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automotivo

Manutenção preditiva de veículos

O Decision Flow analisa diferentes peças do veículo e suas respectivas características e, em seguida, gera um caminho para a manutenção do veículo.

DecisionRules

David Škarka

Template author

Manutenção preditiva de veículos 1
This Decision Flow evaluates the health of various vehicle components to determine the appropriate maintenance strategy. It analyzes specific vehicle parts and their operational characteristics (such as engine hours and oil metrics) to output a specific path for vehicle care, ranging from simple logging to immediate grounding of the vehicle.

Solution components:
  • A Decision Table named 'Engine Parts' assesses specific vehicle components (e.g., Valve Train, Oil Pump, Oil Filter, Main Bearings). It assigns a "Wear Score" and determines if a part is "Critical" based on inputs like Engine Hours, Oil Temperature, Oil Viscosity, and Vibration RMS.
  • A Decision Table named 'Flag Decision' assigns a maintenance path (Action) based on the aggregated wear score calculated earlier in the flow.
  • A Decision Flow 'Predictive Vehicle Maintenance' orchestrates these Decision Tables and performs:
    • Part Evaluation: The flow begins by running the input data through the 'Engine Parts' decision table to generate wear scores and criticality flags for each component.
    • Criticality Check: The flow performs a logic check to see if the 'Engine Parts' table returned "Yes" for the isCritical output.
      • If Critical: If any part is deemed critical (e.g., Valve Train exceeding 8000 hours), the flow bypasses score aggregation and immediately assigns the path: "Immediate - ground vehicle".
      • If Not Critical: The flow proceeds to the standard scoring logic.
    • Score Aggregation: If the vehicle is not in a critical state, the flow sums the individual wearScore outputs from all processed parts to create a scoreSum.
    • Final Path Assignment: The scoreSum is passed to the 'Flag Decision' table, which determines the final output path based on the severity of the total score.
Use this Decision Flow as a predictive engine to automate vehicle fleet maintenance decisions, ensuring critical failures are addressed immediately while routine wear is scheduled efficiently.
Check iconA checkmark inside a circle signifying "yes"Minus iconA minus inside a circle signifying "no"PROS IconA plus symbol representing positive aspects or benefits.CONS IconA minus symbol representing negative aspects or drawbacks.

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