Upfront PM Schedules in Demand Forecasting
PTC Orbit integrates confirmed upfront PM Schedules from ServiceMax Core into the Demand Forecasting feature so that planners can see schedule-driven maintenance workload alongside AI-modeled historical forecasts.
Demand forecasting in PTC Orbit traditionally relies on historical work order patterns to project future service demand. For assets covered by ServiceMax Core PM Plans that generate upfront PM Schedules, confirmed future visit dates already exist; they do not need to be inferred. This integration pulls those confirmed schedules directly into PTC Orbit and makes them available as a distinct input to the Demand Forecasting feature.
A planner who opens a demand forecast for a set of assets now sees two types of data side by side: AI-modeled predictions based on historical work orders, and confirmed scheduled maintenance visits drawn from ServiceMax Core PM Schedules. Together, they give planners a complete, centralized view of expected service demand for assets with upfront PM coverage.
PM Plans in ServiceMax Core can be configured to generate PM Schedule records for each covered asset. These records are forward-dated, confirmed visit placeholders that represent scheduled preventive maintenance work. PTC Orbit reads those records through the maintenance data pipeline, normalizes them into the Canonical Data Model, and exposes them as PM forecast data in the Demand Forecasting feature.
This integration has no standalone UI. Planners see its output through the Preventive Maintenance tab inside the demand forecast results overlay on the Demand Forecasting page.
How It Works
When the maintenance data pipeline runs, it extracts PM Plan, PM Coverage, and PM Schedule records from ServiceMax Core and loads them into the Canonical Data Model in Snowflake. When a planner generates a demand forecast that includes assets covered by those PM Plans, PTC Orbit queries the Canonical Data Model for confirmed schedule visits within the forecast period and adds them to the forecast output.
The result appears in the forecast results overlay as a separate count of planned maintenance visits and projected work hours for the selected assets and time window. The planner can compare this planned workload against the AI-modeled historical forecast and against the total forecast on the dedicated tabs in the overlay.
Considerations
Review the following conditions before relying on PM Schedule data in your demand forecast output.
• Only PM Plans that generate upfront PM Schedule records contribute data to this integration. PM Plans that use recurring PM Schedule Definitions and produce no upfront records are handled by the Maintenance Forecasting Engine; see
Maintenance Forecasting Engine for Recurring PM Plans.
• The maintenance data pipeline must be deployed and running before PM Schedule data appears in forecast results. A pipeline that has not synced recently may return stale or incomplete schedule data.
• PM Plans and PM Schedule records must be correctly configured in ServiceMax Core before the pipeline can extract them.
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