Operations Management Domain Ontology

FLOW ALGEBRA
TITLE: Operations Management Domain Ontology
VERSION: 1.0
DOMAIN: Business Domains / Operations Management
SOURCE_URL: https://kirethresearch.org/booksai-core/ontologies/domain-ontologies/business-domains/operations-management-domain-ontology.html
STATUS: Domain-based draft; source page content not independently verified.
AUTHORS: Mark Higgins — Sky (Recursive AI)

ONTOLOGY:
  id: operations_management_domain_ontology
  type: DomainOntology
  parent: business_domain_ontology
  purpose: Represent, connect and reason over operational processes, resources, capacity, quality, performance and continuous improvement.

TYPED_ENTITIES:
  Organisation: {id: string, name: string}
  Operation: {id: string, name: string, objective: string}
  Process: {id: string, name: string, inputs: list, outputs: list}
  Activity: {id: string, name: string, duration: duration?}
  Resource: {id: string, category: string, availability: decimal?}
  Workforce: {id: string, skills: list, capacity_hours: decimal?}
  Facility: {id: string, location: string, capacity: decimal?}
  Equipment: {id: string, condition: string, uptime: decimal?}
  Supplier: {id: string, name: string}
  InventoryItem: {id: string, sku: string, quantity: decimal, reorder_point: decimal?}
  Demand: {id: string, period: string, quantity: decimal}
  ProductionPlan: {id: string, period: string, target_output: decimal}
  WorkOrder: {id: string, status: string, due_date: date?}
  QualityStandard: {id: string, metric: string, threshold: decimal}
  PerformanceMetric: {id: string, metric: string, value: decimal, unit: string, measured_at: datetime}
  Risk: {id: string, likelihood: decimal?, impact: decimal?}
  ImprovementAction: {id: string, objective: string, status: string}

RELATIONSHIPS:
  Organisation --OPERATES--> Operation
  Operation --COMPRISES--> Process
  Process --CONTAINS--> Activity
  Process --CONSUMES--> Resource
  Process --PRODUCES--> Output
  Workforce --PERFORMS--> Activity
  Equipment --SUPPORTS--> Process
  Facility --HOSTS--> Operation
  Supplier --SUPPLIES--> InventoryItem
  InventoryItem --INPUT_TO--> Process
  Demand --INFORMS--> ProductionPlan
  ProductionPlan --SCHEDULES--> WorkOrder
  WorkOrder --USES--> Resource
  QualityStandard --GOVERNS--> Process
  PerformanceMetric --MEASURES--> Process
  Risk --THREATENS--> Operation
  ImprovementAction --IMPROVES--> Process

DERIVED_METRICS:
  utilisation = actual_resource_use / available_resource_capacity
  throughput = completed_units / elapsed_time
  cycle_time = total_process_time / completed_units
  defect_rate = defective_units / inspected_units
  on_time_delivery = on_time_orders / completed_orders
  inventory_turnover = cost_of_goods_sold / average_inventory_value
  capacity_gap = forecast_demand - effective_capacity
  NOTE: Ratios require non-zero denominators, consistent units and aligned reporting periods.

INFERENCE_RULES:
  R1: IF forecast_demand > effective_capacity THEN flag capacity_constraint.
  R2: IF stock_on_hand <= reorder_point AND reorder_point is defined THEN propose_replenishment_review.
  R3: IF observed_defect_rate > quality_threshold THEN flag quality_nonconformance.
  R4: IF task_dependency is incomplete THEN mark dependent_task as blocked.
  R5: IF equipment_downtime increases AND process_throughput decreases THEN flag potential_equipment_bottleneck; do not assert causality without evidence.
  R6: IF improvement_action changes a measured process THEN compare before_and_after metrics with comparable periods and confounder checks.
  R7: IF delivery_date > committed_date THEN flag late_delivery.
  R8: IF risk_exposure exceeds approved_limit THEN request mitigation_review.

CONFIDENCE:
  range: [0.0, 1.0]
  evidence_factors: [source_reliability, data_freshness, measurement_quality, sample_size, contextual_fit]
  rule: Keep observed facts separate from predictions, hypotheses and inferred causes.

SEMANTIC_EQUIVALENCE:
  operations_management: [operational_management, management_of_operations]
  throughput: [output_rate]
  lead_time: [elapsed_time_from_request_to_completion]
  utilisation: [capacity_utilisation]
  constraints: Do not equate lead_time with cycle_time, efficiency with effectiveness, or utilisation with productivity.

PROVENANCE:
  required_fields: [source_id, source_type, captured_at, method, licence_or_access_basis]
  preserve: [original_value, original_unit, reporting_period, transformation_history]

FLOW_HASH:
  algorithm: SHA-256
  canonical_input: canonical_serialisation_of_ontology_version_entities_relationships_rules_and_provenance
  implementation_note: Compute hash on publication; no hash value is asserted in this draft.

UPDATE_MODEL:
  strategy: versioned_incremental_updates
  triggers: [new_measurement, process_change, supplier_change, standard_revision, correction]
  actions: [validate_schema, reconcile_entities, recompute_derived_metrics, reassess_confidence, record_provenance, recompute_flow_hash]
  history: preserve_prior_versions

AI_CONSUMPTION:
  formats: [plain_text, structured_graph, JSON-LD_mapping_optional]
  capabilities: [entity_resolution, dependency_tracing, capacity_analysis, operational_risk_detection, quality_monitoring, improvement_reasoning]
  safeguards: [no_unsupported_causality, unit_validation, temporal_alignment, uncertainty_disclosure, human_review_for_high_impact_decisions]

END FLOW ALGEBRA