System and method for providing automated customized product support for material testing systems

Abstract

Providing a system to support customized material testing systems. [Solution] An exemplary system disclosed for providing support for a customized material testing system comprises: a support server configured to supplement queries with information identifying one or more identifiable components; a knowledge base containing troubleshooting information; a knowledge base editor configured to modify the knowledge base based on input received via a user interface; and a query processing server configured to generate a response to a query by processing natural language user input, information identifying one or more identifiable components, and troubleshooting information, and to provide the response and a selection of troubleshooting information based on the response to the user device.

Description

Technical Field

[0001] [Related Applications] This application claims the benefit of U.S. Provisional Patent Application No. 63 / 746,574, filed on January 17, 2025, entitled "SYSTEMS AND METHODS FOR PROVIDING AUTOMATED CUSTOMIZED PRODUCT SUPPORT FOR MATERIAL TEST SYSTEMS". The entire content of U.S. Provisional Patent Application No. 63 / 746,574 is hereby incorporated by reference in its entirety.

[0002] This disclosure relates generally to mechanical testing, and more particularly to systems and methods for providing automated customized product support for material test systems.

Background Art

[0003] General-purpose testing machines are used to perform mechanical tests such as compression strength tests or tensile strength tests on materials or components. When an error or problem occurs in such a testing machine, the user or owner often tries to obtain support from the machine manufacturer. For this purpose, the testing machine manufacturer may provide support services including telephone-based support by trained technicians and / or on-site visits.

Summary of the Invention

[0004] Systems and methods for providing automated customized product support for a material test system are disclosed, which are generally illustrated by at least one of the figures and generally described with respect to such figures and fully described by the claims.

[0005] These features, aspects, and advantages of the present disclosure, as well as other features, aspects, and advantages, will be better understood when the following detailed description is read with reference to the accompanying drawings, in which like reference numerals represent like parts throughout.

Brief Description of the Drawings

[0006] [Figure 1] This figure shows an example of a test apparatus for performing mechanical property testing according to an aspect of the present disclosure.

[0007] [Figure 2] Figure 1 is a block diagram of an example embodiment of the test apparatus.

[0008] [Figure 3] This figure shows an exemplary system that provides automated customized product support for a materials testing system according to aspects of this disclosure.

[0009] [Figure 4] Figure 3 shows an example user interface that can be used to implement the user device and receive user input, including queries related to the material testing system.

[0010] [Figure 5A] This figure shows an exemplary user interface that can be provided by a knowledge base editor for receiving user input containing troubleshooting information to modify the knowledge base, including troubleshooting task information and / or troubleshooting resource information. [Figure 5B] This figure shows an exemplary user interface that can be provided by a knowledge base editor for receiving user input containing troubleshooting information to modify the knowledge base, including troubleshooting task information and / or troubleshooting resource information.

[0011] [Figure 6] This flowchart shows example machine-readable instructions that the support server in Figure 3 can execute to supplement user support queries using information that identifies one or more identifiable components of the corresponding material testing system.

[0012] [Figure 7] Figure 3 is a flowchart illustrating exemplary machine-readable instructions that an exemplary knowledge base editor can execute to modify a knowledge base based on input received through the user interface.

[0013] [Figure 8] Figure 3 is a flowchart illustrating example machine-readable instructions that the query processing server can execute to generate responses to user support queries by processing natural language user input using troubleshooting information stored in a knowledge base.

[0014] [Figure 9] Figure 3 is a block diagram of an example computing system that can implement a user device, support server, query processing server, language model, knowledge base, and / or knowledge base editor. [Modes for carrying out the invention]

[0015] The drawings are not necessarily to exact scale. Where appropriate, similar or identical reference numbers are used to refer to similar or identical components.

[0016] When conventional mechanical testing equipment is not functioning as required, the operator (or other personnel associated with the equipment) may contact the manufacturer or distributor of the equipment to attempt to troubleshoot the operational problem. Troubleshooting conventional testing systems often requires multiple individual contacts, such as phone calls, emails, text chats, and / or other steps, to provide the service worker with the necessary information to resolve the issue to the operator's satisfaction. Such multiple steps can be a source of frustration for the operator and / or reduce the uptime of the equipment for performing mechanical testing. Furthermore, if the problem cannot be resolved by a remote service worker, a visit by the service worker themselves may be required, which increases service costs for the equipment owner and / or support service provider.

[0017] The disclosed exemplary systems and methods improve the ability of test system owners or operators to diagnose common problems encountered by material testing systems at a lower cost and / or in less time. In the disclosed examples, the support system for the material testing system provides users with relevant troubleshooting information more quickly and accurately, using language models such as large-scale language models, along with information about the identifiable individual components of the material testing system. The disclosed exemplary systems and methods reduce problem resolution time, reduce equipment service costs, and improve uptime.

[0018] As used herein, "large language model" refers to a very large deep learning model pre-trained on a large amount of data. The underlying Transformer is a set of neural networks consisting of an encoder and a decoder with self-attention capabilities. The encoder and decoder extract meaning from text sequences and understand the relationships between words and between sentences in those text sequences.

