Method for the automated creation of a skill interface, computer program product, and device

US2023280733A1 · US · A1

Patent metadata
FieldValue
Publication numberUS-2023280733-A1
Application numberUS-202018019307-A
CountryUS
Kind codeA1
Filing dateAug 4, 2020
Priority dateAug 4, 2020
Publication dateSep 7, 2023
Grant date

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  1. Title

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  2. Abstract

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  3. Assignees and inventors

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  4. Key dates

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  5. First independent claim

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  6. CPC / IPC classifications

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  7. Citations and related patents

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Abstract

Official abstract text for this publication.

The invention relates to a method in which an information model having state graphs for the individual skills and general machine behaviour or error cases is created for the user in an automated manner. This drastically reduces the engineering effort for the subsequent implementation of skill interfaces and in many cases would make an economically viable implementation possible in the first place.

First claim

Opening claim text (preview).

1 . A method for an automated creation of a skill interface for a production step carried out in a system, the method comprising: detecting all states of the system; creating a general state model consisting of the detected states and relationships between the detected states; transferring the general state model into an information model; defining a start state and an end state of the production step within the general state model, determining all sequences of states from the start state to the end state of a required skill, separating all sequences of method steps that are associated with further skills, separating states for error handling of the required skill. 2 . The method of claim 1 , wherein each state must be activated and passed through at least once in a targeted manner in order to detect the states. 3 . The method of claim 1 , wherein the system is observed over a time period in which each state has been passed through at least once in order to detect the states. 4 . The method of claim 1 , wherein at least two production steps are intended to be identified within the general state model, wherein a sequence of method-steps of a first skill that is also associated with further skills is performed by comparing matches in determined state graphs of the first skill with determined sequence state graph of a second skill, and the state sequence determined in this way is marked and removed from the state graphs. 5 . The method of claim 1 , wherein the start state and the end state of the production step are determined by passing through a skill and identifying the states in a targeted manner. 6 . The method of claim 1 , wherein the information model is formed according to a OPC-UA standard. 7 . A non-transitory computer readable storage medium comprising a set of computer-readable instructions stored thereon for creating a skill interface for a production step, the computer-readable instructions which, when executed by at least one processor cause the at least one processor to: detect all states of a system; create a general state model consisting of the detected states and relationships between the states; transfer the general state model into an information model; define a start state and an end state of the production step within the general state model; define all sequences of states from the start state to the end state of a required skill; remove all sequences of method steps that are associated with further skills; and remove states for error handling of the skill. 8 . The non-transitory computer readable storage medium of claim 7 , wherein each state must be activated and passed through at least once in a targeted manner in order to detect the states. 9 . The non-transitory computer readable storage medium of claim 7 , wherein the system is observed over a time period in which each state has been passed through at least once in order to detect the states. 10 . The non-transitory computer readable storage medium of claim 7 , wherein at least two skills/production steps are identified within the general state model, wherein a sequence of method steps of a first skill that is associated with further skills is performed by comparing matches in determined state graphs of the first skill with determined sequence state graph of a second skill, and the state sequence determined in this way is marked and removed from the state graphs. 11 . The non-transitory computer readable storage medium of claim 7 , wherein the start state and end state of the production step are determined by passing through a skill and identifying the states in a targeted manner. 12 . The non-transitory computer readable storage medium of claim 7 , wherein the information model is formed according to a OPC-UA standard. 13 . (canceled)

Assignees

Inventors

Classifications

  • characterised by program execution, i.e. part program or machine function execution, e.g. selection of a program · CPC title

  • by protocol, e.g. MAP, TOP · CPC title

  • characterised by modeling, simulation of the manufacturing system · CPC title

  • Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS] · CPC title

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Frequently asked questions

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What does patent US2023280733A1 cover?
The invention relates to a method in which an information model having state graphs for the individual skills and general machine behaviour or error cases is created for the user in an automated manner. This drastically reduces the engineering effort for the subsequent implementation of skill interfaces and in many cases would make an economically viable implementation possible in the first place.
Who is the assignee on this patent?
Siemens Ag
What technology area does this patent fall under?
Primary CPC classification G05B19/41885. Mapped technology areas include Physics.
When was this patent published?
Publication date Thu Sep 07 2023 00:00:00 GMT+0000 (Coordinated Universal Time) (A1). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 3 related publications on this page (citations in our corpus or others sharing the same primary CPC).