INTERNET OF THINGS BASED DETERMINATION OF MACHINE RELIABILITY AND AUTOMATED MAINTAINENACE, REPAIR AND OPERATION (MRO) LOGS
First Claim
1. A computer implemented method for determining reliability of a machine, comprising:
- receiving at least one of machine operational condition data, machine historical operational data and machine specific information data from at least one location through an internet of things (IOT) based machine wearable sensor network;
storing the data in a distributed computer database communicatively coupled to an enterprise resource planning (ERP) system;
extracting, through a computer server, at least one entity information from the data to compare against a pre-defined baseline;
mapping, though a big data machine learning engine, the extracted at least one entity information into a multi-classification model,wherein the mapping includes;
classifying the data into a root cause analysis engine,mapping the data into one or more levels of predictive maintenance (PM) states,wherein the PM states are associated with color schemes including one of a red, yellow and green;
analyzing, through a real-time data feed platform associated with a distributed real-time computation system, the mapped at least one entity information;
indicating, through a machine learning engine coupled to a predictive analytics engine, on a user interface a set of analytical predictions for machine maintenance, repair and operation.
6 Assignments
0 Petitions
Accused Products
Abstract
A computer implemented method and system for determining reliability of a machine includes receiving one of a machine data from one or more locations through an internet of things (IOT) based machine wearable sensor network. The method further includes storing the data in a distributed computer database communicatively coupled to an enterprise resource planning (ERP) system and extracting, through a computer server, one or more entity information from the data to compare against a pre-defined baseline. Further, mapping, though a big data machine learning engine, the extracted one or more entity information into a multi-classification model. The method includes indicating, through a machine learning engine coupled to a predictive analytics engine, on a user interface a set of analytical predictions for machine maintenance, repair and operation.
-
Citations
18 Claims
-
1. A computer implemented method for determining reliability of a machine, comprising:
-
receiving at least one of machine operational condition data, machine historical operational data and machine specific information data from at least one location through an internet of things (IOT) based machine wearable sensor network; storing the data in a distributed computer database communicatively coupled to an enterprise resource planning (ERP) system; extracting, through a computer server, at least one entity information from the data to compare against a pre-defined baseline; mapping, though a big data machine learning engine, the extracted at least one entity information into a multi-classification model, wherein the mapping includes; classifying the data into a root cause analysis engine, mapping the data into one or more levels of predictive maintenance (PM) states, wherein the PM states are associated with color schemes including one of a red, yellow and green; analyzing, through a real-time data feed platform associated with a distributed real-time computation system, the mapped at least one entity information; indicating, through a machine learning engine coupled to a predictive analytics engine, on a user interface a set of analytical predictions for machine maintenance, repair and operation. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
-
-
12. A real-time IOT based system for determination of machine reliability comprising:
-
one or more machine wearable sensors associated with a communications network; an internet of things (IOT) sensor network communicatively coupled to the communications network; an ERP system communicatively coupled to a distributed database over the communications network; a real-time data feed platform associated with a distributed real-time computation system communicatively coupled to the internet of things (IOT) sensor network over the communications network; and a big data machine learning engine coupled to a predictive analytics engine over the communications network, wherein the at least one of machine operational condition data, machine historical operational data and machine specific information data from at least one location is received through an internet of things (IOT) sensor network, wherein the data is stored in a distributed computer database communicatively coupled to an enterprise resource planning (ERP) system, wherein at least one entity information is extracted from the data to compare against a pre-defined baseline, wherein the at least one entity information is mapped onto a supervised multi-classification machine learning model; wherein the mapping includes at least one of; classifying the data into a root cause analysis engine, and mapping the data into one or more predictive maintenance (PM) states, wherein the PM states are associated with color schemes including one of a red, yellow and green, wherein the data is analyzed, through a real-time data feed platform associated with a distributed real-time computation system, and wherein a set of analytical predictions for machine maintenance is indicated, through a machine learning engine coupled to a predictive analytics engine, on a user interface for at least one of a repair, maintenance and operation of the machine. - View Dependent Claims (13, 14, 15, 16, 17, 18)
-
Specification