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EP-4740075-A1 - COMMUNICATING INFORMATION REGARDING AN INDUSTRIAL MACHINE TO AN OPERATOR BY USING A COMMUNICATION ASSISTANT THAT IS SPECIFIC TO OPERATOR CONTEXT

EP4740075A1EP 4740075 A1EP4740075 A1EP 4740075A1EP-4740075-A1

Abstract

A computer provides communication assistance to communicate information regarding an industrial machine to an operator. The computer detects (413) an operator context of the operator from context data that it receives from the industrial machine. The computer has a plurality of data modules are adapted to process (443) a query to obtain a response. The computer activates (423-A, 423-B) at least one data module from the plurality of data modules, according to the detected operator context. When the computer receives (433-1) a question from the operator, it translates (433-2) the question to the query (340-Q) and directs (433-3) the query (340- Q) to one of the activated data modules. The computer also translates (453-1) the response (340-R) to an answer (350-A) and forwards (453-2) the answer (350-A) to the operator.

Inventors

  • SCHOCKAERT, Cédric

Assignees

  • Paul Wurth S.A.

Dates

Publication Date
20260513
Application Date
20240704

Claims (14)

  1. 1. Computer-implemented method (403) to communicate information regarding an industrial machine (100) to an operator (190) of the industrial machine (100), the method (403) being executed by a computer (200), comprising: by a context detector (210), detecting (413) an operator context (210-C) of the operator (190) from context data (210-D) that the context detector (210) receives from the industrial machine (100), wherein the operator context (210-C) is defined by the relation of the operator (190) to the industrial machine (100) and by the function of the operator to control the industrial machine (100); by a task manager (240), activating (423) at least one data module (220-A, 220-B) from a plurality of data modules (220-A, 220-B, 220-C, 220-D), according to the detected operator context (210-C), thereby the computer (200) activating (423) data modules for that the probability of being used is related to the operator context; upon a query interface (230) receiving (433-1) a question from the operator (190), translating (433-2) the question to a query (340-Q) and directing (433-3) the query (340-Q) to one of the previously activated data modules (220-B); by one of the activated data modules (220-B), processing (443) the query (340-Q) to obtain a response (340-R); and translating (453-1) the response (340-R) to an answer (350-A) and forwarding (453-2) the answer (350-A) to the operator (190).
  2. 2. Method according to claim 1, wherein the step activating (423) the at least one data module (220-A, 220-B), comprises any of the following: loading the data module (220-A, 220-B) to the main memory of the computer (200); establishing a data connection to the industrial machine (100) to receive machine data that represents current operation parameters of the industrial machine (100); associating model data with the to-be-activated data module (220-A, 220-B); and instructing the data module to start operating.
  3. 3. Method according to any of claims 1 and 2, wherein the step activating (423) the at least one data module (220-A, 220-B) comprises to communicatively couple a data source to the at least one data module (220-A, 220-B), comprising any of the following: coupling the data module (220-A, 220-B) to a collection of data regarding the past operation of the industrial machine (100) if the data module is adapted to process data from the past; and coupling the data module (220-A, 220-B) to a collection of data regarding the past operation of the industrial machine (100) during a window interval if the data module is adapted to make predictions.
  4. 4. Method according to any of claims 1 to 3, wherein step detecting (413) the operator context (210-C) of the operator (190) by the context detector (210) comprises to receive updated context data (210-D) from the industrial machine (100) for occasions, selected from the following: determining that the operator (190) of the industrial machine has changed to a different person; determining that the operator (190) of the industrial machine has performed a predefined activity with effect to the industrial machine (100); determining that the operator (190) has changed his or her physical location ((A), ( B)) in relation to the industrial machine (100); determining that the operator (190) has escaped the location of the industrial machine (100); determining that the operator (190) wears particular clothing or has changed clothing; and determining that the operator (190) has changed the language of interaction with the operator interface (180) of the industrial machine (100).
  5. 5. Method according to any of claims 1 to 4, wherein the steps translating (433-2) the question (330-Q) to the query (340-Q) and translating (453-1) the response (340-R) to the answer (350-A) are executed by keeping data that presents language statements, and wherein in step directing (433-3) the query (340-Q) to one of the activated data modules (220-B) comprises to direct the query to a data module that processes language statements.
  6. 6. Method according to claim 5, wherein directing (433-3) the query (340-Q) comprises to direct the query to a data module that processes language statements that are selected from the following: language statements in natural language, language statements in artificial language, with the statements coded in alpha-numeric characters, and statements that are derivatives of language statements.
  7. 7. Method according to any of claims 1 to 6, wherein in the steps translating (433-1) the question (330-Q) to the query (340-Q) and translating (453-1) the response (340-R) to the answer (350-A), the computer identifies a domain of the question (330-Q) and provides the answer (350-A) in the same domain.
  8. 8. Method according to any of claims 1 to 7, wherein the context detector (210), in step detecting (413) the operator context (210-C) provides the operator context (210-C) by classifying the context data (210-D).
  9. 9. Method according to any of claims 1 to 8, wherein after receiving (433-1) the question from the operator (190) by the query interface (230), and before translating (433-2) the question to a query (340-Q) by the query interface (230), the method-executing computer checks the question for ambiguity (433-4), wherein for the absence of ambiguity, the computer continues with translating (433-2) the question, and for the presence of ambiguity, the computer performs further steps, selected from the following: (i) modifying (433-5) the question according to operator context, (ii) translating (433-2') the question according to operator context, and (iii) interacting (433-6) with the operator to obtain further details in a follow-up question.
  10. 10. Method according to any of claims 1 to 9, wherein the task manager (240), in step activating (423) at least one data module (220-A, 220-B) from a plurality of data modules (220-A, 220-B, 220-C, 220-D) also processes the state of the machine (100).
  11. 11. Using the method (403) according to claims 1 to 10 in an assistance system to communicate information regarding an industrial machine to an operator of the industrial machine.
  12. 12. A computer program product that, when loaded into a memory of a computer system and executed by at least one processor of the computer system, causes the computer system to perform the steps of a computer-implemented method according to any of the claims 1 to 10.
  13. 13. A computer system comprising a plurality of modules which perform the steps of the computer-implemented method according to any of the claims 1 to 10.
  14. 4. Computer-implemented assistance system (200) - an assistant hereinafter - to communicate information regarding an industrial machine (100) to an operator (190) of the industrial machine (100), the assistant (200) comprising: a context detector (210) that is adapted to detect (413) an operator context (210-C) of the operator (190) from context data (210-D), wherein the context detector (210) receives the context data (210-D) from the industrial machine (100); a plurality of data modules (220-B) that are adapted to process (443) a query (340-Q) to obtain a response (340-R); a task manager (240) that is adapted to activate (423) at least one data module (220-A, 220-B) from the plurality of data modules (220-A, 220-B, 220-C, 220-D), according to the detected operator context (210-C); a query interface (230) that is adapted to receive (433-1) a question from the operator (190), to translate (433-2) the question to the query (340-Q) and to direct (433-3) the query (340-Q) to one of the activated data modules (220-B), wherein the query interface (230) is also adapted to translate (453-1) the response (340-R) to an answer (350-A) and to forward (453-2) the answer (350-A) to the operator (190).

