Description:DESCRIPTION
TECHNICAL FIELD
[001] This disclosure relates generally to implementing maintenance, and more particularly to a method and system for implementing maintenance of an equipment.
BACKGROUND
[002] Equipment are mechanical asset essential for operations in an industry such as manufacturing, production, and processing. Therefore, the equipment is required to be maintained to enhance the equipment lifecycle, i.e., to maintain an operative, efficient, and cost-effective condition thereof. The equipment lifecycle is enhanced by operating a set of maintenance procedures on the equipment. The set of maintenance procedures are conducted by performing actions on the equipment, such as but not limited to inspecting, tuning, calibrating, repairing, and/or overhauling the equipment periodically.
[003] Conventionally, the set of maintenance procedures are performed by operators and technicians based on a detection of faults and technical manuals. In most of the scenarios, the operators and technicians rely heavily on the technical manuals for guidance. However, the technical manuals are often complex and difficult to interpret, particularly under real-life working conditions. Additionally, when unforeseen equipment malfunctions occur in real-life working conditions, an accurate diagnosis of the malfunction and determination of an appropriate course of action may pose challenges to the technicians and the operators.
[004] Therefore, there is a pressing need to address the above shortcomings and provide a method for maintenance of equipment which is versatile, cost-effective, and can meet a wide range of consumer needs.
SUMMARY
[005] In an embodiment, a method for maintenance of an equipment is disclosed. The method may include determining, by a controller, a procedural information for implementing a maintenance procedure of the equipment based on a user input corresponding to the equipment. The procedural information may be generated by an Artificial Intelligence (AI) model based on a predefined dataset. The method may further include presenting, by a controller, the procedural information on one or more display sections on a graphical user interface (GUI) of an external device communicably coupled to the controller.
[006] In an embodiment, a system for maintenance of an equipment is disclosed. The system may include a controller. The controller may include a processor, and a memory communicatively coupled to the processor. The memory may store processor-executable instructions, which, when executed by the processor, may cause the processor to determine a procedural information for implementing a maintenance procedure of the equipment based on a user input. The procedural information may be generated by a pre-trained Artificial Intelligence (AI) model based on a predefined dataset. Further, the processor may present the determined procedural information on one or more display sections on a graphical user interface (GUI) communicably coupled to the controller.
[007] It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed.
BRIEF DESCRIPTION OF THE DRAWINGS
[008] The accompanying drawings, which are incorporated in and constitute a part of this disclosure, illustrate exemplary embodiments and, together with the description, serve to explain the disclosed principles.
[009] FIG. 1 illustrates a illustrates a functional block diagram of a system for maintenance of equipment, in accordance with an embodiment of the present disclosure.
[0010] FIG. 2 illustrates a functional module diagram of the system of FIG. 1, in accordance with an embodiment of the present disclosure.
[0011] FIG. 3A illustrates an exemplary initial display interface of the system of FIG. 1, in accordance with an embodiment of the present disclosure.
[0012] FIG. 3B illustrates an exemplary GUI with a first display section, in accordance with an embodiment of the present disclosure.
[0013] FIG. 3C illustrates an exemplary GUI with a second display section, in accordance with an embodiment of the present disclosure.
[0014] FIG. 3D illustrates an exemplary GUI with a third display section, in accordance with an embodiment of the present disclosure.
[0015] FIG. 4 illustrates a flowchart of a methodology for maintenance of equipment, in accordance with an embodiment of the present disclosure.
[0016] FIG. 5 illustrates a block diagram of an exemplary computer system for implementing embodiments consistent with the present disclosure.
DETAILED DESCRIPTION OF THE DRAWINGS
[0017] Exemplary embodiments are described with reference to the accompanying drawings. Wherever convenient, the same reference numbers are used throughout the drawings to refer to the same or like parts. While examples and features of disclosed principles are described herein, modifications, adaptations, and other implementations are possible without departing from the scope of the disclosed embodiments. It is intended that the following detailed description be considered as exemplary only, with the true scope being indicated by the following claims. Additional illustrative embodiments are listed.
[0018] Further, the phrases “in some embodiments”, “in accordance with some embodiments”, “in the embodiments shown”, “in other embodiments”, and the like, mean a particular feature, structure, or characteristic following the phrase is included in at least one embodiment of the present disclosure and may be included in more than one embodiment. In addition, such phrases do not necessarily refer to the same embodiments or different embodiments. It is intended that the following detailed description be considered exemplary only, with the true scope and spirit being indicated by the following claims.
[0019] As explained earlier, the equipment is required to be maintained to enhance the equipment lifecycle. The equipment is maintained by the operators and technicians by relying heavily on technical manuals. Nevertheless, the interpretation of the technical manuals, particularly real-life conditions, may pose a risk of inefficiency due to complexity, thus affecting the equipment lifecycle. Additionally, during the equipment malfunctions, the accurate diagnose of the malfunction may be challenging for the operator. Therefore, the need to interpret the technical manuals for maintenance of the equipment.
[0020] To this end, a method for maintenance of equipment is disclosed. The method may include determining by a controller a procedural information for implementing a maintenance procedure of the equipment based on a user input corresponding to the equipment. The procedural information may be generated by an Artificial Intelligence (AI) model based on a predefined dataset. Further, the method may include presenting, by a controller, the procedural information on one or more display sections on a graphical user interface (GUI) of an external device communicably coupled to the controller.
