Abstract: Systems, devices, and methods for optimizing troubleshooting procedures for vehicles are disclosed herein. A system includes a processor and a memory storing executable instructions. The executable instructions, when executed by the processor, cause the processor to: obtain in-operation data of a vehicle, the in-operation data including a fault code indicative of a fault in the vehicle; identify a trained model from a plurality of trained models using the fault code; use the trained model and the in-operation data of the vehicle to generate a troubleshooting procedure for identifying a root cause of the fault; and provide the troubleshooting procedure as output to identify the root cause of the fault.

Abstract: Systems and apparatuses include one or more processing circuits comprising one or more memory devices configured to store instructions thereon that cause one or more processors to: receive electronic field performance analytics (eFPA) information related to a component of the vehicle; receive vehicle information including operating conditions and historical vehicle information of the vehicle; receive fleet information including fleet usage and fleet vehicle types of the fleet of vehicles; develop a prognostic model using a machine learning engine that receives the eFPA information, the vehicle information, and the fleet information; determine a failure probability using the prognostic model; compare the failure probability to a predetermined threshold; determine a remaining life of the component when the failure probability is equal to or greater than the threshold; and generate a report identifying the component and the remaining life.