WO2017048269A1

WO2017048269A1 - Method and apparatus for aligning central recommendations with local action intentions

Info

Publication number: WO2017048269A1
Application number: PCT/US2015/050832
Authority: WO
Inventors: David Sean FARRELL
Original assignee: General Electric Company
Priority date: 2015-09-18
Filing date: 2015-09-18
Publication date: 2017-03-23

Abstract

Approaches are provided for a case management system where a case data structure is stored in a memory device. The case data structure represents characteristics of a case associated with an abnormality detected in an industrial machine or system. A recommendation is transmitted from a central computing device at a central location to a local computing device at a remote location. A transmission is then received from the local computing device, wherein the transmission is indicative of at least one of a recommendation acceptance or a recommendation rejection. In response to receiving the transmission indicative of a recommendation acceptance, the recommendation field is changed to be represented by a new and different name. In response to receiving the transmission indicative of a recommendation rejection, an indication of the recommendation rejection is stored in the recommendation field.

Description

METHOD AND APPARATUS FOR ALIGNING CENTRAL RECOMMENDATIONS WITH LOCAL ACTION INTENTIONS

BACKGROUND OF THE INVENTION

Field of the Invention

[0001] The subject matter disclosed herein generally relates to remote equipment monitoring. More specifically, the subject matter relates to aligning central recommendations with local action intentions.

Brief Description of the Related Art

[0002] In industrial operations, equipment and systems are monitored to ensure proper operation and/or detect anomalies which may arise. During operation, problems oftentimes occur which may warrant an operator or maintenance engineer's involvement. Depending on the severity and complexity of the threat, a solution might be easily employed. However, in many environments, determining the appropriate solution to address the problem may be a lengthy, resource-intensive process.

[0003] g site derives 65% of their actions from M&D recommendations. It may be here may be any number of approaches to address it and provide a desired outcome. These approaches may have varying degrees of difficulty and user involvement to ascertain and implement. Further, some approaches may not be known until a given period of time has elapsed and/or any number of alternative issues may be properly ruled out. In environments in which anomalies or failures occur with some frequency, the process of determining the solution to the problem may result in users unnecessarily exploring options which may be previously shown to have failed or produce less than desirable results.

[0004] In some environments, predictive mathematical modeling systems have the capability to detect a developing problem long before it leads to system or component failure. The early notice systems allow greater opportunity to effectively plan and prevent the failure, but may give rise to a lengthy evaluation and decision life cycle. Oftentimes, a user may be unable to ascertain the relation between events and their implication for how and when to address the issue, which may leave the maintenance or operations teams in a state of confusion and disarray. [0005] Further, in some environments, a small number of engineers may be highly knowledgeable and have a unique understanding of the system and its constructs. These users may be able to quickly identify issues and, based on their past experiences, quickly and efficiently address the problem. However, operator or knowledge turnaround may result in a situation in which a subsequent operator may lack the understanding of the system that the expert was in oversight of. Accordingly, substantial time expenditures may be required to reach the level of skill possessed by the subsequent operator if it is even possible to obtain.

[0006] Remote Monitoring & Diagnostic (M&D) approaches often include personnel at one location communicating with personnel at a separate, geographically remote location. For a variety of reasons, communication between the two locations may be inadequate. This may lead to personnel at one location being left unaware what actions were or were not taken at the other location, and what resulted from those actions or inactions.

[0007] The above-mentioned problems have resulted in some user dissatisfaction with previous approaches, sub-optimal application of resources in managing operations, and sub- optimal results in maintaining uptime and effective system performance.

BRIEF DESCRIPTION OF THE INVENTION

[0008] The approaches described herein provide for monitoring, analyzing, and acting upon information obtained from remote industrial sites. In some aspects, M&D personnel at a central monitoring center make recommendations to engineers located at a remote operating site based, for example, on their intensive analysis. The approaches provided herein better track recommendations provided by the M&D personnel, the intentions and actions of the operating site engineers, and the correlation between the two.