[0021] FIG. 1 illustrates a functional block diagram of a system 100 for maintenance of an equipment, in accordance with an embodiment of the present disclosure. The system 100 may include a controller 102, an external device 112, a data server 114, and a user interface 116 communicably connected to each other through a wired or wireless communication network 110. The controller 102 may include a processor 104, a memory 106, and an input/output (I/O) device 108. Further, the user interface 116 may include a display section 118.
[0022] In an embodiment, examples of processor(s) 104 may include but are not limited to, an Intel® Itanium® or Itanium 2 processor(s), or AMD® Opteron® or Athlon MP® processor(s), Motorola® lines of processors, Nvidia®, FortiSOC™ system on a chip processors or other future processors.
[0023] In an embodiment, the memory 106 may store instructions that, when executed by the processor 104 may cause the processors to execute instructions adapted to manage and monitor the implementation of the maintenance procedure on the equipment. The controller 102 may be configured to receive user input and determine the maintenance procedure of the equipment. The memory 106 may also store various data (for example, an equipment name, an equipment version, a maintenance and operation manual of the equipment, and the like) that may be captured, processed, and/or required by the system 100.
[0024] In an embodiment, the memory 606 may be a non-volatile memory or a volatile memory. Examples of non-volatile memory may include but are not limited to, a flash memory, a Read Only Memory (ROM), a Programmable ROM (PROM), Erasable PROM (EPROM), and Electrically EPROM (EEPROM) memory. Further, examples of volatile memory may include but are not limited to, Dynamic Random Access Memory (DRAM), and Static Random-Access memory (SRAM).
[0025] As will be also appreciated, the above-described techniques may take the form of computer or controller implemented processes and apparatuses for practicing those processes. The disclosure can also be embodied in the form of computer program code containing instructions embodied in tangible media, such as floppy diskettes, solid state drives, CD-ROMs, hard drives, or any other computer-readable storage medium, wherein, when the computer program code is loaded into and executed by a computer or controller, the computer becomes an apparatus for practicing the invention. The disclosure may also be embodied in the form of computer program code or signal, for example, whether stored in a storage medium, loaded into and/or executed by a computer or controller, or transmitted over some transmission medium, such as over electrical wiring or cabling, through fiber optics, or via electromagnetic radiation, wherein, when the computer program code is loaded into and executed by a computer, the computer becomes an apparatus for practicing the invention. When implemented on a general-purpose microprocessor, the computer program code segments configure the microprocessor to create specific logic circuits. The disclosed methods and systems may be implemented on a conventional or a general-purpose computer system, such as a personal computer (PC) or server computer.
[0026] In an embodiment, the controller 102 may include the I/O device 108 which may include a variety of interface(s), for example, interfaces for data input and output devices, and the like. The I/O device 108 may facilitate inputting of instructions by a user communicating with the controller 102. In an embodiment, the I/O device 108 may be wirelessly connected to the controller 102 through wireless network interfaces such as Bluetooth®, infrared, or any other wireless radio communication known in the art. In an embodiment, the I/O device 108 may be connected to a communication pathway for one or more components of the controller 102 to facilitate the transmission of input instructions and output results of data generated by various components such as, but not limited to, processor(s) 104 and memory 106.
[0027] In an embodiment, the data server 114 may be enabled in a remote cloud server or a co-located server and may include a database to store an application, a large language model (LLM) and other data necessary for the system 100 to perform maintenance of the equipment. In an embodiment, the data server 114 may store data input by an external device 112 (e.g., prompts) or output generated by the controller 102. It is to be noted that the application may be designed and implemented as either a web application or a software application. The web application may be developed using a variety of technologies such as HTML, CSS, JavaScript, and various web frameworks like React, Angular, or Vue.js. It may be hosted on a web server and accessible through standard web browsers. On the other hand, the software application may be a standalone program installed on users' devices, which may be developed using programming languages such as Java, C++, Python, or any other suitable language depending on the platform. In an embodiment, the controller 102 may be communicably coupled with the data server 114 through the communication network 110.
[0028] In an embodiment, the communication network 110 may be a wired or a wireless network or a combination thereof. The communication network 110 can be implemented as one of the different types of networks, such as but not limited to, ethernet IP network, intranet, local area network (LAN), wide area network (WAN), the internet, Wi-Fi, LTE network, CDMA network, 5G and the like. Further, the communication network 110 can either be a dedicated network or a shared network. The shared network represents an association of the different types of networks that use a variety of protocols, for example, Hypertext Transfer Protocol (HTTP), Transmission Control Protocol/Internet Protocol (TCP/IP), Wireless Application Protocol (WAP), and the like, to communicate with one another. Further the communication network 110 can include a variety of network devices, including routers, bridges, servers, controllers, storage devices, and the like.
[0029] In an embodiment, the controller 102 may receive a user input for implementing the maintenance procedure on the equipment from an external device 112 through the communication network 110. In an embodiment, the controller 102 and the external device 112 may be a computing system, including but not limited to, a smart phone, a laptop computer, a desktop computer, a notebook, a workstation, a server, a portable computer, a handheld, or a mobile device. In an embodiment, the controller 102 may be, but not limited to, in-built into the external device 112 or may be a standalone controller.
[0030] The system 100 may further include the graphical user interface (GUI) 116. The user may interact with the system 100 via a display section 118 accessible via the GUI 116.
