Canonical Data Model for Maintenance Objects

PTC Orbit Reference > Canonical Data Model for Maintenance Objects

Reference for the standardized data model in PTC Orbit that normalizes preventive maintenance data from ServiceMax Core and other source systems.

The Canonical Data Model (CDM) for Maintenance defines a standardized set of objects and fields in PTC Orbit that store normalized preventive maintenance data from external source systems. Regardless of the originating platform, all maintenance plan, schedule, coverage, and processing data follows a single, consistent schema in Snowflake.

For this release, the CDM supports data from ServiceMax Core. The Input Data Adaptor extracts PM-related objects from ServiceMax Core, transforms them to the CDM format, and loads them into the corresponding Snowflake tables. Future releases will extend support to additional source systems including ServiceMax Asset 360 on Salesforce, Salesforce Field Service, and SAP.

CDM Objects

The following objects comprise the Canonical Data Model for Maintenance. Each object maps to one or more source objects in ServiceMax Core.

CDM object	Description	ServiceMax Core source
PM Plan	Represents a preventive maintenance plan that defines the scope, frequency, and rules for scheduled maintenance across covered assets.	SVMXC__PM_Plan__c
PM Coverage	Links a PM Plan to specific assets (installed products). Each coverage record identifies an asset covered by the plan and any asset-specific overrides for schedule or template rules.	SVMXC__PM_Coverage__c
PM Schedule	Represents an individual scheduled maintenance visit generated from a PM Plan. Contains the scheduled date, target asset, and work order template reference. Exists only for non-recurring (upfront) PM Schedule Definitions.	SVMXC__PM_Schedule__c
PM Schedule Definition	Defines the recurrence pattern for PM Schedules within a PM Plan: frequency, interval, start date, and generation rules. Plans with recurring definitions do not produce upfront schedule records; the Maintenance Forecasting Engine calculates visits dynamically.	SVMXC__PM_Schedule_Definition__c
PM Process	Defines the processing logic and workflow steps that execute when a PM Schedule is triggered. Contains references to work order templates and service flow configurations.	SVMXC__PM_Process__c
PM Expressions	Defines condition-based or rule-based expressions evaluated during PM processing. Expressions control branching logic, field assignments, and validation rules within the PM workflow.	SVMXC__PM_Expressions__c
PM Work History	Stores a record of each completed preventive maintenance work order linked back to its originating PM Plan and PM Schedule. Captures completion date, actual cost, and on-time status for maintenance performance analytics and trend reporting.	SVMXC__Service_Order__c (filtered)

Key Fields

The following table lists significant fields on the CDM objects that downstream features depend on for demand forecasting and maintenance performance analytics.

CDM object	Field	Description	Data type
PM Plan	Plan Start Date	Date the PM Plan becomes active. The Maintenance Forecasting Engine uses this as the calculation start boundary.	Date
PM Plan	Plan End Date	Date the PM Plan expires. The Forecasting Engine uses this as the calculation end boundary.	Date
PM Schedule Definition	Frequency	Recurrence interval for schedule generation (for example, every 30 days, every 3 months). Used by the Forecasting Engine to calculate projected visits.	Number
PM Schedule Definition	Last Scheduled On	Date of the most recent schedule generation for this definition. Used as the starting point for next-visit calculations.	DateTime
PM Coverage	Asset Reference	Lookup to the Asset (Installed Product) record covered by this PM Plan.	Reference
PM Schedule	Scheduled Date	Target date for the maintenance visit. Populated only for upfront (non-recurring) schedule records.	Date

Considerations

• The CDM supports time-based PM Plans from ServiceMax Core in this release. Condition-based PM Plans are not supported.

• Changes to source system schemas might require corresponding updates to the Input Data Adaptor transformation logic.

• Data quality in the CDM depends on the completeness and accuracy of source system records. Missing or incomplete PM Plan data might affect forecasting accuracy.

• Custom fields on source PM objects that do not map to CDM fields are not extracted by the adaptor. Contact your PTC representative to discuss custom field mapping requirements.