公开(公告)号：US20220374003A1

公开(公告)日：2022-11-24

申请号：US16245404

申请日：2019-01-11

Applicant: General Electric Company

Inventor： Mustafa Gokhan Uzunbas ,  Ser Nam Lim ,  Ashish Jain ,  Vladimir Shapiro ,  Weiwei Qian ,  Mohamad Bagheri Esfe

IPC: G05B19/418

Abstract: An apparatus, system and method of providing industrial analytics. The apparatus, system and method include at least a plurality of sensors sensing performance indicators for an industrial process across multiple nodes, wherein ones of the multiple nodes are remote from each other; at least one machine learning module comprising non-transitory computing code executed by a processor. When executed by the processor, the code causes the steps of: receiving user input regarding at least the industrial process and a data set; selecting a model based on at least the user input, wherein the selected model comprises a plurality of learnings based on the performance indicators sensed by multiple sensors across at least multiple ones of the multiple nodes; applying the selected model to the data set; assessing at least the performance indicators for the data set upon application of the selected model; and outputting the assessed performance indicator.

公开(公告)号：US11846933B2

公开(公告)日：2023-12-19

申请号：US16245404

申请日：2019-01-11

Applicant: General Electric Company

Inventor： Mustafa Gokhan Uzunbas ,  Ser Nam Lim ,  Ashish Jain ,  Vladimir Shapiro ,  Weiwei Qian ,  Mohamad Bagheri Esfe

IPC: G05B19/418

CPC classification number: G05B19/41875 ,  G05B19/4183 ,  G05B19/41885

Abstract: An apparatus, system and method of providing industrial analytics. The apparatus, system and method include at least a plurality of sensors sensing performance indicators for an industrial process across multiple nodes, wherein ones of the multiple nodes are remote from each other; at least one machine learning module comprising non-transitory computing code executed by a processor. When executed by the processor, the code causes the steps of: receiving user input regarding at least the industrial process and a data set; selecting a model based on at least the user input, wherein the selected model comprises a plurality of learnings based on the performance indicators sensed by multiple sensors across at least multiple ones of the multiple nodes; applying the selected model to the data set; assessing at least the performance indicators for the data set upon application of the selected model; and outputting the assessed performance indicator.