[0031] FIG. 2 illustrates a functional module diagram 200 of the system 100 for implementing maintenance of equipment, in accordance with an embodiment of the present disclosure. In an embodiment, the system 100 may include a graphical user interface (GUI) 116 and the controller 102 of the system 100 may include an input identification module 202, a preprocessing module 204, a mapping module 206, a fault detection module 208, a pre-trained Artificial Intelligence (AI) Model 210, and 3D representation module 216. Further, the mapping module 206 may be communicably connected to a predefined dataset of a database. Further, the pre-trained AI Model 210 may be coupled to an external network 212 and a 3D model repository 218.
[0032] In an embodiment, the graphical user interface (GUI) 116 may be configured to receive user input via the external device 112 in at least one of a text-based input, a speech-based input or an image-based input. Referring to FIG. 3A, which illustrates an initial GUI 300A of the system 100 for implementing maintenance of the equipment, in accordance with an embodiment of the present disclosure. As apparent in FIG. 3A, the initial display interface 300A may include a text input field 302, a selectable camera icon 304 and a selectable microphone icon 306. By way of example, the text input field 302 may allow the user input i.e., the text-based input. Further, the selectable camera icon 304 may allow the user input i.e., the image-based input. Further, the selectable microphone icon 306 may allow the user input i.e., the speech-based input. The processing of the user input is explained in greater details hereinafter.
[0033] In an embodiment, the initial display interface 300A may include the text input field 302. The text input field 302 may include the text-based input which may include a query corresponding to the equipment. The text-based input may include a description of a fault which may include a metadata such as the equipment name, the equipment version classification or serial number, and the like. By way of example, the description of the fault may include a plurality of features defining a degree of fault corresponding to the equipment. The plurality of features may include a user-observed symptoms such as abnormal vibration during operation of the equipment, abnormal noises, a set of indicators, and the like, generated messages such as the servo motor overload error, screen flickering, and the like, a power cycle induced failure, and the like. By way of another example, the equipment name may include an electric chain hoist, servo motor, lathes, mills, slotters, shapers, and the like. The equipment version classification may include EQ series, and the like. For example, the text-based input may include “How to remove chain guide from the electric chain hoist E04?”.
[0034] As depicted in FIG. 3A, the initial display interface 300A may include the selectable camera icon 304 configured to allow the user input i.e., the image-based input. Further, upon selection of the selectable camera icon 304 may invoke a camera of the external device 112 to capture an image or record a video clip of the equipment. The image may include a set of visual indicators from the set of indicators of the equipment such as an error message displayed on the equipment digital screen, a physical deformation, a leakage, smoke, a damaged component, and the like. The image may be utilized to identify the equipment corresponding to the fault and provide the maintenance procedure for the equipment. Further, the video clip may include a set of audible indicators and the set of visual indicators from the set of indicators. The set of audible indicators may include abnormal noises, alarm tones, clicking sounds produced by the equipment, blinking LEDs, and the like.
[0035] In another embodiment, as evident in FIG. 3A, the initial display interface 300A may include the selectable microphone icon 306 which may allow user input i.e., the speech-based input. The selectable microphone icon 306 when activated by the user may invoke a microphone of the external device 112 to receive the speech-based input. The speech-based input may include a verbal information such as but not limited to the description of the fault defining the equipment name, the equipment version, the error description, operating conditions, observed symptoms and the like.
[0036] Referring back to FIG. 2, the input identification module 202 may be configured to receive and analyze the user input fed by the user via the GUI 116 from the external device 112. The input identification module 202 may detect and classify the modality of the user input 116 as the text-based input, the speech-based input or the image-based input by utilizing an input pre-processing technique.
[0037] Upon detecting the user input, the input identification module 202 may transmit the data to the preprocessing module 204. The preprocessing module 204 may be configured to initiate a corresponding preprocessing techniques to convert the user input into a machine-interpretable language to determine a procedural information of the equipment. By way of example, the equipment may be a faulty equipment which is required to be repaired or the equipment which may be due for maintenance.
[0038] For instance, upon receiving the text-based input, the input identification module 202 may tokenize the text-based input into a set of semantic units and transmit the data to the pre-processing module 204. Accordingly, the preprocessing module 204 may apply algorithms such as but not limited to natural language processing (NLP), Named Entity Recognition (NER), rule-based text parsing, finite-state machines (FSM), and the like for intent recognition, entity extraction and context disambiguation. Further, the preprocessing module 204 may transmit the data to the mapping module 206 which may further convert the tokenized text-based input into a structured query format for interfacing with the predefined dataset 214 to retrieve corresponding to maintenance procedure. Particularly, the predefined dataset may include a user manual, a characteristics data, and a specification data. Each data from the predefined dataset may include a failure pattern repository defining the plurality of features non-existent in a database of the system 100 and a matching pattern repository defining the plurality of features existent in the database of the system 100. Based on the predefined dataset and the tokenized text-based input, the maintenance procedure may be determined. The maintenance procedure may include, but not limited to a replacement of worn or degraded component of the equipment, lubricating the moving the plurality of components of the equipment, cleaning of the filtration unit, replenishment of thermal management fluids, and the like.
[0039] In another instance, upon receiving the image-based input, the input identification module 202 may transmit the image or the video clip to the preprocessing module 204 which may include a cloud-based or edge-deployed image analysis engine which may apply convolutional neural networks (CNN), optical character recognition, capsule network, recurrent neural network, graph neural network, and the like for a feature extraction of the fault of the equipment and a classification of the equipment. By way of example, the feature extraction may include the plurality of features defining the faults in the equipment. By way of another example, the classification may include determination of one or more faulty components of the equipment, determination of the equipment name and equipment version corresponding to the fault. Further, the preprocessing module 204 may transmit the extracted feature to the mapping module 206 to compare the extracted features with the failure pattern of the predefined dataset 210 to retrieve corresponding maintenance procedure.
