Method and apparatus for managing maintenance for a service provider

Patent metadata

Field	Value
Publication number	US-10607194-B2
Application number	US-201414526768-A
Country	US
Kind code	B2
Filing date	Oct 29, 2014
Priority date	Oct 29, 2014
Publication date	Mar 31, 2020
Grant date	Mar 31, 2020

Abstract

Aspects of the subject disclosure may include, for example, obtaining device diagnostic data for a group of devices that provide communication services to a plurality of customer premises of a plurality of users over a network, obtaining configuration data associated with the plurality of customer premises, obtaining quality key performance indicators associated with the communication services of the plurality of customer premises, applying linear regression to the device diagnostic data, the configuration data and the quality key performance indicators to identify a quality threshold based on a particular configuration, detecting a subset of customer premises from among the plurality of customer premises that are not satisfying the quality threshold, and analyzing a subset of the device diagnostic data that corresponds to the subset of customer premises to determine equipment associated with the subset of customer premises for maintenance. Other embodiments are disclosed.

First claim

What is claimed is:

1. A method comprising:
retrieving, by a predictive maintenance dispatch server comprising a processing system including a processor, device diagnostic data from equipment of a service provider network for a group of devices that provide communication services to a plurality of customer premises of a plurality of users over a network, wherein the device diagnostic data is based on performance monitoring of the group of devices, wherein the device diagnostic data is retrieved from the group of devices via the network, and wherein the predictive maintenance dispatch server is in communication with the group of devices;
retrieving, by the predictive maintenance dispatch server from the equipment of the service provider network, call records obtained via the network and associated with maintenance for the plurality of customer premises;
retrieving, by the predictive maintenance dispatch server from the equipment of the service provider network, dispatch records obtained via the network and associated with site visits for the plurality of customer premises;
retrieving, by the predictive maintenance dispatch server from the equipment of the service provider network, historical records obtained via the network and associated with service performance of the plurality of customer premises;
retrieving, by the predictive maintenance dispatch server from the equipment of the service provider network, configuration data obtained via the network and associated with the plurality of customer premises;
retrieving, by the predictive maintenance dispatch server from the equipment of the service provider network, quality key performance indicators obtained via the network and associated with the communication services of the plurality of customer premises;
applying, by the predictive maintenance dispatch server, linear regression to the configuration data and one of the device diagnostic data, the call records, the dispatch records, the historical records and combinations thereof to obtain a linear regression result that characterizes a quality according to a particular configuration of devices of the group of devices;
identifying, by the predictive maintenance dispatch server, a quality threshold of the particular configuration based on the linear regression result in conjunction with the quality key performance indicators;
comparing, by the predictive maintenance dispatch server, the device diagnostic data to the quality threshold to obtain comparisons;
detecting, by the predictive maintenance dispatch server, a subset of customer premises from among the plurality of customer premises that are not satisfying the quality threshold based on the comparisons;
analyzing, by the predictive maintenance dispatch server, a subset of the device diagnostic data that corresponds to the subset of customer premises;
identifying, by the predictive maintenance dispatch server, equipment associated with the subset of customer premises for corrective action;
generating, by the predictive maintenance dispatch server, a notice to a technician to perform corrective action on the identified equipment, wherein the notice identifies a customer premises where the corrective action is to occur, wherein the technician performs the corrective action at the customer premises using tools specified by the predictive maintenance dispatch server;
evaluating, by the predictive maintenance dispatch server, a success of the corrective action to obtain an evaluation result, the evaluating based on the quality key performance indicators, records of customer care calls for the customer premises subsequent to the corrective action, or a combination thereof; and
integrating, by the predictive maintenance dispatch server, the evaluation result with the dispatch records and the historical records, thereby facilitating determining future corrective action at the customer premises.

2. The method of claim 1 , comprising:
determining, by the predictive maintenance dispatch server, a history of dispatch repair for the plurality of customer premises based on dispatch records; and
determining, by the predictive maintenance dispatch server, corrective actions for the equipment of the subset of customer premises according to the history of dispatch repair.

3. The method of claim 2 , comprising:
evaluating, by the predictive maintenance dispatch server, a success of the corrective actions for the equipment of the subset of customer premises; and
revising, by the predictive maintenance dispatch server, the dispatch records according to the evaluating.

4. The method of claim 1 , wherein the device diagnostic data includes one of set top box counter data, residential gateway counter data, very-high-bit-rate digital subscriber line counter data, wireless access point counter data and combinations thereof, and wherein the quality key performance indicators are based on one of video, broadband, voice services quality.

5. The method of claim 4 , wherein the group of devices includes set top boxes and residential gateways, and wherein the quality key performance indicators are based on one of customer surveys, counters and combinations thereof.

6. The method of claim 1 , wherein the configuration data describes a hardwire connection used by the plurality of customer premises, and wherein the quality key performance indicators are based on demographics of the plurality of users.

7. The method of claim 1 , comprising:
determining, by the predictive maintenance dispatch server, corrective actions for the equipment of the subset of customer premises according to a history of dispatch repair;
determining, by the predictive maintenance dispatch server, tools for the corrective actions for the equipment of the subset of customer premises; and
generating, by the predictive maintenance dispatch server, a dispatch notice identifying the corrective action, the tools for the corrective actions, and a customer premises of the subset of customer premises.

8. A predictive maintenance dispatch server, comprising:
a processing system including a processor; and
a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations, the operations comprising:
retrieving, via network messages, a plurality of device diagnostic datasets for a group of devices that provide communication services to a plurality of customer premises of a plurality of users over a network, wherein the device diagnostic datasets are based on performance monitoring of the group of devices, and wherein the device diagnostic datasets are retrieved from the group of devices via the network;
merging the plurality of device diagnostic datasets obtained via the network to obtain a merged device diagnostic dataset;
retrieving, via network messages, configuration data obtained via the network and associated with the plurality of customer premises;
retrieving quality key performance indicators obtained via the network and associated with the communication services of the plurality of customer premises;
applying linear regression to the merged device diagnostic dataset, the configuration data and the quality key performance indicators to obtain a linear regression result that characterizes a quality according to a particular configuration of devices of the group of devices;
identifying a quality threshold based on the linear regression result in conjunction with the particular configuration;
detecting a subset of customer premises from among the plurality of customer premises that are not satisfying the quality threshold, based on a comparison of the merged device diagnostic dataset to the quality threshold;
analyzing a subset of the merged device diagnostic dataset that correspond

Assignees

• At & T Ip I Lp
• At & T Mobility Ii Llc

Inventors

• Fix Jeremy
• Goehring George
• Lugo Michael

Classifications

• G06Q50/10

  Services · CPC title

• G06Q10/20 Primary

  Administration of product repair or maintenance · CPC title

• G06Q50/32

  Physics · mapped topic

• G06Q50/60

  Business processes related to postal services (shipping G06Q10/083; franking apparatus G07B17/00) · CPC title