[0019] According to an aspect of the present disclosure, an exemplary system for providing support for a customized material testing system is a support server configured to supplement a query with information identifying one or more identifiable components of the material testing system related to the query, the material testing system being configured to perform a mechanical test on a test specimen and measure the results of the mechanical test, the query including a natural language input, a support server, a knowledge base including troubleshooting information related to a plurality of material testing systems and a plurality of identifiable components, a knowledge base editor configured to transmit a user interface for input of the troubleshooting information and modify the knowledge base based on the input received via the user interface, and a query processing server configured to generate a response to the query by processing the natural language user input, information identifying one or more of the identifiable components, and the troubleshooting information, and provide the response and a selection of the troubleshooting information related to the query to a user device, the selection of the troubleshooting information being based on the response.

[0020] In some exemplary systems, the information of identifiable components includes information identifying at least one of the type of components of the material testing system, the characteristics of the components, the manufacturing number (serial number) of the components, the model number of the components, or the batch number of the components. In some exemplary systems, the information of identifiable components includes a list of components installed in the material testing system. In some exemplary systems, the query processing server is configured to process natural language user input using a large language model. In some exemplary systems, the user device is a smartphone, a tablet computer, or a computer.

[0021] In some exemplary systems, the support server is configured to communicate with the material testing system to update a list of multiple identifiable components in the material testing system stored in the support server. In some exemplary systems, the support server is configured to communicate with the material testing system and update the list in response to receiving a query.

[0022] Some exemplary systems further include a material testing system, and the material testing system is configured to perform one or more of a compressive strength test, a tensile strength test, a shear strength test, a flexural strength test, a deflection strength test, a tear strength test, a peel strength test, a torsional strength test, or any other compressive or tensile test, or a dynamic test. In some exemplary systems, one or more of the multiple identifiable components are related to the type of test performed by the material testing system. In some exemplary systems, the troubleshooting information includes one or more of a troubleshooting task, a troubleshooting task step, an information document, or a web link to an information resource.

[0023] Figure 1 shows an illustrative materials testing system 100. As shown, the materials testing system 100 includes a materials testing machine 102 (also known as a general-purpose testing machine) and a computing system 200 connected to the materials testing machine 102 via a cable 106. Although shown as physically connected, in some examples the connection may be wireless rather than wired.

[0024] In the example shown in Figure 1, the material testing machine 102 includes a frame 112. In some examples, the frame 112 provides rigid structural support for other components of the material testing machine 102. As shown, the frame 112 comprises a top plate 114 and a bottom base beam 116 connected by two columns 118. In some examples, the columns 118 of the frame 112 can accommodate guide rails and / or drive shafts 212 of the material testing machine 102 (see, for example, Figure 2). For example, the columns 118 may include two lead screws with zero, one, or two or more guide rails, or one lead screw and one or more guide rails.

[0025] In the example in Figure 1, the movable crosshead 120 extends between the support columns 118. In some examples, the movable crosshead 120 can be connected to a guide rail and / or drive shaft 212 housed in the support columns 118 and / or can be configured to move toward and away from the base beam 116 through the (e.g., motorized) operation of the drive shaft(s) 212. Although one movable crosshead 120 is shown in the example in Figure 1, in some examples the material testing machine 102 may have multiple movable crossheads 120 and / or other movable members.

[0026] In the example in Figure 1, the fixture 122 is attached to the bottom base beam 116 of the frame 112 and to the movable crosshead 120. As shown, the lower fixture 122a includes a gripping portion 124a, while the upper fixture 122b includes both a test sensor 126 and a gripping portion 124b. Although one test sensor 126 and two gripping portions 124 are shown in the example in Figure 1, in some examples the number of test sensors 126 and / or gripping portions 124 included in the material testing machine 102 may be more or fewer.

[0027] In the example in Figure 1, the gripping section 124 holds the specimen 128. Although illustrated as a (e.g., steel) rope / wire, in some examples the specimen 128 may be made of some other type of material and / or component. The gripping sections 124a and / or 124b are illustrated as rope holders, but in some examples they may be configured as bolt holders, wedge grips, side-acting grips, manual grips, roller grips, capstan grips, and / or syringe holders, either alternatively or additionally. In some examples one or both of the gripping sections 124 may be replaced by a compression platen configured to compress the specimen 128.

[0028] In the example shown in Figure 1, the test sensor 126 is connected to the gripping section 124 so that the test sensor 126 can measure the force acting on the gripping section 124 (and / or the test piece 128, crosshead 120, etc.). In some examples, the test sensor 126 can be a load cell. In some examples, the test sensor 126 can be any other type of sensor.

[0029] In some cases, the material testing machine 102 can be configured for static mechanical testing. For example, the material testing machine 102 can be configured for compressive strength testing, tensile strength testing, shear strength testing, bending strength testing, deflection strength testing, tear strength testing, peel strength testing (e.g., strength of adhesive bonds), torsional strength testing, and / or any other compressive and / or tensile tests. Additionally or alternatively, the material testing machine 102 can also be configured to perform dynamic testing.

[0030] In some examples, the material testing machine 102 is configured to interface with a computing system 200 to carry out a test method. For example, the computing system 200 can communicate with the controller 214 of the material testing machine 102 (see, for example, Figure 2) to carry out a test method.