[0040] In case of the image-based input, the preprocessing module 204 may extract textual information from the plurality of features such as the error message displayed on the display screen of the equipment, the set of indicators, the classification of the equipment. The extracted textual information may be transmitted to the mapping module 206 for interfacing with the predefined dataset 214.
[0041] Further, in case of the video-based input, the pre-processing module 204 may perform frame-by-frame analysis combined with audio signal processing to detect abnormal audio indicators from the set of indicators and abnormal visual indicators from the set of indicators. Such extracted features may be mapped, via the mapping module 206, with the failure pattern repository of the predefined dataset 210 for further analysis and determination of the maintenance procedure corresponding to the equipment.
[0042] In yet another instance, upon receiving the speech-based input, the input identification module 202 may transmit a verbal waveform to the preprocessing module 204 which may include a cloud-based automatic speech recognition (ASR) system for transcription. Based on the transcription, a predefined text (in a predefined format) defining the features of the fault may be extracted. Upon extraction, the predefined text may undergo preprocessing techniques such as NLP, NER, FSM and the like as explained earlier including tokenization, semantic tagging, entity recognition, syntactic parsing and the like to extract features. Further, the extracted features may be mapped, via the mapping module 206, with the failure pattern repository of the predefined dataset 210 for further analysis and determination of the maintenance procedure corresponding to the equipment.
[0043] Further, the fault detection module 208 may be configured to determine a procedural information of the equipment based on the user input i.e., the text-based input, the image-based input, and the speech-based input corresponding to the equipment. The procedural information may be utilized to implement maintenance procedure of the equipment based on the user input corresponding to the equipment. By way of example, the procedural information may include but not limited to a replacement of worn or degraded component from the equipment, lubricating the plurality of components of the equipment, cleaning the filtration unit, replenishment of thermal management fluids, and the like. The procedural information may be generated by the pre-trained artificial intelligence (AI) model 210 based on the predefined dataset 214. Particularly, the pre-trained AI model 210 may be configured to receive, analyze and interpret features extracted from the user input as processed by the mapping module 206. The pre-trained AI model 210 may retrieve inference from trained with the predefined dataset 214 corresponding to the equipment using Retrieval-Augmented Generation (RAG) method. By way of example, the inference may be configured to generate the maintenance procedure based on the predefined dataset. The predefined dataset 210 may include at least one of the user manual, the characteristics data and the specification data.
[0044] By way of example, the RAG method is a hybrid AI architecture which may include a retrieval component and a generative component augmented by the retrieval component that searches relevant text from the predefined dataset 214. The mapping module 206 may be configured to compare the extracted features against the failure pattern repository of the predefined dataset 214 to determine a corresponding fault and intensity thereof. Particularly, the pre-trained AI model 210 may query the predefined dataset 214 using the extracted features to retrieve the most relevant information from the predefined dataset 214. The retrieved information may then be analyzed using the generative model to infer the appropriate maintenance procedure along with the safety instructions and one or more maintenance tools required to implement the maintenance procedure. In case a matching solution is identified within the predefined dataset 214, the corresponding maintenance procedure along with the safety instructions and maintenance tools requirement may be communicated to the user via one or more display sections of the GUI 116.
[0045] In case the solution may be non-existent or not found within the predefined dataset 214, the pre-trained AI model 210 may initiate an external source retrieval. Particularly, the pre-trained AI model 210 may be configured to perform dynamic content retrieval over the external network 212, such as the internet. The pre-trained AI model 210 may search for publicly available knowledge bases such as manufacturer support portals, equipment forums, technical documentation repositories, structured databases, and the like. The pre-trained AI model 210 may leverage keyword-based or semantic search techniques to identify potentially relevant web resources and extract maintenance procedures from the resources using content parsing, contextual summarization, and the like. The extracted maintenance procedure may be communicated to the user via one or more display sections of the GUI 116. In an exemplary embodiment, the pre-trained AI model 210 may apply ranking algorithm or confidence scoring mechanism to prioritize an external maintenance procedure before presenting to the user. Such prioritization may be based on factors such as but not limited to content relevance, source reliability, match confidence, user feedback from previous queries and the like.
[0046] The GUI 116 may be configured to present the procedural information determined by the pre-trained AI model 210 on the one or more display sections on the GUI 116 of the system 100. It is to be noted that the system 100 may be an application, a website, and the like. Particularly, the GUI 116 of the system 100 may include one or more display sections for presenting the procedural information.
[0047] The 3D representation module 216 may be configured to display a 3-dimensional (3D) model of the equipment to at least one of the display sections. The 3D model of the equipment may highlight the areas on the plurality of components of the equipment at which the maintenance procedure needs to be implemented. Further, at least one of the display sections may include an animated 3D representation exhibiting implementation of the maintenance procedure on the equipment.
[0048] Referring to FIG. 3B which illustrates an exemplary GUI 116 with a first display section 300B, in accordance with an embodiment of the present disclosure. FIG. 3C illustrates an exemplary GUI 116 with a second display section 300C, in accordance with an embodiment of the present disclosure. FIG. 3D illustrates an exemplary GUI 116 with a third display section 300D, in accordance with an embodiment of the present disclosure.
