公开(公告)号：US20240326838A1

公开(公告)日：2024-10-03

申请号：US18694927

申请日：2022-09-30

Applicant: CUMMINS INC.

Inventor： Anshaj Chadha ,  Fatiha Anouar ,  Thomas Lynn McKinley ,  Vikas Narang ,  Greesham Anand

IPC: B60W50/02 ,  B60W50/035

CPC classification number: B60W50/0205 ,  B60W50/035

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.

公开(公告)号：US20240176341A1

公开(公告)日：2024-05-30

申请号：US18431393

申请日：2024-02-02

Applicant: CUMMINS INC.

Inventor： Thomas Lynn McKinley ,  Neha Kichambare ,  Zigmund W. Meluskey ,  Meghana Somwanshi ,  Hari Vedam ,  Devawrat S. Bhave ,  Archana Sahu ,  David C. Hall ,  Tanvi Rao ,  Mrunal Chaudhary

IPC: G05B23/02

CPC classification number: G05B23/0283 ,  G05B23/024

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.