[0031] Figure 2 is a block diagram showing details of the computing system 200 and additional details of the material testing machine 102. In the example in Figure 2, the exemplary material testing machine 102 includes one or more actuators 210 connected to one or more drive shafts 212. In some examples, the actuators 210 can be used to provide force to the drive shafts 212 and / or to guide the movement of the drive shafts 212. In some examples, the actuators 210 may include electric motors, pneumatic actuators, hydraulic actuators, piezoelectric actuators, relays, and / or switches.

[0032] A drive shaft 212 is further shown connected to a movable crosshead 120, such that the motion of the drive shaft(s) 212 via an actuator(s) 210 results in the motion of the movable crosshead 120. In the example of Figure 2, the drive shaft 212 is named drive shaft 212, but in some examples, it may be any other mechanical means that moves the movable crosshead 120 through induction by an actuator(s) 210.

[0033] The exemplary material testing machine 102 further includes a controller 214 that electrically communicates with actuators 210. In some examples, the controller 214 may include a processing circuit and / or a memory circuit. In some examples, the controller 214 may be configured to control the material testing machine 102 based on one or more commands, control inputs, and / or test parameters. In some examples, the controller 214 may be configured to convert commands, control inputs, and / or test parameters (received, for example, from a computing system 200) into appropriate signals (e.g., electrical signals) that can be delivered to actuators 210, thereby controlling the operation of the material testing machine 102 (e.g., via actuators 210). For example, the controller 214 may provide one or more signals that instruct actuators 210 to provide more or less power, thereby increasing or decreasing the applied force.

[0034] In the example in Figure 2, the controller 214 further communicates electrically with the fixture 122 (e.g., the gripping unit 124 and one or more test sensors 126). In some examples, the controller 214 can be configured to convert commands, control inputs, and / or test parameters (received, for example, from the computing system 200) into appropriate signals (e.g., electrical signals) that can be delivered to the gripping unit 124, thereby controlling the operation of the gripping unit 124 (e.g., gripping or releasing). In some examples, the controller 214 can be configured to convert commands, control inputs, and / or parameters (received, for example, from the computing system 200) into appropriate signals (e.g., electrical signals) that can be delivered to one or more sensors 126, thereby controlling the operation of one or more sensors 126. In some examples, the controller 214 can be configured to convert measurement data received from one or more sensors 126 and / or to transmit the measurement data to the computing system 200.

[0035] The exemplary controller 214 further communicates electrically with the control panel 216 of the material testing machine 102. In some examples, the control panel 216 may include one or more input devices (e.g., buttons, switches, slides, knobs, microphones, dials, and / or other electromechanical input devices). In some examples, the control panel 216 may be used by an operator to directly control the material testing machine 102. In some examples, the controller 214 may be configured to control the material testing machine 102 by converting commands, control inputs, and / or test parameters received via the control panel 216 into appropriate signals (e.g., electrical signals) that can be delivered to the actuator(s) 210 and / or gripping(s) 124.

[0036] The controller 214 is also illustrated as communicating electrically with the network interface 218b of the material testing machine 102. In some examples, the network interface 218b includes hardware, firmware, and / or software for connecting the material testing machine 102 to a complementary workstation network interface 218a of the computing system 200. In some examples, the controller 214 can receive information (e.g., commands) from the computing system 200 through the network interface 218 and / or transmit information (e.g., measurement data from one or more sensors 126) to the computing system 200 through the workstation network interface 218.

[0037] In the example shown in Figure 2, the computing system 200 includes a test workstation 202 and a user interface (UI) 204 interconnected with each other. As shown, the UI 204 may include one or more input devices 206 configured to receive input from the user and one or more output devices 208 configured to provide output to the user.

[0038] In some examples, one or more input devices 206 may include one or more touchscreens, mice, keyboards, buttons, switches, slides, knobs, microphones, dials, and / or other input devices 206. In some examples, one or more output devices 208 may include one or more displays / touchscreens, speakers, lighting, haptic devices, and / or other output devices 208. In some examples, one or more output devices 208 (e.g., display screens) of the UI 204 may output one or more representations of a material testing process 250 configured to allow a user to set up and / or run a test method and / or analyze the test results of the test method. In some examples, one or more input devices 206 of the UI 204 may receive input from a user and send input data representing user input to the test workstation 202.

[0039] In the example in Figure 2, the illustrative test workstation 202 includes a workstation network interface 218a. As shown, one workstation network interface 218a communicates with the network interface 218b of the material tester 102 via cable 106. As shown, the test workstation 202 further includes a workstation network interface 218a that communicates with a network 220 (e.g., the Internet). In the example in Figure 2, the test workstation 202 communicates with a remote interface 230 via network 220 and the workstation network interface 218a. In some examples, the test workstation 202 may also communicate with one or more other test systems, servers, and / or other devices via the network and / or workstation network interface(s) 218a. As shown, the workstation network interface 218a is electrically connected to the common electrical bus 222 of the test workstation 202.

[0040] In some examples, the test workstation can be a computing device. In the example in Figure 2, the test workstation 202 includes a workstation processing circuit 224 connected to a common electric bus 222. In some examples, the workstation processing circuit 224 may comprise one or more processors. In some examples, the workstation processing circuit 224 is configured to process information received from the UI 204, one or more data import devices 108, and / or the material tester 102.

