WO2017048218A1

WO2017048218A1 - Method and apparatus for providing a graphical display associated with a case data structure

Info

Publication number: WO2017048218A1
Application number: PCT/US2015/049910
Authority: WO
Inventors: David Sean FARRELL; David C. Bingham
Original assignee: General Electric Company
Priority date: 2015-09-14
Filing date: 2015-09-14
Publication date: 2017-03-23

Abstract

Approaches are provided for storing a case data structure in a memory device. The case data structure is representative of characteristics of a case associated with an abnormality detected in an industrial machine or system. The case data structure has one or more case content fields, including an evidence field, an interpretation field, and a recommendation field. One or more graphical dashboard widgets are bound to the case data structure and selectively displayed at a display device with one or more of the case content fields. A user viewing the display device can concurrently evaluate the one or more widgets and the case content fields in order to identify a course of action associated with the abnormality detected in the industrial machine or system.

Description

METHOD AND APPARATUS FOR PROVIDING A GRAPHICAL DISPLAY

ASSOCIATED WITH A CASE DATA STRUCTURE

BACKGROUND OF THE INVENTION

FIELD OF THE INVENTION

[0001] The subject matter disclosed herein generally relates to providing information associated with case data structures. More specifically, the subject matter relates to displaying selected graphical widgets along with case data structure associated with a problematic industrial machine or system.

BRIEF DESCRIPTION OF THE RELATED ART

[0002] In industrial operations, industrial machines and systems are monitored to ensure proper operation and/or detect anomalies which may arise. Remote Monitoring & Diagnostic (M&D) approaches often include personnel at one location communicating with personnel at an operating site located at a separate, geographically remote location. The M&D personnel view information related to industrial machines or systems located at the operating site.

[0003] During operation, problems oftentimes occur which may warrant an operator or maintenance engineer's involvement. Using information related to the industrial machine or system, M&D personnel provide recommendations to personnel at the operating site.

[0004] Prior to providing recommendations to operators at the operating site, M&D personnel often consider large amounts of data, such as data associated with the same or similar machine and/or data associated with the same or similar problem. In doing so, M&D personnel must navigate vast amounts of irrelevant or only partially relevant information. When subsequently reviewing a case, it may be difficult for M&D personnel to recall the specific information relied upon in forming a recommendation.

[0005] At the operating site, operators review recommendations provided by M&D personnel. However, operators often are not provided with an indication of the reasoning behind the M&D personnel's recommendation. In some instances, this lack of information results in operators failing to implement the provided recommendation. [0006] The above-mentioned problems have resulted in some user dissatisfaction with previous approaches, inefficient case resolution, and sub-optimal application of remote monitoring and diagnostic approaches.

BRIEF DESCRIPTION OF THE INVENTION

[0007] The approaches described herein provide for selecting and displaying graphical summary widgets to a case data structure associated with a problematic industrial machine or system. The graphical widgets may include a visual representation rolling up underlying data associated with the machine. The approaches discussed herein allow M&D personnel to observe information that has been determined to be relevant or important to a case. Doing so helps M&D personnel achieve higher quality decision-making. The approaches discussed herein also provide operators at an operating site insight into the information assessed by the M&D personnel. As will be apparent, these approaches provide for more accurate and efficient case resolution.

[0008] In many of these embodiments, an apparatus includes a memory device. The memory device includes a case data structure that represents characteristics of a case associated with an abnormality detected in an industrial machine or system. The case data structure includes one or more content fields, including an evidence field with evidence, an interpretation field with an interpretation, and a recommendation field with a

recommendation.

[0009] The evidence in the evidence field includes a characteristic associated with the industrial machine or system. In some approaches, the evidence associated with the industrial machine or system is at least one 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.

[0010] The interpretation in the interpretation field includes a user determined condition based at least in part on the evidence. In some approaches, the interpretation is at least one of a case diagnosis, a case prognosis, a case impact, and a case urgency.

