	US 12,469,012 B2
	Determining maintenance intervals using a combination of models
Ranjan K. Paul, Sammamish, WA (US); Jan Irvahn, Richland, WA (US); Christopher D. Deits, Renton, WA (US); Liessman E. Sturlaugson, St. Louis, MO (US); and Ameya Deepak Kamat, Bengaluru (IN)
Assigned to The Boeing Company, Arlington, VA (US)
Filed by The Boeing Company, Arlington, VA (US)
Filed on Jan. 20, 2023, as Appl. No. 18/157,620.
Prior Publication US 2024/0249248 A1, Jul. 25, 2024
Int. Cl. G06Q 30/00 (2023.01); G06Q 10/20 (2023.01)

CPC G06Q 10/20 (2013.01)

20 Claims

1. A method performed by a computing system for determining a maintenance interval for a subject aircraft configuration, the method comprising:

obtaining sensor data obtained by a set of sensors and reported by an electronic system of each aircraft of a population of multiple aircraft of the subject aircraft configuration;

obtaining a failure mode definition that identifies a set of failure modes involving a component of the subject aircraft configuration;

obtaining a model definition that identifies, for each failure mode of a set of two or more failure modes involving the component, one or more predictive models to be implemented by the computing system for that failure mode from among a set of predictive models;

for a first failure mode of the set of failure modes involving the component, selecting a first predictive model of the set of predictive models based on the model definition;

implementing the first predictive model at the computing system to determine a first lifetime-probability distribution of the first failure mode involving the component based, at least in part, on the sensor data;

for a second failure mode of the set of failure modes involving the component, selecting a second predictive model of the set of predictive models based on the model definition that differs from the first predictive model;

implementing the second predictive model at the computing system that differs from the first predictive model to determine a second lifetime-probability distribution of the second failure mode involving the component based, at least in part, on the sensor data;

determining a maintenance interval for the component based, at least in part, on the first lifetime-probability distribution and the second lifetime-probability distribution; and

outputting the maintenance interval;

wherein the set of predictive models includes two or more of:

a minor-evident model that considers a magnitude of a failure of the component categorized as either (1) loss of function or (2) no loss of function, and by which a lifetime probability distribution determined for a failure mode is based on sensor data involving the loss of function and is not based on sensor data involving no loss of function,

a condition-based model that considers whether a condition has been met on a per-aircraft basis based on the sensor data obtained from the aircraft as a prerequisite to utilizing the sensor data in determining a lifetime probability distribution of a failure mode,

a risk-equivalent model that considers in-service risk by combining (1) a measure of scheduled maintenance with risk with (2) a measure of predictive maintenance with precision in determining a lifetime probability distribution of a failure mode based on sensor data.