[0009] In many of these embodiments, a case data structure is stored in a memory device. The case data structure represents characteristics of a case associated with an abnormality detected in an industrial machine or system. The case data structure includes an evidence field with evidence. The evidence includes a characteristic associated with the industrial machine or system. For example, the evidence associated with the industrial machine or system may include: a measured temperature, a measured vibration, a measured pressured, a calculated efficiency, a structural defect, a lifespan of machine, a machine history, and/or a detected position shift. [0010] The case data structure also includes an interpretation field with an interpretation. The interpretation includes a user determined condition based at least in part on the evidence. For example, the interpretation may be: a case diagnosis, a case prognosis, a case impact (e.g., an indication of the potential scope of impact should the issue proceed to failure), and/or a case urgency (e.g., how soon the analyst feels the issue should be addressed).

[0011] The case data structure also includes a recommendation field with a recommendation. The recommendation includes a user determined course of action to undertake with respect to the industrial machine or system based at least in part on the interpretation. For example, the recommendation may be: watch, wait, manual inspection, offline analysis, contact subject matter expert, contact original equipment manufacturer, change operation, invasive inspection, minor maintenance, schedule work, and/or shut down.

[0012] In some aspects, the case data structure also includes a rating field.

[0013] A recommendation is transmitted from a central computing device at a central location to a local computing device at a remote location. The recommendation may be transmitted, for example, by a processor via an output of an interface.

[0014] A transmission indicative of at least one of a recommendation acceptance or a recommendation rejection is received from the local computing device. The transmission may be received, for example, by the processor via an input of the interface.

[0015] In response to receiving a transmission indicative of a recommendation acceptance, the recommendation field is changed to be represented by a new and different name. The new and different name may include information indicative of an intended action. In response to receiving a transmission indicative of a recommendation rejection, an indication of the recommendation rejection is stored in the recommendation field.

[0016] In some examples, a data signal is transmitted in response to receiving the transmission from the local computing device. The data signal may be, for example, an email. In other approaches, the data signal includes storing, logging, and/or aggregating information derived from the transmission received from the local computing device. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] For a more complete understanding of the disclosure, reference should be made to the following detailed description and accompanying drawings wherein:

[0018] FIG. 1 comprises a comprises an illustration of an informational flow chart for providing information relating to industrial machines or systems according to various embodiments of the present invention;

[0019] FIG. 2 comprises a block diagram illustrating an exemplary apparatus for managing information relating to industrial machines or systems according to various embodiments of the present invention;

[0020] FIG. 3 comprises a block diagram illustrating an exemplary case data structure for managing information relating to industrial machines or systems according to various embodiments of the present invention;

[0021] FIG. 4 comprises an operational flow chart illustrating an approach for case management according to various embodiments of the present invention; and

[0022] FIG. 5 comprises a schematic diagram illustrating an exemplary

recommendation and site intention fields according to various embodiments of the present invention.

[0023] Skilled artisans will appreciate that elements in the figures are illustrated for simplicity and clarity. It will further be appreciated that certain actions and/or steps may be described or depicted in a particular order of occurrence while those skilled in the art will understand that such specificity with respect to sequence is not actually required. It will also be understood that the terms and expressions used herein have the ordinary meaning as is accorded to such terms and expressions with respect to their corresponding respective areas of inquiry and study except where specific meanings have otherwise been set forth herein.

DETAILED DESCRIPTION OF THE INVENTION

[0024] Referring now to FIG. 1, a system 100 for monitoring industrial machines includes an operating site 110, optionally, a data center 120, and a central monitoring center 130. The operating site 110 includes one or more industrial machines, equipment, or systems of industrial machines or equipment 1 12. Examples of industrial machines 1 12 monitored in system 100 include aircraft machinery (e.g., turbine engines), marine machinery, mining machinery, oil machinery, gas machinery, health care machinery, telecom machinery, to mention a few examples. Other examples are possible.

[0025] Industrial machine 112 is operably connected to a local computing device 1 14 such that the computing device 114 receives or obtains information from the industrial machine 112. The computing device 114 may be continuously connected to the industrial machine 112, or may be removably connected to the industrial machine 1 12. In one approach, the computing device 1 14 is located at the operating site 110. In other approaches, the computing device 114 is instead located remotely from the industrial machine 112.

[0026] Information received at the computing device 114 from the industrial machine

112 includes operational characteristics of the industrial machine 112. Operational characteristics may include a measured temperature, a measured vibration, a measured pressured, a calculated efficiency, a structural defect, a lifespan of machine, a machine history, and/or a detected position shift. Other examples are possible.