[0011] The recommendation in the recommendation field 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. In some approaches, the recommendation is at least one 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.

[0012] The apparatus also includes an interface having an input and an output, and a processor coupled to the interface and the memory device. The processor is configured to selectively bind one or more of the graphical widgets received at the input to the case data structure. The one or more graphical widgets include a visual representation of underlying data. In some approaches, the processor binds the one or more graphical widgets in response to receiving a user input. In other approaches, the processor is configured to bind the one or more graphical widgets by using computer code that when executed describes the graphical widgets.

[0013] The processor is also configured to provide via the output the one or more graphical widgets with one or more of the case content fields thereby allowing a user to concurrently evaluate the one or more widgets and the content fields in context of each other in order to identify a course of action associated with the abnormality detected in the industrial machine or system.

[0014] In some approaches, the interpretation and the recommendation are received at a first location, and the graphical widgets and one or more of the content fields are displayed at a second location.

[0015] In some approaches, the processor updates the visual representation of the graphical widget in response to a change in the underlying data.

[0016] In another aspect, a method includes storing a case data structure 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 one or more content fields, including an evidence field with evidence, an interpretation field with an interpretation, and a recommendation field with a recommendation.

[0017] The evidence in the evidence field includes a characteristic associated with the industrial machine or system. In some approaches, the evidence associated with the industrial machine or system is at least one 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.

[0018] The interpretation in the interpretation field includes a user determined condition based at least in part on the evidence. In some approaches, the interpretation is at least one of a case diagnosis, a case prognosis, a case impact, and a case urgency.

[0019] The recommendation in the recommendation field 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. In some approaches, the recommendation is at least one 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.

[0020] The method further includes selectively binding one or more graphical widgets to the case data structure. In some aspects, the one or more graphical widgets include a visual representation of underlying data.

[0021] In some approaches, the binding comprises establishing a pointer to the graphical widgets. In other approaches, the binding comprises storing computer code that when executed describes the graphical widgets.

[0022] The method further includes displaying the one or more graphical widgets at a display device with one or more of the case content fields thereby allowing a user to concurrently evaluate the one or more widgets and the content fields in order to identify a course of action associated with the abnormality detected in the industrial machine or system.

[0023] In some approaches, the interpretation and the recommendation are received at a first location and the displaying occurs at a second location.

[0024] In some approaches, the method includes updating the visual representation of the graphical widget in response to a change in the underlying data.

Brief Description of the Drawings

[0025] For a more complete understanding of the disclosure, reference should be made to the following detailed description and accompanying drawings wherein: [0026] 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;

[0027] 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;

[0028] 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;

[0029] FIG. 4 comprises a block diagram illustrating an exemplary case data structure and an exemplary dashboard for managing information relating to industrial machines or systems according to various embodiments of the present invention; and

[0030] FIG. 5 comprises an operational flow chart illustrating an approach for case management according to various embodiments of the present invention.

[0031] 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

[0032] 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 112. Examples of industrial machines 112 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. [0033] Industrial machine 112 is operably connected to a local computing device 114 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 112. In one approach, the computing device 114 is located at the operating site 110. In other approaches, the computing device 114 is instead located remotely from the industrial machine 112.

[0034] 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.

[0035] 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 114 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 112), input information into the computing device 114, send information from the computing device 114 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 114 may be configured to run specific software applications, such as a historian.

[0036] 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 114. Examples of information received and stored at the data storage module 116 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).

[0037] The optional data center 120 is in communication with the operating site 110 (preferably, with the computing device 114 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.

[0038] 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.

[0039] 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 112 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 114 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.

[0040] 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, 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), and 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).

[0041] In addition to the case data structure, M&D personnel review "dashboards" associated with the problematic machine. As used herein, dashboards are graphical summary views of data and performance metrics associated with an industrial machine or system. Dashboards may web-based applications and/or accessible via other software application on a user's computer, for example.