Description

COMMUNICATING INFORMATION REGARDING AN INDUSTRIAL MACHINE TO AN OPERATOR BY USING A COMMUNICATION ASSISTANT THAT IS SPECIFIC TO OPERATOR CONTEXT Technical Field [001] In general, the disclosure relates to the communication between industrial machines and their operators. More in particular, the disclosure describes a computer-implemented communication assistant that supports the communication between machine operators and machines. Background [002] Despite advances in automation, almost every industrial machine requires some interaction with a human operator. Simplified, the machine presents information regarding its internal states to the operator, and the operator reacts accordingly, for example, by controlling the machine. [003] Traditionally, the machine interacts with the operator via a human-machine interface (HMI). The interface would present information visually (on displays or the like). In addition to that, the interface would eventually issue an audible alarm. [004] Industry sees a trend to make the interaction more efficient, for example, by using further communication modalities or by enhancing data. For example, the machine may communicate information to the operator orally (with text-to-speech translation). Such an approach encodes information directly into a human understandable form. It therefore allows the machine to communicate information in a granularity that is most suitable to the cognitive ability of the human operator. Simple alarm sounds would not be abolished, but the machine can communicate information at least by short spoken phrases. For example, the interface would have to identify a particular machine state (such as, for example, a failure state) and would have to compose an audio message by assembling pre-defined spoken language records (e.g., "The temperature rises above a critical level!"). [005] Using "to-speech" technology tailors the information to the operator. For example, the machine would select a natural language that this understood by the operator. [006] There is a further trend to broaden the temporal range of the interaction. For example, the machine may communicate information relating to the present time, but also relating to the future. Both trends are interrelated. The simplified example would lead to "The temperature WILL raise above a critical level IN ONE HOUR FROM NOW". [007] However, there are technical constraints, at least in the following: • Identifying the information to be communicated to the operator is a process that takes time, and this time depends on the nature of the information. For example, raising an alarm based on real-time data is relatively easy and less time-consuming in comparison to predicting potential failure (in the future). • Communicating information to the operator is a process that takes time as well. Signal propagation delays (i.e., data communicated via a transmission network) can be neglected in many cases, but oral communication requires time until a message has been communicated to the operator. Spoken phrases have a certain minimal duration, otherwise they are not understandable for humans. • Enhancing information is a process that takes time as well, for example, by translating between formats (text to speech or the like). [008] In some situations, the constraints may even amplify each other. For example, if the state would be identified as a potential safety hazard to the operator, the corresponding information must reach the attention of the operator as early as possible. [009] There is a need to overcome the constraints, as well as to speed up the communication and to make it more precise. [0010] US 2014/0365222 Al presents a mobile system with speech-based on non-speech- based interfaces for telematics applications. The system processes natural language statements, determines commands to a vehicle and thereby uses context information. Summary [0011] A computer executes a computer-implemented method to communicate information regarding an industrial machine to an operator of the industrial machine. The computer has the following modules: context detector, task manager, and query interface. The computer also has access to a plurality of data modules. [0012] In a context-detecting step, the context detector detects an operator context of the operator from context data that the context detector receives from the industrial machine. The operator context is defined by the relation of the operator to the industrial machine and by the function of the operator to control the industrial machine. [0013] In an activating step, the task manager activates at least one data module from the plurality of data modules, according to the detected operator context. This approach can be advantageous because the non-activated data modules would not consume computation resources (such as power, access to memory, shares in CPU and the like). [0014] Upon the query interface receiving a question from the operator, the interface translat