[0027] The computing device 114 may be any type of hardware device such as a personal computer, a tablet, a cellular telephone, and/or a personal digital assistant. Other examples are possible. The computing device 1 14 may include a processor, an interface (e.g., a computer based program and/or hardware) having an input (which may also include a user input) and an output, a memory, and a display device (e.g., a screen or a graphical user interface which allows for a visualization to be made). In this way, a user of the computing device 114 is able to observe information at the computing device 114 (such as operational characteristics of the industrial machine 1 12), input information into the computing device 114, send information from the computing device 1 14 to a remote device (such as at the data center 120 or the central monitoring center 130), and receive information from a remote device. The computer device 1 14 may be configured to run specific software applications, such as a historian.

[0028] The computing device 114 is operably connected to a data storage module

116. The data storage module 116 includes a memory for short- and/or long-term storage of information received from the computing device 1 14. Examples of information received and stored at the data storage module 1 16 include historical information relating to the industrial machine 112, or information received at the computing device from a remote device (such as at the data center 120 or the central monitoring center 130).

[0029] The optional data center 120 is in communication with the operating site 110

(preferably, with the computing device 1 14 at the operating site) such that the data center 120 can send and/or receive information pertaining to one or more industrial machines 112 located at the operating site 110. The data center 120 maybe located at the operating site 110, at the central monitoring center 130, or in a location geographically remote from the operating site 110 and the central monitoring center 130. In one approach, the data center 120 is disposed on a cloud based network.

[0030] The data center 120 includes one or more data storage modules 122 having corresponding memories. The data center 120 may also include one or more computing devices 124 that include a processor, an interface having an input (which may include a user input) and an output, a memory, and a display device (e.g., a screen or a graphical user interface which allows for a visualization to be made). Various applications may be performed at the data center 120, including analytic modeling, anomaly detection, and/or calculations of key performance indicators.

[0031] The central monitoring center 130 includes a computing device 132 that is in communication with the data center 120 such that the central monitoring center 130 can send and/or receive information pertaining to one or more industrial machines 1 12 located at the operating site 110. Alternatively, the central monitoring center 130 is in communication with the operating site 110 (preferably, with the computing device 1 14 at the operating site) such that the central monitoring center 130 can send and/or receive information pertaining to one or more industrial machines 112 located at the operating site 110.

[0032] In one example of the operation of the system of 100 of FIG. 1, a case data structure is stored in a memory device that may be located, for example, at the data center 120 or at the central monitoring center 130. The case data structure, discussed in greater detail elsewhere herein, represents characteristics of a case associated with an abnormality detected in an industrial machine or system 112. The case data structure includes an evidence field with evidence (e.g., a characteristic associated with the industrial machine or system), an interpretation field with an interpretation (e.g., a user determined condition based at least in part on the evidence), a recommendation field with a recommendation (e.g., a user determined course of action to undertake with respect to the industrial machine or system based at least in part on the interpretation), and a rating field.

[0033] A recommendation is transmitted from a central computing device 132 at central monitoring center 130 to a local computing device 114 at a remote location, such as operating site 110. Personnel at the operating site 110 accept or reject the recommendation. A transmission indicative of at least one of a recommendation acceptance or a recommendation rejection is then transmitted from the local computing device 114 to the central computing device 132.

[0034] In response to receiving the transmission indicative of a recommendation acceptance, the recommendation field stored in the memory is changed to be represented by a new and different name. In response to receiving the transmission indicative of a

recommendation rejection, an indication of the recommendation rejection is stored in the recommendation field.

[0035] With reference now to FIG. 2, an apparatus 200 (such as computing device

132 of FIG. 1) includes a memory device 202. The memory device 202 stores a case data structure 204 (discussed in greater detail elsewhere herein). The memory device 202 may also store one or more work data plans 206 and/or one or more prior case histories 208. A work data plan 206 includes prior maintenance performed on an industrial machine or system (such as industrial machine 1 12), as well as scheduled maintenance to be performed on an industrial machine or system in the future. A prior case history 208 includes previous case data structures 204 associated with an industrial machine or system, or with one or more classifications of industrial machines or systems.

[0036] The apparatus 200 further includes an interface 210 including an input 212

(which preferably includes a user input) and an output 214. The apparatus 200 may also include a display device 216. The apparatus 200 includes processor 218 coupled to the memory device 202, and the interface 210, and optionally, the display device 216.