[0042] Dashboards provide current (including real-time) information and historical information for the industrial machine or system. Dashboards may provide system-level overviews, groups of related analytics, or more detailed and rigorous visualizations conveying a single data type. In many approaches, dashboards convey Key Performance Indicators ("KPI") or metrics that quantify, monitor, and benchmark operational performance targets of industrial machines or systems. KPIs manipulate raw data in various arithmetic, combination, averaging, statistical, and logic functions. This is sometimes referred to as "KPI rollup." KPIs include, but are not limited to, trends in behavior over time, comparison of status of related machines, specific documentation links, highlights of best or worst performing machines, bad actor or return to service identifications, criticality ratings, peer comparisons, or identification of most frequent issues experienced. KPIs represent performance metrics that can be standard for an industry, or specific to a location.

[0043] Dashboards communicate such information through charts, graphs, and other data visualizations referred to as graphical widgets. "Graphical widgets," as used herein, refer to software applications or components. The graphical widgets are defined by software modules, programs, or routines that are processed by a processor. Widgets may operate as stand-alone functions, or communicate with web servers or application servers directly or via a network such as, but not limited to, the Internet. General graphical widget manifestations could include a histogram, pie chart, or other statistical-type graphics. They may include stylized images such as a gauge, stoplight with particular 'needle' or color values. Other examples are possible. These graphical widgets demonstrate performance of industrial machines or systems.

[0044] Multiple graphical widgets are provided in a dashboard. A dashboard is often associated a machine or an operating site. The graphical widgets may be displayed in a particular chosen layout at the dashboard. Thus at a glance, users are provided with a comprehensive overview of the status of a machine or operating. With this information, the user may then choose to further investigate selected information. [0045] As mentioned, dashboards may be arranged to display many graphical widgets. However, in many instances, only a select few of the graphical widgets may be relevant to an abnormality detected at a machine or operating site. In this way, personnel reviewing the case data structure (e.g., M&D personnel at central monitoring center 130) selectively bind one or more graphical widgets to the case data structure. By '¾inding," and as used herein, it is meant to associate a first software routine or module with a second one. For example, the second software module (e.g., a case data structure) may include a template portion that is replaced or augmented with the first software module (e.g., a graphical widget) upon association. The association is typically carried out by a processor device either automatically or in response to receiving a user input. Thus, a small number of graphical widgets purposefully selected from a potentially large number from the dashboard are dynamically bound to a case data structure.

[0046] The one or more graphical widgets and the one or more content fields are displayed at a display device (for example, at one or both of the operating site 110 and the central monitoring center 130). The one or more graphical widgets may include a visual representation of underlying data deemed to be relevant or important to the machine 112. The widgets may have multiple levels of information display and user interaction.

[0047] In this way, users at either location can concurrently evaluate the graphical widgets and the case content fields in context of each other, in order to identify a course of action associated with the abnormality detected in the industrial machine or system 112.

[0048] 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 112), 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.

[0049] 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.

[0050] When an anomaly, abnormality, or incident is detected in an industrial machine or system (such as machine 112 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.

[0051] 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.

[0052] Once a case data structure 204 is generated, M&D personnel (located, for example, at central monitoring center 130) use information contained in the case data structure 204 to make various interpretations regarding the problematic machine.

[0053] Prior to, during, or after resolution of the problem (i.e., the "case"), it often is apparent at least some of the information contained within a dashboard associated with the problematic machine provides value in resolving the case. Approaches described herein allow a user to associate such information with the case.

[0054] In this regard, the processor 218 of apparatus 200 shown in FIG. 2 is configured to selectively bind one or more of the graphical widgets received at the input 212 to the case data structure 204. The one or more graphical widgets include a visual representation of underlying data. The processor 218 may be configured to update the visual representation of the graphical widget in response to a change in the underlying data. In some approaches, the processor 218 is configured to bind the one or more graphical widgets in response to receiving a user input. For example, a user at central monitoring center 130, using a computer mouse, touchpad, or other input, may drag the graphical widget into a graphical

representation of the case data structure 204 displayed on a computer monitor. In other approaches, the processor 218 is configured to bind the one or more graphical widgets by using computer code that when executed describes the graphical widgets.