[0041] In some examples, the workstation processing circuit 224 is configured to transmit commands and / or test parameters to the material testing machine 102 (for example, via a network interface(s) 218a). In some examples, the workstation processing circuit 224 is configured to output information to the operator via the UI 204. In some examples, the workstation processing circuit 224 is configured to execute machine-readable instructions stored in the workstation memory circuit 226.

[0042] In the example in Figure 2, the test workstation 202 further includes a workstation memory circuit unit 226 connected to a common electric bus 222. As shown, the workstation memory circuit unit 226 includes a material testing process 250. In some examples, the material testing process 250 includes machine-readable instructions. In some examples, the workstation processing circuit unit 224 is configured to execute the machine-readable instructions of the material testing process 250, communicate with the material testing machine 102 (e.g., the controller 214 of the material testing machine 102), and perform testing of the test specimen 128.

[0043] In some cases, the workstation 202 may be operated using a separate user device, such as a smartphone, tablet computer, or other mobile computing device, configured to communicate with the material testing machine 102.

[0044] In some examples, the test of test specimen 128 is carried out according to a specific test method (and / or the test results are analyzed). In some examples, the test method is defined by parameters in a test file. The test file may contain a collection of data (e.g., stored data) representing one or more parameters (e.g., test parameters, sample / test specimen parameters, analytical parameters, etc.) that define at least a part of the test method. For example, test parameters may include the date the test is performed, test identification information (e.g., number, name, type, description, etc.), target start / end positions of gripping section(s) 124, target start / end positions of crosshead 120, target distance / direction moved by crosshead 120, target speed of crosshead 120, expected test results(s) (e.g., location / type of fracture, distance moved before fracture, force applied before fracture, post-test characteristics of the sample, etc.), time(s) when sensor(s) 126 should perform measurement(s), and / or other matters related to a particular test method. The specimen parameters may include the date the specimen 128 was manufactured / shipped / packaged, identification information of the specimen 128 (e.g., number, name, description, etc.), pre-test characteristics of the specimen 128 (e.g., actual size / dimensions, material type, weight, color, shape, modulus of elasticity, maximum tensile strength, etc.), and / or other information relevant to a particular specimen 128. The analysis parameters may include one or more algorithms that can be used to evaluate the results of the test method (and / or generate additional test results), one or more test result report formats, and / or one or more thresholds and / or threshold ranges (for example, which can be used to make a ruling on the test result to determine whether the specimen 128 passed or failed the test).

[0045] The exemplary test fixture 122 may further include one or more additional sensors 126 for measuring the conditions inside and / or around the test fixture 122, and / or monitoring or measuring the activity of the test fixture 122. For example, the sensor(s) 126 may include: an environmental sensor(s) that measures ambient temperature, ambient humidity, and / or any other conditions(s) around the test fixture 122 that may affect its operation; a temperature sensor that measures the temperature of its components; a voltage sensor that measures motor voltage, power input voltage, and / or power output voltage, and / or other voltages in the test fixture 122, the duty cycle of its components in the test fixture 122, and / or data derived from other voltages; a current sensor that measures motor current, power input current, and / or power output current, and / or other currents in the test fixture 122, the duty cycle of its components, and / or data derived from other currents; a distance sensor and / or proximity sensor that measures the distance a component in the test fixture 122 has traveled (e.g., the distance a grip, crosshead, etc., has traveled); and / or any other type of sensor for obtaining relevant information about the test fixture 122.

[0046] In addition to using sensors to detect the internal and / or surrounding conditions of the test fixture 122, the exemplary processing circuit 224 can monitor other conditions or states of the test fixture 122 and / or the computing system 200. For example, the processing circuit 224 can monitor and / or obtain error codes generated in the material testing system (e.g., codes detected or generated by software), error messages in the material testing system (e.g., messages generated by software in response to problematic user behavior), security information about the material testing system, log data in the material testing system, load string information about load string equipment installed in the material testing system, software version in the material testing system, diagnostic information detected in the material testing system, and / or other arbitrary software detection information.

[0047] In some examples, one or more conditions or states of the test fixture 122 and / or computing system 200 can be detected using a combination of sensors and software.

[0048] Figure 3 shows an exemplary system 300 for providing automated customized product support for a materials testing system. The exemplary system 300 can provide faster, easier, and more relevant support for customized products or a wide variety of other products, while reducing the involvement of customer support personnel for many support tasks.

[0049] The example system 300 includes a support server 302, a query processing server 304, a language model 306, a knowledge base 308, and a knowledge base editor 310.

[0050] System 300 is shown in Figure 3 along with an example material testing system 312, such as the material testing system 100 in Figures 1 and 2. The material testing system 312 can be paired with or otherwise communicate with a user device 314. The example user device 314 allows the user to interface with system 300 to control the material testing system 312, view test results, and / or obtain technical support for operating the material testing system 312.

[0051] Figure 4 shows an exemplary user interface 400 that can be used to implement the user device 314 of Figure 3 and receive user input, including queries related to the material testing system 312. The exemplary user interface 400 is implemented via software, such as a web page interface and / or a dedicated application. The exemplary user interface 400 allows an operator, technician, or any other user to enter queries (for example, via an input field 402) for processing by the query processing server 304.

