Automated generation of condition state information for one or more machines, devices, or systems associated with service or repair events
Examples related to facilitating the training, assessment, and dispatching of technicians to a customer location for at least the purpose of servicing or repairing machines, devices, or systems present at the customer location are presented. The technician can be selected for dispatch to the customer location by review of database information, including training information for the technician, among other things. While at the customer location, the technician can be provided with training information delivered via a training module, where such training material content can comprise written materials, photos, video, virtual assistance, remote assistance, games, or the like. The technician can generate videos or other collateral while at the customer location, which can be included for use in a library of training materials for subsequent use, or for other purposes. Various systems and processes for facilitating the selection, management and deployment of training materials for technicians are also provided herein.
1 . A method of generating information associated with a collection of machines, devices, or systems present at a location, comprising:
a. selecting a location associated with a collection comprising a plurality of machines, devices, or systems for which condition state information is of interest;
b. generating information associated with the plurality of machines, devices, or systems in the collection, wherein the information is derived from:
i. machine, device, or system baseline information associated with each of:
1. Type;
2. Manufacturer;
3. model number;
4. Serial number;
5. Date of manufacture; and
6. Manufacturer-provided technical specifications;
ii. machine, device, or system usage information comprising some or all of:
1. Purchase date;
2. Information associated with a use location;
3. owner or user information; and
4. Information associated with one or more previous service or repair events;
c. deriving, by a computer, context-relevant information associated with the collection from a historical library of machine, device, or system information;
d. analyzing, by the computer, the context-relevant information to generate condition state information for the collection, wherein the collection condition state information is configured as:
i. current or future condition state ratings for one or more machines, devices, or systems in the collection;
ii. current or future condition state ratings for the collection;
iii. costs associated with ownership or management of the plurality of machines, devices, or systems in the collection from a first time to a second time; or
iv. costs associated with management of the collection from the first time to the second time;
e. generating, by the computer, a recommendation associated with whether one or more of the plurality of machines, devices, or systems in the collection should be replaced at a current time or at a later time, thereby providing condition state information for one or more of the plurality of machines, devices, or systems in the collection; and
f. configuring, by the computer, the condition state information for use in one or more of:
i. a user notification;
ii. a report;
iii. a dashboard;
iv. as information for use in a current service or repair event associated with one or more of the machines, devices, or systems in the collection; or
v. as information for use in subsequent condition state generation determinations for one or more of the machines, devices, or systems in the same or a different collection of one or more additional machines, devices, or systems of interest.
2 . The method of claim 1 , wherein the recommendation is associated with a prediction of a number and type of future service or repair events associated with the one or more machines, devices, or systems in the collection.
3 . The method of claim 1 , wherein the context-relevant information includes for the plurality of machines, devices, or systems some or all of:
a. purchase dates;
b. installation location;
c. usage relevant observations; and
d. information associated with one or more previous service or repair events.
4 . The method of claim 3 , wherein the usage-relevant observations include some or all of:
a. approximate amount of use;
b. maintenance observations; and
c. owner or user demographics.
5 . The method of claim 1 further comprising providing a recommendation to an owner or manager for use in selection of a new machine, device, or system for a specific use-case.
6 . The method of claim 1 , wherein the condition state information is used in a subsequent generation of condition state information for the same collection or a different collection.
7 . The method of claim 1 , wherein the collection condition state information is generated automatically by the computer.
8 . The method of claim 7 , wherein the computer-generated collection state information is provided to a human for review, and wherein human-reviewed condition state information is used in a subsequent generation of condition state information for the collection or a different collection.
9 . The method of claim 1 , wherein the collection condition state information is incorporated into machine learning library information for use in subsequent generation of condition state information.
10 . The method of claim 1 , comprising communicating the recommendation to a technician, customer, or owner associated with the selected location associated with the collection.
11 . A method of generating information associated with a condition state for a collection of machines, devices, or systems at a location comprising:
a. selecting a location associated with a collection of machines, devices, or systems for which condition state information is of interest;
b. generating information for the machines, devices, or systems in the collection, wherein the information is derived from:
i. machine, device, or system baseline information associated with each of:
1. Type;
2. Manufacturer;
3. model number;
4. Serial number;
5. Date of manufacture; and
6. Manufacturer-provided technical specifications;
ii. machine, device, or system usage information comprising some or all of:
1. Purchase date;
2. Information associated with a use location;
3. owner or user information; and
4. Information associated with one or more previous service or repair events;
c. deriving, by a computer, context-relevant information associated with the collection from a library of machine, device, or system information;
d. analyzing, by the computer, the context-relevant information to generate condition state information for the collection, wherein the collection condition state information is configured as:
i. current or future condition state ratings for one or more machines, devices, or systems in the collection;
ii. current or future condition state ratings for the collection;
iii. costs associated with ownership or management of the machines, devices, or systems in the collection from a first time to a second time; or
iv. costs associated with management of the collection from the first time to the second time;
e. configuring, by the computer, the collection condition state information for use in one or more of:
i. a user notification;
ii. a report;
iii. a dashboard;
iv. as information for use in a current service or repair event associated with one or more of the machines, devices, or systems in the collection; or
v. as information for use in subsequent condition state generation determinations for one or more of the machines, devices, or systems in the same or a different collection of one or more additional machines, devices, or systems of interest; and
f. incorporating the collection condition state information into machine learning library information for use in subsequent generation of condition state information.
12 . The method of claim 11 , wherein the collection condition state information further includes a prediction of a number and type of future service or repair events associated with one or more machines, devices, or systems in the collection.
13 . The method of claim 11 , further comprising generating a recommendation of whether one or more machines, devices, or systems in the collection need to be replaced at a current time or at a future time.
14 . The method of claim 11 , wherein the context-relevant information includes for the machines, devices, or systems some or all of:
a. purchase dates;
b. installation location;
c. usage relevant observations; and
d. information associated with one or more previous service or repair events.
15 . The method of claim 14 , wherein the usage-relevant observations include some or all of:
a. approximate amount of use;
b. maintenance observations; and
c. owner or user demographics.
16 . The method of claim 11 further comprising providing a recommendation to an owner or manager for use in the selection of a new machine, device, or system for a specific use-case.
17 . The method of claim 11 , wherein the condition state information is used in a subsequent generation of condition state information for the collection or a different collection.
18 . The method of claim 11 , wherein the collection condition state information is generated automatically by the computer.
19 . The method of claim 18 , wherein the computer-generated collection state information is provided to a human for review, and wherein human-reviewed condition state information is used in a subsequent generation of condition state information for the collection or a different collection.