[0055] The processor 218 is further configured to provide via the output 214 the one or more graphical widgets with one or more of the case content fields. This allows a user to concurrently evaluate the one or more widgets and the content fields. In some approaches, this assists personnel with more relevant information to identify the best course of action associated with the abnormality detected in the industrial machine or system.

[0056] In some approaches, the interpretation and the recommendation are received at a first location (e.g., central monitoring center 130), and the graphical widgets and one or more of the content fields are displayed at a second location (e.g., operating site 110).

[0057] In an example implementation of the apparatus 200, a case data structure 204 is generated in response to M&D personnel at a central monitoring center 130 determining a parameter variation in a gearbox of a wind turbine at operating site 110. M&D personnel view information contained in a dashboard associated with the wind turbine. The dashboard displays several graphical widgets associated with the wind turbine, including a graphical widget conveying a peer comparison metric associated with the type of wind turbine. Using this information, M&D personnel determine the gearbox is operating at a reduced efficiency as compared to similar wind turbines. M&D personnel enter a recommended action

("perform maintenance on gearbox") into the case data structure 204. M&D personnel also bind to the case data structure 204 the graphical widget indicative of the peer comparison metric. The graphical widget, along with at least a portion of the case data structure 204, is provided by the output 214 to operators at the operating site 110.

[0058] At the operating site 110, operators are informed not just of the recommended action ("perform maintenance"), but also of a reason for performing the recommended action; i.e., the wind turbine is operating at a reduced efficiency as compared to similar wind turbines, as clearly indicated visually in the widget.

[0059] With reference now to FIG. 3, a case data structure 300 (such as case data structure 204 stored in memory device 202) may store information associated with an industrial machine or system. For example, a recommendation provided to operators at an operating site may be stored in a recommendation field 310. 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.

[0060] Graphical widgets provided to operators at an operating site may be stored in a widget field 322, including those bound from a separate dashboard view.

[0061] A case data structure 300 also includes 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.

[0062] 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.

[0063] The case data structure 300 may also include a rating field 312 (which may further include a rating explanation field 314 and/or a rating provider field 316), a permission field 318, and/or a case history field 320.

[0064] 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.

[0065] With references now to FIG. 4, a case data structure 400 is generated in response to a detected abnormality in an industrial machine or system such as a boiler feed pump turbine. The case data structure includes content fields similar to the case data structure 300 of FIG. 3, such as widget field 402. Also shown in FIG. 4 is a dashboard 404 associated with the same or similar boiler feed pump turbine. The dashboard 404 includes several graphical widgets, including graphical widget 406 indicative of the criticality of the machine or system to the production plan. The graphical widget 406 is bound to the case data structure 400, and more specifically, in the widget field 402 of the case data structure 400.

[0066] With reference now to FIG. 5, a method 500 includes storing 502 a case data structure 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 one or more content fields, including an evidence field with evidence, an interpretation field with an interpretation, and a recommendation field with a

recommendation.

[0067] The evidence in the evidence field includes a characteristic associated with the industrial machine or system. In some approaches, the evidence associated with the industrial machine or system is at least one 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.

[0068] The interpretation in the interpretation field includes a user determined condition based at least in part on the evidence. In some approaches, the interpretation is at least one of a case diagnosis, a case prognosis, a case impact, and a case urgency.

[0069] The recommendation in the recommendation field 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. In some approaches, the recommendation is at least one 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.

[0070] The method further includes selectively binding 504 one or more graphical widgets from a dashboard comprising multiple widgets to the case data structure, the one or more graphical widgets including a visual representation of underlying data.