[0052] In the examples in Figures 3 and 4, the input field 402 receives natural language input, such as conversational question input from the user. Natural language input can be entered into the input field 402 via a keyboard (implemented, for example, by hardware and / or software), voice input to a microphone, and / or any other type of input.

[0053] The user interface 400 further includes an output interface 404 that displays troubleshooting information and / or other information provided by the query processing server 304 and / or the support server 302 in response to a query (for example, an illustrative query 406). As disclosed in more detail below, the troubleshooting information may include troubleshooting tasks, troubleshooting subtasks or steps, resources such as videos, images, documents, and / or links to access such resources.

[0054] In some examples, the user interface 400 allows the user to request support for any of several material testing systems. The user interface 400 may include a selection field that allows the user to select one or more material testing systems to which a given query applies.

[0055] Returning to Figure 3, the exemplary support server 302 receives queries from a user device (e.g., user device 314) for support regarding the material testing system 312. The support server 302 supplements the queries with information that identifies one or more of the identifiable components. In the example of Figure 3, the material testing system 312 can be a customized system having one or more components that are installable and, in some cases, interchangeable with other similar components. For example, the material testing system 312 may be configured to have interchangeable gripping parts that allow the material testing system 312 to apply various levels of gripping force to a test specimen using various operating types (e.g., pneumatic, hydraulic, electric, etc.) and / or provide fixation with fixtures for various types of test specimens and / or various types of tests. At least some components of the material testing system 312 are individually identifiable, whether detachable or integrated with the material testing system 312. In some cases, identifiers for some of the components of the material testing system 312 are identified during manufacturing, installation, and / or calibration and provided to the support server 302. Additionally or alternatively, the support server 302 may communicate with the material testing system 312 to receive and / or update identifiers for one or more components installed in the material testing system 312 (for example, periodically, in response to a query, in response to other types of triggers, etc.).

[0056] In several other examples, the user device 314 can receive identifiers of identifiable components from the material testing system 312 and send these identifiers to the support server 302 in a query along with natural language input. For example, the user device 314 can receive data representing identifiable components installed in the material testing system 312 by scanning a barcode or QR code (registered trademark) or by other means. Exemplary techniques for receiving data are disclosed in U.S. Patent Application Publication 2024 / 0159633, corresponding to U.S. Patent Application No. 18 / 506,694, entitled “MATERIAL TEST SYSTEMS FOR GENERATING STATIC AND DYNAMIC DIAGNOSTIC INFORMATION”. The entire contents of U.S. Patent Application Publication 2024 / 0159633 constitute part of this application by reference. In some cases, information on identifiable components is further supplemented with test file information, test specimen information, test result information, and / or other dynamic information that the user or support server 302 determines to be relevant to the natural language information in the query.

[0057] In further examples, the user device 314 can communicate queries directly to the query processing server 304 and receive responses from the query processing server 304. In some such examples, the support server 302 can provide the user device 314 with information on identifiable components, which is then provided to the query processing server 304 by the user device 314 along with the query. For example, the support server 302 can associate the information on identifiable components with the user account of the user device 314 for retrieval by the user device 314 when the user device 314 logs in and / or submits a query.

[0058] The exemplary query processing server 304 receives queries (e.g., natural language input) and information on identifiable components from the support server 302, generates a response to the query, and sends it to the user device 314 (e.g., directly or via the support server 302). In the example in Figure 3, the query processing server 304 processes the natural language user input and information on identifiable components using a language model 306. The language model 306 can be trained at least partially using information contained in troubleshooting resources related to the material testing system 312 and identifiable components adapted to the material testing system 312. The exemplary language model 306 is a large language model (LLM), which may be a newly trained model or based on an underlying model.

[0059] In the example in Figure 3, the query processing server 304 can be trained, tuned, and / or updated using information from the knowledge base 308. The exemplary knowledge base 308 stores troubleshooting information relating to multiple material testing systems (which may be the subject of technical support requests) and multiple identifiable components adapted to the material testing systems. The exemplary troubleshooting information that can be used to train and / or tune the language model 306 used by the query processing server 304 includes owner manuals, field service manuals, technical documentation, previous support history (e.g., copies of support services provided to date), training materials, and / or any other public, confidential, and / or proprietary information relating to the material testing system 312 and / or identifiable components adapted to the material testing system 312.

[0060] The Knowledge Base Editor 310 provides an interface for inputting troubleshooting information into the Knowledge Base 308 and / or modifying troubleshooting information in the Knowledge Base 308. For example, authorized users, such as users considered to be subject matter experts, can be permitted to add troubleshooting information to the Knowledge Base 308 and / or modify troubleshooting information in the Knowledge Base 308 using the interface provided by the Knowledge Base Editor 310. The Knowledge Base Editor 310 can also provide an interface for enhancing and / or improving the structure of troubleshooting information entered by users. For example, the Knowledge Base Editor 310 may include input for natural language information, material testing system identification information (e.g., model number), and / or identifiable components.

[0061] Figure 5A shows an exemplary user interface 500 that can be provided by the knowledge base editor 310 for receiving user input containing troubleshooting information for modifying the knowledge base 308. The exemplary user interface 500 includes inputs that allow the user to enter troubleshooting task information, which can be used by the language model 306 to correlate the troubleshooting task with one or more material testing systems and / or identifiable components of the material testing systems. In the example in Figure 5A, the user has already entered a first task 502 which may include steps or subtasks, and a specified order in a set of tasks which can be used to perform troubleshooting according to an established troubleshooting process. The exemplary user can further define user types (e.g., roles) that are authorized to perform task 502.