[0049] Particularly, the one or more display sections 300B, 300C, 300D of the GUI 116 may include a first display section 300B which may be configured to display one or more safety instructions and warnings to be followed before initiating the maintenance procedure corresponding to the equipment. Further, the one or more display sections 300B, 300C, 300D of the GUI 116 may include a second display section 300C succeeding the first display section 300B which may be configured to display one or more maintenance tools required to implement the maintenance procedure of the equipment. Further, the one or more display sections 300B, 300C, 300D of the GUI 116 may include a third display section 300D succeeding the second display section 300C which may configured to display the procedural information to implement the maintenance procedure of the equipment.
[0050] As explained earlier, the fault detection module 208 may determine the procedural information corresponding to the equipment. Upon determination, the fault detection module 208 may retrieve the associated safety instructions and maintenance tools requirements either from the predefined dataset 214 or from the external network 212. Further, the fault detection module 208 may parse, organize and present the extracted maintenance procedure in a structural format on one or more display sections 300B, 300C, 300D of the GUI 116. Specifically, the fault detection module 208 may display the safety instructions and warnings on the first display section 300B, thereby ensuring that critical safety measures which are known to the user prior to the implementation of the maintenance procedure. Succeeding to the first display section 300B, the fault detection module 208 may display a detailed list of one or more maintenance tools required to implement the maintenance procedure on the second display section 300C. The structured presentation of the maintenance tool requirement may enable the user to prepare the necessary equipment prior in order to reduce procedural delays. Succeeding to the second display section 300C, the fault detection module 208 may display the procedural information to implement the maintenance procedure on the third display section 300D. The procedural information may be presented as a sequential operation to be executed by the user. Further, each procedural information may be indexed and/or time-stamped to facilitate sequential execution.
[0051] In an instance when the user is unable to visually identify the location of the fault or the exact component of the equipment requiring intervention, the 3D representation module 216 may incorporate view of the 3D model of the equipment in the at least one of the display section 300B, 300C, and 300D. The pre-trained AI model 210 may retrieve the 3D model corresponding to the equipment from a 3D model repository 218 of either the predefined dataset 214 or the external network 212. The 3D representation module 216 based on the maintenance procedure may further be configured to algorithmically identify and highlight the relevant sub-components on the 3D model. Further, to enhance user comprehension and provide realistic depiction of the maintenance procedure, the 3D representation module 216 may include the animated 3D representation in the at least one display section 300B, 300C, and 300D. The animated 3D representation may simulate the implementation of each sequential procedure. The animation may depict the manipulation of individual components, positioning of tools, sequence of procedure and the like ensuring an intuitive understanding of complex mechanical and operational procedures.
[0052] To elaborate further, a user may initiate a query to obtain procedural information for the removal of chain guide from the electric chain hoist. To perform the operation, the user may provide either the text-based input, the image-based input or the speech-based input on the GUI 116 of the system. For the text-based input the user may enter the query such as “procedure to remove chain guide from electric chain hoist” in the text input field 302 provided in the initial display interface 300A of the GUI 116. Alternatively, for image-based input, the user may activate the selectable camera icon 304 provided in the initial display interface 300A, which invokes the camera of the external device 112. The user may then capture the image of the electric chain hoist, particularly the region housing the chain guide. Alternatively, for speech-based input, the user may activate the selectable microphone icon 306 provided on the initial display interface 300A which may invoke the microphone of the external device 112. The user may then verbally state a request such as “how to remove a chain guide of electric chain hoist”. Further, upon receiving the input, the input identification module 202 may transmit the user input to the preprocessing module 204 which may convert the user input into the machine-interpretable language and extract features from the user input. The preprocessing module 204 may transmit the extracted feature to the mapping module 206 which may compare the extracted features with the failure pattern of the predefined dataset 210 to retrieve corresponding fault condition. Further, the mapping module 206 may transmit the fault condition to the fault detection module 208.
[0053] The mapping module 206 may access the predefined dataset. Based on the metadata such as but limited to equipment model (e.g. ER2), equipment version (e.g. EQ series), and the like, the mapping module 206 may isolate the manual relevant to the electric chain hoist. Further, the mapping module 206 may locate and extract content pertaining to the procedure for removal of chain guide, the associated safety instructions which must be followed prior to the implementation of the procedure and a list of required maintenance tools. Further, the mapping module 206 may compile the extracted procedure and transmit the data to the fault detection module 208. The fault detection module 208 may parse and present the received data on one or more display sections 300B, 300C, 300D of the GUI 116.
[0054] As evident in FIG. 3B, the fault detection module 208 may display the safety instructions and the warnings to be followed by the user before initiating the chain guide removal procedure such as not to perform disassembly/reassembly during conduction, not to scratch the gear case junction face, and the like on the first display section 300B. Further, as evident in FIG. 3C, the fault detection module 208 may display the list of maintenance tools required for the removal of the chain guide such as plastic hammer, precision screwdriver, three-pawl puller and the like on the second display section 300C. Subsequently, as evident in FIG. 3D, the fault detection module 208 may display a sequential procedure to be followed by the user to remove the chain guide from the electric chain hoist on the third display section 300D.
[0055] For instance, the first step may include the removal of the limit switch cord cover, and the second step may include the removal of the chain guide. Further, to enhance spatial understanding of the procedure, the 3D representation module 216 may generate the 3D model 308 of the electric chain hoist as evident in FIG. 3D. The 3D model 308 may highlight the chain guide assembly within the electric chain hoist. The 3D representation module 216 may further display the animated 3D representation simulating the procedure of removal of chain guide from electric chain hoist such as loosening mounting bolts, disengaging the guide from the chain track and the like.