[0037] When an anomaly, abnormality, or incident is detected in an industrial machine or system (such as machine 1 12 of FIG. 1), a case data structure 204 (or combination of case data structures 204) associated with the case is created and stored in the memory device 202. As used herein, a "case" is associated with an anomaly, an abnormality, or an incident detected in an industrial machine or system, and a "case data structure" 204 includes a data structure that represents a compilation of characteristics of the case. In one approach, the case data structure 204 is generated by personnel at the central monitoring center 130. In another approach, the case data structure 204 is generated at a local computing device (e.g., local computing device 114 at the operating site 110 shown in FIG. 1). In either approach, a user may link evidence, expert interpretation associated with the evidence, metadata describing the particular nature of the industrial machine at issue, and/or other relevant information such that a visual aid is created.

[0038] In one example of the apparatus 200 of FIG. 2, a processor 218 is configured to receive, at the input 212, a response to a recommendation sent from a central computing device at a central location to a remote computing device at a remote location. The response is indicative of at least one of a recommendation acceptance or a recommendation rejection. In response to receiving a transmission indicative of a recommendation acceptance, the processor 218 is configured to change a recommendation field to be represented by a new and different name. In response to receiving a transmission indicative of a recommendation rejection, the processor 218 is configured store in the rejection field an indication of the recommendation rejection.

[0039] With reference now to FIG. 3, a case data structure 300 (such as case data structure 204 stored in memory device 202) may include an evidence field 302 with evidence. The evidence includes information associated with the anomaly and/or the industrial machine 112. For example, the evidence associated with the industrial machine or system may include: a measured temperature, a measured vibration, a measured pressured, a calculated efficiency, a structural defect, a lifespan of machine, a machine history, and/or a detected position shift. The evidence may be in the form of advisories, alarms, charts, or reports.

[0040] The case data structure 300 also includes an interpretation field 304 with one or more interpretations. The interpretation includes a user determined condition based at least in part on the evidence. For example, the interpretation may be: a case diagnosis, a case prognosis, a case impact, and/or a case urgency. The interpretation field 304 may further include an impact field 306 for storing a case impact value, and an urgency field 308 for storing a case urgency value.

[0041] The case data structure 300 also includes a recommendation field 310 with one or more recommendations. The recommendation includes a user determined course of action to undertake with respect to the industrial machine or system based at least in part on the interpretation. For example, the recommendation may be: watch, wait, manual inspection, offline analysis, contact subject matter expert, contact original equipment manufacturer, change operation, invasive inspection, minor maintenance, schedule work, and/or shut down.

[0042] The case data structure 300 may also include a rating field 312 for storing one or more ratings. The rating field 312 may include an explanation field 314 for storing a rating explanation and/or a provider field 316 for storing a rating provider. The case data structure 300 may also include a permission field 318, a case history field 320, and/or one or more widgets 322.

[0043] The information contained in a case data structure 300 may not only be used to assist an analyst in ascertaining a solution to the present case, but it also may be used in subsequent cases to better aid analysts in exploring resolutions which have been historically shown to be effective. Additionally, the system may be configured to automatically access past cases which may be related to the present case to assist the analyst in determining the best solution. Any information that is used in the present case may also be linked to provide additional information within the apparatus.

[0044] The case data structure 300 is structured so as to allow a user to provide updates to the case, to evidence relating to the case, to their expert interpretation as to the meaning and implication of the evidence (that is, what the issue might be, and what to do about it at a particular time), and to their recommendation regarding actions to be taken. Additional abnormalities which may occur prior to or after the creation of the case data structure 300 may also be linked to the created case data structure 300. Ancillary capabilities such as collaboration, workflow with assignment/request timers, analytic escalation notifications, and other constructs can be input and stored in the case data structure 300. That is, whatever data structure is used, the case data structure 300 is easily modified.

[0045] Personnel (e.g., M&D personnel at the central monitoring center 130) review the case data structure 300 and transmit one or more recommendations (e.g., to the local computing device 114 at the remote operating site 110). The central monitoring center 130 may include the apparatus 200 and the recommendation may be transmitted, for example, at the output 214 of processor 218. [0046] Personnel at the remote operating site 110 view the recommendation and send a transmission responsive to the recommendation back to the central monitoring center 130. The responsive transmission is indicative of at least one of a recommendation acceptance or a recommendation rejection.

[0047] At the central monitoring center 130, the transmission indicative of at least one of a recommendation acceptance or a recommendation rejection is received from the local computing device 1 14. The transmission may be received, for example, at the input 212 of processor 218.