[0062] Interface 500 can be used to allow the user to select to edit Task 502 and / or elements of Task 502. Interface 500 provides structure to Task 502. Knowledge base editor 310 uses the structured data to appropriately tag the troubleshooting information represented by Task 502 for input into knowledge base 308 for consumption by language model 306.

[0063] Figure 5B shows an exemplary user interface 550 that can be provided by the knowledge base editor 310 for receiving user input containing troubleshooting information for modifying the knowledge base 308. The exemplary user interface 550 allows the user to input or upload troubleshooting resources such as documents, videos, images, and / or other resources. The troubleshooting resources can be processed by the language model 306 to further associate the troubleshooting information with the material testing system and / or identifiable components, and / or stored for delivery in association with responses to user queries. The exemplary troubleshooting resources may include owner manuals, field service manuals, technical documents, previous support history (e.g., copies of support services provided to date), training materials, and / or any other public, confidential, and / or proprietary information relating to the material testing system 312 and / or identifiable components adapted to the material testing system 312.

[0064] After the input and submission of task(s) 502 and / or resource(s) 552, the knowledge base editor 310 adds troubleshooting information to the knowledge base 308. The knowledge base editor 310 can process the data entered by the user (e.g., via user interfaces 500, 550) to structure and / or tag the data. Based on the specified tasks and feedback, the language model 306 updates the model vector and / or other aspects to improve the delivery of troubleshooting resource information.

[0065] Users may not recognize the challenges arising from the configuration of component combinations in a material testing system. However, the advantage of training the language model 306 in the knowledge base 308 using information on identifiable components is that the language model 306 can identify statistically likely correlations. In some cases, newly identified statistical correlations identified by the language model can be identified for validation by designated technical support personnel, and this validation may result in the enhancement or reduction of the language model 306.

[0066] The query processing server 304 generates a response to a query by processing natural language user input and information that identifies one or more identifiable components (for example, provided by the support server 302), and by processing troubleshooting information in the language model 306. For example, the LLM portion of the language model 306 can request an appropriate response based on weights set during model training and / or tuning, which can be based on updated troubleshooting information entered via the knowledge base editor 310. The response may include a selection of stored troubleshooting information (e.g., documents, videos, images, web links, etc.) that has been identified, based on the language model 306, as having at least a threshold relevance to the query.

[0067] The query processing server 304 provides the user device 314 that initiated the query with a response and selection of troubleshooting information. In some examples, the query processing server 304 provides the response to the support server 302, which routes the response to the user device 314. The support server 302 may route the query to the query processing server 304 and / or other support resources based on the type and / or content of the received query and / or the customer's status (e.g., service level agreement).

[0068] The support server 302 can be operated by a first service provider (e.g., the manufacturer of the material testing system 312) for managing and maintaining the material testing system 312, while the query processing server 304 and language model 306 are operated by a second service provider. The exemplary knowledge base 308 and knowledge base editor 310 can be operated by the first service provider, the second service provider, a service provider other than the first and second providers, and / or a combination of providers. In yet another example, the system 300 is operated by a single service provider. The exemplary support server 302 communicates queries (e.g., natural language input) and information identifying one or more identifiable components to the query processing server 304. The support server 302, query processing server 304, language model 306, knowledge base 308, and / or knowledge base editor 310 can be implemented using a combination of one or more software components implemented on one or more hardware systems. For example, each of the support server 302, query processing server 304, language model 306, knowledge base 308, and / or knowledge base editor 310 may run on different computing systems or combinations of computing systems, or one or more of the support server 302, query processing server 304, language model 306, knowledge base 308, and / or knowledge base editor 310 may run on the same computing system using server components implemented by software. In some examples, one or more of the support server 302, query processing server 304, language model 306, knowledge base 308, and / or knowledge base editor 310 may be implemented on one or more cloud computing instances that can be combined or separated based on the service provider responsible for each component.

[0069] The illustrative user devices 314 and 316 may be smartphones, tablet computers, desktop computers, laptops, and / or any other type(s) of computing devices(s). User devices 314 and 316 may communicate with the support server 302, the query processing server 304, the knowledge base editor 310, and / or the material testing system 312 using wired or wireless communication, which may include direct communication and / or one or more communication networks. In some examples, user devices 314 and 316 are implemented by a computing system 200 that controls the material testing system 312.

[0070] Figure 6 is a flowchart showing exemplary machine-readable instructions 600 that the support server 302, as illustrated in Figure 3, can execute to supplement user support queries with information that identifies one or more identifiable components of the corresponding material testing system 312. The exemplary instructions 600 are described below with reference to Figure 3.

[0071] In block 602, the support server 302 determines whether natural language user input containing a query about the material testing system has been received. For example, the support server 302 may receive a query from the user device 314 related to the material testing system 312 (e.g., identifying the material testing system 312). If a query is received (block 602), in block 604, the support server 302 seeks information about identifiable components related to the material testing system 312. For example, the support server 302 may use a lookup table and the identifying information in the query to determine the installed components in the material testing system 312 and / or communicate with the identified material testing system 312.