[0056] It should be noted that all such aforementioned modules 202–216 may be represented as a single module or a combination of different modules. Further, as will be appreciated by those skilled in the art, each of the modules 202–216 may reside, in whole or in parts, on one device or multiple devices in communication with each other. In some embodiments, each of the modules 202–216 may be implemented as dedicated hardware circuit comprising custom application-specific integrated circuit (ASIC) or gate arrays, off-the-shelf semiconductors such as logic chips, transistors, or other discrete components. Each of the modules 202–216 may also be implemented in a programmable hardware device such as a field programmable gate array (FPGA), programmable array logic, programmable logic device, and so forth. Alternatively, each of the modules 202–216 may be implemented in software for execution by various types of processors (e.g., processor 104). An identified module of executable code may, for instance, include one or more physical or logical blocks of computer instructions, which may, for instance, be organized as an object, procedure, function, or other construct. Nevertheless, the executables of an identified module or component need not be physically located together but may include disparate instructions stored in different locations which, when joined logically together, include the module and achieve the stated purpose of the module. Indeed, a module of executable code could be a single instruction, or many instructions, and may even be distributed over several different code segments, among different applications, and across several memory devices.
[0057] FIG. 4 illustrates a flowchart 400 of a methodology for implementing maintenance of the equipment, in accordance with an embodiment of the present disclosure. The method may include a plurality of steps that may be performed by various modules of the controller 102 to determine the maintenance procedure of the equipment.
[0058] At step 402, the controller 102 may determine a procedural information for implementing a maintenance procedure of the equipment based on a user input corresponding to the equipment. Particularly, a user may initiate a query to obtain the procedural information for the maintenance of the equipment by providing a user input. The user input may include at least one of the text-based input, the image-based input and the speech-based input. Based on the detected input type, the controller 102 may be configured to initiate a corresponding preprocessing routine to convert the user input into a machine-interpretable language. Further, the controller 102 may be configured to determine the procedural information of the equipment based on the user input corresponding to the equipment. The procedural information may be generated by an artificial intelligence (AI) model based on a predefined dataset. Particularly, the pre-trained AI model may be operable to receive, analyze and interpret features extracted from the user input. It is to be noted that the pre-trained AI model leverages the predefined dataset related to the equipment during inference using the Retrieval-Augmented Generation (RAG) method to enhance contextual relevance and accuracy. The pre-trained AI model may be configured to compare the extracted features against a failure pattern repository of the predefined dataset to determine a corresponding fault condition and determine the procedural information. In case a matching solution is identified within the predefined dataset, the corresponding maintenance procedure along with the safety instructions and maintenance tools requirement may be communicated to the user via one or more display sections 300B, 300C, 300D.
[0059] Conversely, if the solution is not found within the predefined dataset, the pre-trained AI model may initiate an external source retrieval. Particularly, the pre-trained AI model may be configured to perform dynamic content retrieval over a wide-area network such as internet. The pre-trained AI model may extract maintenance procedures from the resources using content parsing, contextual summarization and the like. The extracted maintenance procedure may be communicated to the user via one or more display sections 300B, 300C, 300D.
[0060] At step 404, the controller 102 may present the procedural information on one or more display sections 300B, 300C, 300D on a graphical user interface (GUI) 116 of an external device communicably coupled to the controller 102. Particularly, the GUI 116 of the system 100 may include one or more display sections 300B, 300C, 300D for presenting the procedural information. Particularly, the one or more display sections 300B, 300C, 300D of the GUI 116 may include a first display section 300B which is configured to display one or more safety instructions and warnings to be followed before initiating a maintenance procedure of the equipment. Further, the one or more display sections 300B, 300C, 300D of the GUI 116 may include a second display section 300C succeeding the first display section 300B which is configured to display one or more maintenance tools required to implement the maintenance procedure of the equipment. Further, the one or more display sections 300B, 300C, 300D of the GUI 116 may include a third display section 300D succeeding the second display section 300C which is configured to display the procedural information to implement the maintenance procedure of the equipment. Further, at least one of the display sections may include a 3-dimensional (3D) model of the equipment highlighting areas on the equipment at which the maintenance procedure needs to be implemented. Further, at least one of the display sections may include an animated 3D representation exhibiting implementation of the maintenance procedure on the equipment.
[0061] The disclosed methods and systems may be implemented on a conventional or a general-purpose computer system, such as a personal computer (PC) or server computer. Referring now to FIG. 5, an exemplary computing system 500 that may be employed to implement processing functionality for various embodiments (e.g., as a SIMD device, client device, server device, one or more processors, or the like) is illustrated. Those skilled in the relevant art will also recognize how to implement the invention using other computer systems or architectures. The computing system 500 may represent, for example, a user device such as a desktop, a laptop, a mobile phone, personal entertainment device, DVR, and so on, or any other type of special or general-purpose computing device as may be desirable or appropriate for a given application or environment. The computing system 500 may include one or more processors, such as a processor 502 that may be implemented using a general or special purpose processing engine such as, for example, a microprocessor, microcontroller or other control logic. In this example, the processor 502 is connected to a bus 504 or other communication medium. In some embodiments, the processor 502 may be an Artificial Intelligence (AI) processor, which may be implemented as a Tensor Processing Unit (TPU), or a graphical processor unit, or a custom programmable solution Field-Programmable Gate Array (FPGA).