[0048] In response to receiving a transmission indicative of a recommendation acceptance, the processor 218 changes the recommendation field (e.g., recommendation field 310 of the case data structure 300) to be represented by a new and different name. The new and different name may include information indicative of an intended action. In response to receiving a transmission indicative of a recommendation rejection, the processor 218 stores in the recommendation field (e.g., recommendation field 310) an indication of the

recommendation rejection.

[0049] In other examples, the processor 218 is configured to transmit via the output

214 a data signal in response to receiving the transmission from the local computing device 114. The data signal may be, for example, an email. In other approaches, transmitting the data signal includes storing, logging, and/or aggregating information derived from the transmission received from the local computing device 114.

[0050] With reference now to FIG. 4, a method 400 includes storing 402 a case data structure (e.g., case data structure 300) in a memory device. As previously discussed, the case data structure represents characteristics of a case associated with an abnormality detected in an industrial machine or system and may include any one or more of the fields and/or information discussed with respect to case data structure 300.

[0051] The method 400 further includes transmitting 404 a recommendation from a central computing device at a central location to a local computing device at a remote location. [0052] The method 400 further includes receiving 406 a transmission from the local computing device, where the transmission is indicative of at least one of a recommendation acceptance or a recommendation rejection.

[0053] In response to receiving a transmission indicative of a recommendation acceptance, the method 400 includes changing 408 the recommendation field to be represented to a new and different name. The new and different name may include information indicative of an intended action. In response to receiving a transmission indicative of a recommendation rejection, the method 400 includes storing 410 in the recommendation field an indication of the recommendation rejection.

[0054] In other examples, the method includes transmitting a data signal in response to receiving the transmission from the local computing device. The data signal may be, for example, an email. In other approaches, transmitting the data signal includes storing, logging, and/or aggregating information derived from the transmission received from the local computing device.

[0055] An example implementation will now be discussed using the examples of FIG.

1, FIG. 3, and FIG. 5. In this example, the M&D personnel at a central monitoring center (e.g., central monitoring center 130) makes a recommendation 500 to engineers at the operating site (e.g., operating site 110). As shown in FIG. 5, the recommendation 500 may be made in one or more forms, including free text form 502, and categorized form 504.

Examples of the categorized recommendation options could include: Watch; Wait; Manual Inspection; Offline Analysis; Contact SME; Contact OEM; Change Operation; Invasive Inspection; Minor Maintenance; Schedule Work; and/or Shut Down. A visual indication at the local computing device (e.g., local computing device 114) of the operating site would then clearly show the on-site engineers that there is an active recommendation.

[0056] The operating site engineers observe this indication, review the case, and assess the need to perform the action recommended. If the operating site engineers agree, they provide an input (for example, by selecting a "Match / Accept" option 506) indicative of their intentions. The name of the recommendation field of the case data structure (e.g., recommendation field 310 of the case data structure 300) is then changed to reflect the intended action. For example, the field is changed from "recommendation" to "intended action." This change in status of the field is clearly evident to both on-site engineers and the M&D personnel at the central monitoring center because the interfaces viewed at the operating site and at the central monitoring center are substantially similar.

[0057] If the operating site engineers do not agree with the recommendation 500, they provide an input (for example, by selecting a "Mismatch / Reject" option 508) indicative of their intentions. They may also enter their intended action (via free text and categorized form) by similarly providing an input (for example, by selecting "Site Initiative" option 510). This option overrides the recommendation 500 provided by the central monitoring center.

[0058] In one aspect, the "rejection" or mismatch between recommendation and on- site intention is logged and bound to other case metadata as future knowledge to aggregate. If the operating site performs an action of its own volition, this is also recorded.

[0059] Thus, the disclosed apparatus and method provide the additional benefit of providing a benchmarking function to capture greater insights and learnings around the human decision processes that can be leveraged over time. Such benchmarking allows for future guidance as to the "synch" between the central monitoring center and the operating site, the veracity of the M&D recommendations on various types of issues, and the correlation of match/mismatch with ultimate outcomes.

[0060] For example, using an aggregation of recommendations and subsequent actions, it may be determined that a specific operating site derives 65% of their actions from M&D recommendations. It may be further observed that this operating site has greater availability and reliability than another operating site that performs 90% of their actions on their own volition. In such a scenario, the other operating site may be directed to follow the M&D recommendations more closely. This directive may also be applied to other operating sites, and fleet-wide improvement may be tracked.