[0072] In block 606, the support server 302 generates a prompt for the query processing server 304 containing information about identifiable components and provides this prompt to the query processing server 304.

[0073] After generating a prompt (block 606), or if no query has been received (block 602), in block 608, the support server 302 determines whether a query response regarding the material testing system 312 has been received. If a query response regarding the material testing system 312 has been received (block 608), in block 610, the support server 302 sends the received response to the user device 314 that initiated the corresponding query. The exemplary instruction 600 then terminates.

[0074] Figure 7 is a flowchart representing exemplary machine-readable instructions 700 that the exemplary knowledge base editor 310 in Figure 3 can execute to modify the knowledge base based on input received through the user interface. The exemplary instructions 700 are described below with reference to Figure 3.

[0075] In block 702, the knowledge base editor 310 generates user interfaces (e.g., user interfaces 500, 550) and sends them to the user device 316 logged into the knowledge base editor 310. The exemplary knowledge base editor 310 may provide multiple different interfaces to facilitate navigation of the interfaces and / or input of desired data by the user. For example, a web page-style interface may allow an operator to navigate to an interface for inputting specific types of troubleshooting information.

[0076] In block 704, the knowledge base editor 310 determines whether troubleshooting information has been received via the provided user interface. If troubleshooting information has been received (block 704), in block 706, the knowledge base editor 310 modifies the knowledge base 308 based on the input received via the user interface. In some examples, the knowledge base editor 310 structures and / or tags the received information for input into the knowledge base 308. Control then returns to block 704 to receive further information.

[0077] If no further information is received (block 704), the example instruction 700 terminates.

[0078] Figure 8 is a flowchart illustrating exemplary machine-readable instructions that the query processing server 304 in Figure 3 can execute to generate responses to user support queries by processing natural language user input using troubleshooting information stored in the knowledge base 308.

[0079] In block 802, the query processing server 304 determines whether the knowledge base 308 has been updated. If the knowledge base 308 has been updated (block 802), in block 804, the query processing server 304 instructs the language model 306 to update based on the updated information in the knowledge base 308.

[0080] After updating the language model 306 (block 804), or if the knowledge base 308 is not updated (block 802), in block 806, the query processing server 304 determines whether a user support query has been received. An example user support query may include identifying information about the natural language input and / or identifiable components of the material testing system 312.

[0081] When a user support query is received (block 806), in block 808, the query processing server 304 analyzes the user support query using the language model 306. This language model 306 is trained in the knowledge base 308 to determine relevant troubleshooting information from the query and identifiable component information. For example, the language model 306 can process natural language input and identifiable component information to determine a statistical correlation between the natural language input and / or identifiable component information and troubleshooting information stored in the knowledge base 308.

[0082] In block 810, the query processing server 304 generates and sends a response (e.g., a natural language response or another user-readable response) containing the identified troubleshooting information. The identified troubleshooting information may include troubleshooting tasks and / or external troubleshooting resources. The query processing server 304 can send the response to the support server 302 and / or directly to the originating user device 314.

[0083] Figure 9 is a block diagram of an exemplary computing system 900 that can implement a computing system 200, user devices 314 and 316 from Figure 3, a support server 302, a query processing server 304, a language model 306, a knowledge base 308, and / or a knowledge base editor 310.

[0084] The exemplary computing device 900 can be a general-purpose computer, laptop computer, tablet computer, mobile device, server, all-in-one computer, and / or any other type of computing device. The computing device 900 in Figure 9 includes a processor 902. The processor 902 can be a general-purpose central processing unit (CPU). In some examples, the processor 902 may include one or more dedicated processing units such as an FPGA, a RISC processor with an ARM core, a graphics processing unit, a digital signal processor, and / or a system-on-chip (SoC). The processor 902 executes machine-readable instructions 904 that can be stored locally in a processor (e.g., an internal cache or SoC), random access memory 906 (or other volatile memory), read-only memory 908 (or other non-volatile memory such as flash memory), and / or a mass storage device 910. The exemplary mass storage device 910 can be a hard drive, a solid storage drive, a hybrid drive, a RAID array, and / or any other mass data storage device. Bus 912 enables communication between processor 902, RAM 906, ROM 908, mass storage device 910, network interface 914, and / or input / output interface 916.

[0085] The illustrated network interface 914 includes hardware, firmware, and / or software for connecting the computing device 900 to a communication network 918 such as the Internet. For example, the network interface 914 may include IEEE 902.X compliant wireless communication hardware and / or wired communication hardware for transmitting and / or receiving communications.

[0086] The illustrative I / O interface 916 in Figure 9 includes hardware, firmware, and / or software that connects one or more input / output devices 920 to the processor 902 to provide input to and / or output from the processor 902. For example, the I / O interface 916 may include a graphics processing unit for interface with a display device, a universal serial bus port for interface with one or more USB-compliant devices, FireWire®, a fieldbus, and / or any other type of interface. Other illustrative I / O devices 920 may include a keyboard, keypad, mouse, trackball, pointing device, microphone, audio speaker, display device, optical media drive, multitouch touchscreen, gesture recognition interface, magnetic media drive, and / or any other type of input and / or output device.