[0062] The computing system 500 may also include a memory 506 (main memory), for example, Random Access Memory (RAM) or other dynamic memory, for storing information and instructions to be executed by the processor 502. The memory 506 also may be used for storing temporary variables or other intermediate information during execution of instructions to be executed by the processor 502. The computing system 500 may likewise include a read only memory (“ROM”) or other static storage device coupled to bus 504 for storing static information and instructions for the processor 502.
[0063] The computing system 500 may also include a storage devices 508, which may include, for example, a media drive 510 and a removable storage interface. The media drive 510 may include a drive or other mechanism to support fixed or removable storage media, such as a hard disk drive, a floppy disk drive, a magnetic tape drive, an SD card port, a USB port, a micro USB, an optical disk drive, a CD or DVD drive (R or RW), or other removable or fixed media drive. A storage media 512 may include, for example, a hard disk, magnetic tape, flash drive, or other fixed or removable medium that is read by and written to by the media drive 510. As these examples illustrate, the storage media 512 may include a computer-readable storage medium having stored therein particular computer software or data.
[0064] In alternative embodiments, the storage devices 508 may include other similar instrumentalities for allowing computer programs or other instructions or data to be loaded into the computing system 500. Such instrumentalities may include, for example, a removable storage unit 514 and a storage unit interface 516, such as a program cartridge and cartridge interface, a removable memory (for example, a flash memory or other removable memory module) and memory slot, and other removable storage units and interfaces that allow software and data to be transferred from the removable storage unit 514 to the computing system 500.
[0065] The computing system 500 may also include a communications interface 518. The communications interface 518 may be used to allow software and data to be transferred between the computing system 500 and external devices. Examples of the communications interface 518 may include a network interface (such as an Ethernet or other NIC card), a communications port (such as for example, a USB port, a micro USB port), Near field Communication (NFC), etc. Software and data transferred via the communications interface 518 are in the form of signals which may be electronic, electromagnetic, optical, or other signals capable of being received by the communications interface 518. These signals are provided to the communications interface 518 via a channel 520. The channel 520 may carry signals and may be implemented using a wireless medium, wire or cable, fiber optics, or other communications medium. Some examples of the channel 520 may include a phone line, a cellular phone link, an RF link, a Bluetooth link, a network interface, a local or wide area network, and other communications channels.
[0066] The computing system 500 may further include Input/Output (I/O) devices 522. Examples may include, but are not limited to a display, keypad, microphone, audio speakers, vibrating motor, LED lights, etc. The I/O devices 522 may receive input from a user and also display an output of the computation performed by the processor 502. In this document, the terms “computer program product” and “computer-readable medium” may be used generally to refer to media such as, for example, the memory 506, the storage devices 508, the removable storage unit 514, or signal(s) on the channel 520. These and other forms of computer-readable media may be involved in providing one or more sequences of one or more instructions to the processor 502 for execution. Such instructions, generally referred to as “computer program code” (which may be grouped in the form of computer programs or other groupings), when executed, enable the computing system 500 to perform features or functions of embodiments of the present invention.
[0067] In an embodiment where the elements are implemented using software, the software may be stored in a computer-readable medium and loaded into the computing system 500 using, for example, the removable storage unit 514, the media drive 510 or the communications interface 518. The control logic (in this example, software instructions or computer program code), when executed by the processor 502, causes the processor 502 to perform the functions of the invention as described herein i.e., the processor 502 may be configured to manage and monitor the implementation of the maintenance procedure on the equipment.
[0068] As will be appreciated by one skilled in the art, a variety of processes may be employed for optimizing resource utilization in cloud-based data processing platforms. For example, the system 100 and the associated processor 102 may determine reference to dynamic values for performing load testing by the processes discussed herein. In particular, as will be appreciated by those of ordinary skill in the art, control logic and/or automated routines for performing the techniques and steps described herein may be implemented by the system 100 and the associated controller 102 either by hardware, software, or combinations of hardware and software. For example, suitable code may be accessed and executed by the one or more processors on the system 100 to perform some or all of the techniques described herein. Similarly, application specific integrated circuits (ASICs) configured to perform some, or all of the processes described herein may be included in the one or more processors on the system 100.
[0069] As will be appreciated by those skilled in the art, the techniques described in the various embodiments discussed above are not routine, or conventional, or well-understood in the art. The techniques discussed above provide for the system and method for maintenance of equipment.
[0070] In light of the above-mentioned advantages and the technical advancements provided by the disclosed method and system, the claimed steps as discussed above are not routine, conventional, or well understood in the art, as the claimed steps enable the following solutions to the existing problems in conventional technologies. Further, the claimed steps bring an improvement in the functioning of the system itself as the claimed steps provide a technical solution to a technical problem.
[0071] As will be appreciated by those skilled in the art, the method and system described in the various embodiments discussed above are not routine, or conventional or well understood in the art. The method and system discussed above may provide several advantages. The disclosed method and the system is capable of storing plurality of user manual, characteristics data, specification dataset corresponding to repair, maintenance and operation for various equipment types and configurations. The system architecture may significantly reduce the time and cognitive effort required by users to locate pertinent information within extensive technical user manuals. The 3D model representation aids the user in accurately identifying physical components and understanding the spatial relationships during maintenance.
[0072] The illustrated steps are set out to explain the exemplary embodiments shown, and it should be anticipated that ongoing technological development will change the manner in which particular functions are performed. These examples are presented herein for purposes of illustration, and not limitation. Further, the boundaries of the functional building blocks have been arbitrarily defined herein for the convenience of the description. Alternative boundaries can be defined so long as the specified functions and relationships thereof are appropriately performed. Alternatives (including equivalents, extensions, variations, deviations, etc., of those described herein) will be apparent to persons skilled in the relevant art(s) based on the teachings contained herein. Such alternatives fall within the scope and spirit of the disclosed embodiments.
