do not need additional setup for this forecasting capability.

A planner building a demand forecast sees three record count cards on the configuration screen: matching assets, matching work orders, and matching PM schedules. The PM schedule count includes only time-based PM schedules with an upfront schedule. After the forecast completes, the results panel offers three viewing tabs: Total Forecast, AI Forecast, and Preventive Maintenance. Bar charts and a data table display forecasted work orders and forecasted work hours per month across the selected time horizon. Each view supports export to PDF, CSV, or Excel.

For more information, see Demand Forecasting.

PTC Orbit introduces Salesforce credential authentication that connects the platform to a ServiceMax Core environment. An administrator stores Salesforce user credentials within PTC Orbit, and the platform uses those credentials to push updated or corrected data back to Core through HTTP Notifications. Without this connection, data flows only into PTC Orbit; corrected records and Windchill-sourced product information require manual re-entry in Core.

Organizations managing asset data in both PTC Orbit and ServiceMax Core face a one-directional data flow problem. Corrections made in PTC Orbit remain isolated from Core unless someone re-enters them manually. Salesforce authentication removes this barrier by establishing a secure, automated connection for data synchronization back to Core; technicians and planners work with the same corrected data across both platforms.

An administrator configures Salesforce authentication credentials in PTC Orbit through the platform credentials workflow. After the credentials are stored, HTTP Notifications can target the connected ServiceMax Core environment for outbound data operations. No additional Matillion pipeline configuration is required for the authentication step itself.

Technicians and planners working in ServiceMax Core see corrected or enriched data that PTC Orbit pushes back automatically. Product information sourced from Windchill, resolved data quality issues, and updated asset attributes synchronize to Core without manual re-entry.

For more information, see Configuring Salesforce Authentication.