[0087] The computing device 900 can access the non-temporary machine-readable medium 922 via the I / O interface 916 and / or one or more I / O devices 920. Examples of the machine-readable medium 922 in Figure 9 include optical discs (e.g., compact discs (CDs), digital versatile / video discs (DVDs), Blu-ray® discs, etc.), magnetic media (e.g., floppy disks), portable storage media (e.g., portable flash drives, secure digital (SD) cards, etc.), and / or any other type of removable and / or mounted machine-readable medium.

[0088] The method and system can be implemented in hardware, software, and / or a combination of hardware and software. The method and / or system can be implemented centrally in at least one computing system, or distributedly, with different elements distributed across several interconnected computing systems. Any type of computing system or other device adapted to perform the method described herein is suitable. A typical combination of hardware and software may include a general-purpose computing system, along with a program or other code that, once loaded and executed, controls the computing system to perform the method described herein. Another typical embodiment may include an application-specific integrated circuit or chip. Some embodiments may include a non-temporary machine-readable (e.g., computer-readable) medium (e.g., flash drive, optical disk, magnetic storage disk, etc.) which stores one or more lines of machine-executable code, thereby causing a machine to perform a process such as that described herein. As used herein, the term “non-temporary machine-readable medium” includes all types of machine-readable storage media and is defined to exclude propagated signals.

[0089] As used in this application, the terms “circuit” and “circuit section” refer to a physical electronic component (i.e., hardware) and any software and / or firmware ("code") that can constitute the hardware, can be executed by the hardware, and / or can be otherwise associated with the hardware. As used in this application, for example, a particular processor and memory may include a first “circuit” when executing one or more first lines of the code, and a second “circuit” when executing one or more second lines of the code. As used in this application, “and / or” means any one or more items in the list linked by “and / or”. For example, “x and / or y” means any element of the set of three elements {(x), (y), (x,y)}. In other words, “x and / or y” means “one or both of x and y”. As another example, “x, y and / or z” means any element of the seven-element set {(x), (y), (z), (x,y), (x,z), (y,z), (x,y,z)}. In other words, “x, y and / or z” means “one or more of x, y and z.” As used in this application, the term “exemplary” means to serve as an unrestricted example, case, or illustration. As used in this application, the term “for example” means to begin a list of one or more unrestricted examples, cases, or illustrations. As used in this application, whenever a circuit section includes the hardware and code (if any of which are required) necessary to perform a certain function, the circuit section is “operable” to perform that function, regardless of whether the performance of that function is disabled or not (e.g., by user-configurable settings, factory trim, etc.).

[0090] While the Method and / or System has been described with reference to certain specific embodiments, those skilled in the art will understand that various modifications and substitutions can be made without departing from the scope of the Method and / or System. For example, blocks and / or components of the disclosed examples can be combined, divided, rearranged, and / or otherwise modified. In addition, many modifications can be made without departing from the scope of the Disclosure to adapt the teachings of the Disclosure to specific circumstances or materials. Therefore, the Method and / or System is not limited to the specific embodiments disclosed. Instead, the Method and / or System includes all embodiments that fall within the scope of the appended claims, either literally or under the doctrine of equivalents.

Claims

1. A system for providing support for customized material testing systems, A support server configured to supplement a query with information identifying one or more identifiable components of a material testing system associated with the query, wherein the material testing system is configured to perform mechanical testing on a test specimen and to measure the results of said mechanical testing, and the query includes natural language input to the support server. A knowledge base containing troubleshooting information related to multiple material testing systems and multiple identifiable components, A knowledge base editor configured to send a user interface for inputting troubleshooting information and to modify the knowledge base based on input received through the user interface, It is a query processing server, The process involves generating a response to the query by processing the natural language user input, the information identifying one or more of the identifiable components, and the troubleshooting information. To provide the aforementioned response and the selection of troubleshooting information to the user device associated with the query, wherein the selection of troubleshooting information is based on the aforementioned response, A query processing server configured to perform the following actions: A system equipped with these features.

2. The system according to claim 1, wherein the information of the identifiable component includes information that identifies at least one of the following: the type of component of the material testing system, the characteristics of the component, the manufacturing number of the component, the model number of the component, or the batch number of the component.

3. The system according to claim 1, wherein the information of the identifiable components includes a list of the components installed in the material testing system.

4. The system according to claim 1, wherein the query processing server is configured to process the natural language user input using a large-scale language model.

5. The system according to claim 1, wherein the user device includes a smartphone, a tablet computer, or a computer.

6. The system according to claim 1, wherein the support server is configured to communicate with the material testing system to update the list of the plurality of identifiable components in the material testing system stored in the support server.

7. The system according to claim 6, wherein the support server is configured to communicate with the material testing system to update the list in response to the receipt of the query.

8. The system according to claim 1, further comprising the material testing system, wherein the material testing system is configured to perform one or more of the following: a compressive strength test, a tensile strength test, a shear strength test, a bending strength test, a deflection strength test, a tear strength test, a peel strength test, a torsional strength test, or any other compressive or tensile test, or a dynamic test.

9. The system according to claim 1, wherein one or more of the plurality of identifiable components are related to the type of test performed by the material testing system.

10. The system according to claim 1, wherein the troubleshooting information includes one or more of the following: troubleshooting tasks, troubleshooting task steps, informational documents, or web links to informational resources.

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