[0073] Furthermore, one or more computer-readable storage media may be utilized in implementing embodiments consistent with the present disclosure. A computer-readable storage medium refers to any type of physical memory on which information or data readable by a processor may be stored. Thus, a computer-readable storage medium may store instructions for execution by one or more processors, including instructions for causing the processor(s) to perform steps or stages consistent with the embodiments described herein. The term “computer-readable medium” should be understood to include tangible items and exclude carrier waves and transient signals, i.e., be non-transitory. Examples include random access memory (RAM), read-only memory (ROM), volatile memory, nonvolatile memory, hard drives, CD ROMs, DVDs, flash drives, disks, and any other known physical storage media.
[0074] It is intended that the disclosure and examples be considered as exemplary only, with a true scope of disclosed embodiments being indicated by the following claims. , Claims:CLAIMS
I/We Claim:
1. A method for implementing maintenance of an equipment, the method comprising:
determining, by a controller (102), a procedural information for implementing a maintenance procedure of the equipment based on a user input corresponding to the equipment,
wherein the procedural information is generated by a pre-trained Artificial Intelligence (AI) model based on a predefined dataset; and
presenting, by a controller (102), the procedural information on one or more display sections (300B, 300C, 300D) on a graphical user interface (GUI) (116) of an external device (112) communicably coupled to the controller (102).
2. The method as claimed in claim 1, wherein the pre-trained AI model leverages a predefined dataset related to the equipment during inference using the Retrieval-Augmented Generation (RAG) method to enhance contextual relevance and accuracy, wherein the predefined dataset comprises at least one of:
a user manual;
a characteristics data; and
a specification data.
3. The method as claimed in claim 1, wherein the user input comprises at least one of:
a text-based input;
an image-based input; or
a speech-based input.
4. The method as claimed in claim 1, wherein the one or more display sections (300B, 300C, 300D) comprises:
a first display section (300B) configured to display one or more safety instructions and warnings to be followed before initiating the maintenance procedure of the equipment;
a second display section (300C) succeeding the first display section (300B), wherein the second display section (300C) is configured to display one or more maintenance tools required to implement the maintenance procedure of the equipment; and
a third display section (300D) succeeding the second display section (300C), wherein the third display section (300C) is configured to display the procedural information to implement the maintenance procedure of the equipment.
5. The method as claimed in claim 4, wherein at least one of the display sections comprises:
a 3-dimensional (3D) model (308) of the equipment highlighting areas on the equipment at which the maintenance procedure needs to be implemented; and
an animated 3D representation exhibiting implementation of the maintenance procedure on the equipment.
6. A system (100) for implementing maintenance of an equipment, comprising:
a controller (102), comprising:
a processor (104); and
a memory (106) communicatively coupled to the processor (104), wherein the memory (106) stores processor-executable instructions, which, when executed by the processor (104), causes the processor (104) to:
determine a procedural information for implementing a maintenance procedure of the equipment based on a user input,
wherein the procedural information is generated by a pre-trained Artificial Intelligence (AI) model based on a predefined dataset; and
present the determined procedural information on one or more display sections (300B, 300C, 300D) of a graphical user interface (GUI) (116) communicably coupled to the controller (102).
7. The system (100) as claimed in claim 6, wherein the pre-trained AI model leverages a predefined dataset related to the equipment during inference using the Retrieval-Augmented Generation (RAG) method to enhance contextual relevance and accuracy, wherein the predefined dataset comprises at least one of:
a user manual;
a characteristics data; and
a specification data.
8. The system (100) as claimed in claim 6, wherein the user input comprises at least one of:
a text-based input;
an image-based input; or
a speech-based input.
9. The system (100) as claimed in claim 6, wherein the one or more display sections (300B, 300C, 300D) comprises:
a first display section (300B) configured to display one or more safety instructions and warnings to be followed before initiating a maintenance procedure of an equipment;
a second display section (300C) succeeding the first display section (300B), wherein the second display section is configured to display one or more maintenance tools required to implement the maintenance procedure of the equipment; and
a third display section (300D) succeeding the second display section (300C), wherein the third display section (300D) is configured to display the procedural information to implement the maintenance procedure of the equipment.
10. The system (100) as claimed in claim 9, wherein at least one of the display sections comprises:
a 3-dimensional (3D) model (308) of the equipment highlighting areas on the equipment at which the maintenance procedure needs to be implemented; and
an animated 3D representation exhibiting implementation of the maintenance procedure on the equipment.
11. A graphical user interface (GUI) (116) for presenting procedural information, comprising:
one or more display sections (300B, 300C, 300D) , comprising:
a first display section (300B) configured to display one or more safety instructions and warnings to be followed before initiating a maintenance procedure of an equipment;
a second display section (300C) succeeding the first display section, wherein the second display section (300C) is configured to display one or more maintenance tools required to implement the maintenance procedure of the equipment; and
a third display section (300D) succeeding the second display section (300C), wherein the third display section (300D) is configured to display the procedural information to implement the maintenance procedure of the equipment.
12. The GUI (100) as claimed in claim 11, wherein at least one of the display sections comprises:
a 3-dimensional (3D) model (308) of the equipment highlighting areas on the equipment at which the maintenance procedure needs to be implemented; and
an animated 3-dimensional (3D) representation exhibiting implementation of the maintenance procedure on the equipment.