[0071] In some approaches, the binding comprises establishing a pointer to the graphical widgets. In other approaches, the binding comprises storing computer code that when executed describes the graphical widgets. [0072] The method further includes displaying 506 the one or more graphical widgets at a display device with one or more of the case content fields thereby allowing a user to concurrently evaluate the one or more widgets and the content fields in order to identify a course of action associated with the abnormality detected in the industrial machine or system.

[0073] In some approaches, the interpretation and the recommendation are received at a first location and the displaying occurs at a second location.

[0074] In some approaches, the method includes updating the visual representation of the graphical widget in response to a change in the underlying data.

[0075] 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

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 one or more case content fields, the one or more case content fields including 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, and 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;

selectively binding one or more graphical widgets to the case data structure; and

displaying the one or more graphical widgets at a display device with one or more of the case content fields thereby allowing a user to concurrently evaluate the one or more widgets and the case content fields in order to identify a course of action associated with the abnormality detected in the industrial machine or system.

2. The method of claim 1 , wherein the evidence associated with the industrial machine or system comprises a measured temperature, a measured vibration, a measured pressured, a calculated efficiency, a structural defect, a lifespan of machine, a machine history, or a detected position shift.

3. The method of claim 1, wherein the interpretation comprises a case diagnosis, a case prognosis, a case impact, or a case urgency.

4. The method of claim 1 , wherein the recommendation comprises watch, wait, manual inspection, offline analysis, contact subject matter expert, contact original equipment manufacturer, change operation, invasive inspection, minor maintenance, schedule work, or shut down.

5. The method of claim 1 , wherein the interpretation and the recommendation are received at a first location and the displaying occurs at a second location.

6. The method of claim 1, wherein the binding comprises establishing a pointer to the graphical widgets.

7. The method of claim 1 , wherein the binding comprises storing computer code that when executed describes the graphical widgets.

8. The method of claim 1 , wherein the one or more graphical widgets comprise a visual representation of underlying data.

9. The method of claim 8, further comprising:

updating the visual representation of the graphical widget in response to a change in the underlying data.

10. The method of claim 8, wherein the selectively bound graphical widgets are selected from a dashboard comprising a plurality of graphical widgets.

11. 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 one or more case content fields, the one or more case content fields including 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, and 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;

an interface including an input and an output;

a processor coupled to the interface and the memory device, the processor configured to selectively bind one or more of the graphical widgets received at the input to the case data structure, and provide via the output the one or more graphical widgets with one or more of the case content fields thereby allowing a user to concurrently evaluate the one or more widgets and the case content fields in order to identify a course of action associated with the abnormality detected in the industrial machine or system.

12. The apparatus of claim 11 , wherein the evidence associated with the industrial machine or system comprises a measured temperature, a measured vibration, a measured pressured, a calculated efficiency, a structural defect, a lifespan of machine, a machine history, or a detected position shift.

13. The apparatus of claim 11, wherein the interpretation comprises a case diagnosis, a case prognosis, a case impact, or a case urgency.

14. The apparatus of claim 11 , wherein the recommendation comprises watch, wait, manual inspection, offline analysis, contact subject matter expert, contact original equipment manufacturer, change operation, invasive inspection, minor maintenance, schedule work, or shut down.

15. The apparatus of claim 11 , wherein the interpretation and the recommendation are received at a first location, and the graphical widgets and one or more of the case content fields are displayed at a second location.

16. The apparatus of claim 11 , wherein the processor is configured to bind the one or more graphical widgets in response to receiving a user input.

17. The apparatus of claim 11 , wherein the processor is configured to bind the one or more graphical widgets by using computer code that when executed describes the graphical widgets.

18. The apparatus of claim 11 , wherein the one or more graphical widgets comprise a visual representation of underlying data.

19. The apparatus of claim 18, wherein the processor is further configured to update the visual representation of the graphical widget in response to a change in the underlying data.

20. The apparatus of claim 10, wherein the selectively bound graphical widgets are selected from a dashboard comprising a plurality of graphical widgets.