[0061] In another example of using an aggregation of recommendations and subsequent actions, it may be determined that one of the central monitoring centers has a much higher rate of recommendation rejections than the others. In such a scenario, further investigation of the alignment of expertise between the senior M&D analysts and their operating sites should be conducted.

[0062] Preferred embodiments of this invention are described herein, including the best mode known to the inventors for carrying out the invention. It should be understood that the illustrated embodiments are exemplary only, and should not be taken as limiting the scope of the invention.

Claims

WHAT IS CLAIMED IS:

1. A method comprising:

storing a case data structure in a memory device, the case data structure representing characteristics of a case associated with an abnormality detected in an industrial machine or system, the case data structure comprising:

- an evidence field with evidence, the evidence being a characteristic associated with the industrial machine or system;

- an interpretation field with an interpretation, the interpretation being a user determined condition based at least in part on the evidence;

- a recommendation field with a recommendation, the recommendation being a user determined course of action to undertake with respect to the industrial machine or system based at least in part on the interpretation; and

- a rating field;

transmitting a recommendation from a central computing device at a central location to a local computing device at a remote location;

receiving a transmission from the local computing device, the transmission indicative of at least one of a recommendation acceptance or a recommendation rejection;

in response to receiving the transmission indicative of a recommendation acceptance, changing the recommendation field to be represented by a new and different name;

in response to receiving the transmission indicative of a recommendation rejection, storing in the recommendation field an indication of the recommendation rejection.

2. The method of claim 1, further comprising:

in response to receiving the transmission from the local computing device, transmitting a data signal.

3. The method of claim 2, wherein the data signal comprises an email.

4. The method of claim 2, wherein transmitting the data signal comprises at least one of storing, logging, or aggregating information derived from the transmission received from the local computing device.

5. The method of claim 1, wherein the evidence associated with the industrial machine or system is selected from the group consisting of: a measured temperature, a measured vibration, a measured pressured, a calculated efficiency, a structural defect, a lifespan of machine, a machine history, and a detected position shift.

6. The method of claim 1, wherein the interpretation is selected from the group consisting of: a case diagnosis, a case prognosis, a case impact, and a case urgency.

7. The method of claim 1, wherein the recommendation is selected from the group consisting of: watch, wait, manual inspection, offline analysis, contact subject matter expert, contact original equipment manufacturer, change operation, invasive inspection, minor maintenance, schedule work, and shut down.

8. The method of claim 1, wherein the new and different name comprises information indicative of an intended action.

9. An apparatus comprising:

a memory device, the memory device including a case data structure, the case data structure representing characteristics of a case associated with an abnormality detected in an industrial machine or system, the case data structure comprising:

- a rating field;

an interface including an input and an output;

a processor coupled to the memory device and the interface, the processor configured to receive at the input a transmission responsive to a recommendation, the transmission sent from a local computing device at a remote location, the transmission indicative of at least one of a recommendation acceptance or a recommendation rejection, the processor configured to in response to receiving the transmission indicative of a recommendation acceptance, change the recommendation field to be represented by a new and different name, the processor configured in response to receiving the transmission indicative of a recommendation rejection, store in the recommendation field an indication of the recommendation rejection.

10. The apparatus of claim 9, wherein in response to receiving the transmission from the local computing device, the processor is configured to transmit via the output a data signal.

1 1. The apparatus of claim 10, wherein the data signal comprises an email.

12. The apparatus of claim 10, wherein transmission of the data signal comprises at least one of storing, logging, or aggregating information derived from the transmission received from the local computing device.

13. The apparatus of claim 9, wherein the evidence associated with the industrial machine or system is selected from the group consisting of: a measured temperature, a measured vibration, a measured pressured, a calculated efficiency, a structural defect, a lifespan of machine, a machine history, and a detected position shift.

14. The apparatus of claim 9, wherein the interpretation is selected from the group consisting of: a case diagnosis, a case prognosis, a case impact, and a case urgency.

15. The apparatus of claim 9, wherein the recommendation is selected from the group consisting of: watch, wait, manual inspection, offline analysis, contact subject matter expert, contact original equipment manufacturer, change operation, invasive inspection, minor maintenance, schedule work, and shut down.

16. The apparatus of claim 9, wherein the new and different name comprises information indicative of an intended action.