Abstract: Methods and systems for generating digital threads that connect models and software tools for an interconnected digital engineering and certification ecosystem are provided. In one embodiment, a process for generating a software-code-defined digital thread includes receiving a first model representation of a first model, a second model representation of a second model, and an intent input. Determining, using an artificial intelligence (AI) model, one or more model endpoints in the first and the second model representations. Generating, using a script-generating AI model, a platform orchestration script that accomplishes the intent input by connecting the first model representation and the second model representation, using the model endpoints. Finally, storing the platform orchestration script as the software-code-defined digital thread.

Abstract: Digital model platform that enables the streamlined creation and management of digital twins and physical twins by leveraging external feedback and artificial intelligence (AI) is disclosed. Methods and systems for a model collaboration platform that facilitate the integration of external feedback, whether from physical, virtual, or human sources, into the streamlined design, validation, verification, certification, assembly, operations, and maintenance processes of complex systems. Updated results are output to those external sources, including physical twins, other digital twins or models and simulations, and/or human users. External feedback includes feedback data from physical prototypes and their environment, virtual prototypes, simulations, and subject-matter experts.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for securely certifying products in an ecosystem. In some implementations, a digital platform receives a user request to access digital models. The digital platform determines whether the user is authorized to access the digital models. In response, the digital platform generates a transaction request to send to a location of the digital models, wherein the transaction request comprises data identifying operations to perform using the digital models. The digital platform transmits, to the location of the digital models, the generated transaction request that causes execution of the operations. The digital platform receives data representative of a result of the operations performed. The digital platform provides, to a user interface of the user device, the data representative of the result. The digital platform audits the data related to the transaction request and the data representative of the result.

Abstract: A digital documentation system for preparation of engineering documents utilizing one or more artificial intelligence (AI) algorithms is provided. The system includes a user interface for selecting and populating templates with data, and one or more AI algorithms for creating and recommending templates, and preparing documents based on the recommended templates. The system uses natural language processing and semantic analysis algorithms to understand the content of the templates, documents, and associated engineering data, and to generate and recommend relevant templates to the user based on user prompts. The system also uses machine learning and predictive modeling and decision-tree algorithms to assist with the preparation of documents, by generating suggestions for data fields and values based on the user's previous inputs and the overall context of the document and available engineering data, including model data and metadata from digital models accessed in a zero-trust framework.

Abstract: Digital model platform that enables the streamlined creation and management of digital twins and physical twins by leveraging external feedback and artificial intelligence (AI) is disclosed. Methods and systems for a model collaboration platform that facilitate the integration of external feedback, whether from physical, virtual, or human sources, into the streamlined design, validation, verification, certification, assembly, operations, and maintenance processes of complex systems. Updated results are output to those external sources, including physical twins, other digital twins or models and simulations, and/or human users. External feedback includes feedback data from physical prototypes and their environment, virtual prototypes, simulations, and subject-matter experts.

Abstract: An artificial intelligence (AI) assisted generative digital task fulfillment process within digital model platforms is provided. Disclosed are methods and systems for carrying out digital tasks through generative AI, including tasks related to the streamlined design, validation, verification, certification, assembly, operations, and maintenance processes of complex systems. The method includes receiving access to a context AI model trained on Internet-scale data, receiving a user prompt indicating the digital task, and generating contextual data based on the user prompt using the context AI model, where the contextual data identifies a syntax AI model. The method includes training the syntax AI model to generate a template script having a placeholder variable for a parameter related to the digital task. The method also includes using a parameter substitution process to generate the orchestration script by substituting the variable with a parameter value.

Abstract: A digital documentation system for preparation of engineering documents utilizing one or more artificial intelligence (AI) algorithms is provided. The system includes a user interface for selecting and populating templates with data, and one or more AI algorithms for creating and recommending templates, and preparing documents based on the recommended templates. The system uses natural language processing and semantic analysis algorithms to understand the content of the templates, documents, and associated engineering data, and to generate and recommend relevant templates to the user based on user prompts. The system also uses machine learning and predictive modeling and decision-tree algorithms to assist with the preparation of documents, by generating suggestions for data fields and values based on the user's previous inputs and the overall context of the document and available engineering data, including model data and metadata from digital models accessed in a zero-trust framework.

Abstract: Methods and systems for generating digital threads that connect models and software tools for an interconnected digital engineering and certification ecosystem are provided. In one embodiment, a process for generating a software-code-defined digital thread includes receiving a first model representation of a first engineering model, a second model representation of a second engineering model, and an intent input. Determining, using a machine learning (ML) model, one or more model endpoints in the first and the second model representations. Generating, using a script-generating ML model, a platform orchestration script that accomplishes the intent input by connecting the first model representation and the second model representation, using the one or more model endpoints. Finally, storing the platform orchestration script as the software-code-defined digital thread.

Abstract: Methods and systems for generating a sharable digital thread orchestration script related to an input digital model on a digital platform are provided.

Abstract: A digital documentation system for preparation of engineering documents utilizing one or more artificial intelligence (AI) algorithms is provided. The system includes a user interface for selecting and populating templates with data, and one or more AI algorithms for creating and recommending templates, and preparing documents based on the recommended templates. The system uses natural language processing and semantic analysis algorithms to understand the content of the templates, documents, and associated engineering data, and to generate and recommend relevant templates to the user based on user prompts. The system also uses machine learning and predictive modeling and decision-tree algorithms to assist with the preparation of documents, by generating suggestions for data fields and values based on the user's previous inputs and the overall context of the document and available engineering data, including model data and metadata from digital models accessed in a zero-trust framework.

Abstract: Methods and systems for generating sharable digital model splices of digital models are provided. The method comprises receiving an input digital model having a digital model type; and generating a default model splice based on the digital model type. The default model splice comprises access to a first splice function script that engages a digital tool associated with the digital model type, that enables external access to a digital artifact derived from the input digital model, and that provides an addressable endpoint to the digital artifact without access to an entirety of the input digital model. The method further comprises receiving an input; generating a second splice function script based on the input; generating a sharable digital model splice from the default model splice and comprising access to the second splice function script; and storing the second splice function script for the digital model type.

Abstract: Methods and systems for generating a sharable script related to an input digital model on a digital platform are provided. The method includes receiving a user request indicative of a digital task involving an input digital model, and retrieving a corresponding input digital model file. Then, determining characteristic attributes of the input digital model, where the characteristic attributes include digital artifacts generated from the input digital model file. Then, selecting from a collection of templates, using a machine learning (ML) engine, a template matching the characteristic attributes of the input digital model. The ML engine may be trained on documentations of digital tools integrated into the digital platform, a resource-capability mapping of the digital platform, and sample digital thread orchestration scripts collected through past uses of the digital platform. Finally, the method includes generating the sharable script that implements the digital task, based on the selected template.

Abstract: Methods and systems for generating a sharable script related to an input digital model on a digital platform are provided. The method includes receiving a user request indicative of a digital task involving an input digital model, and retrieving a corresponding input digital model file. Then, determining characteristic attributes of the input digital model, where the characteristic attributes include digital artifacts generated from the input digital model file. Then, selecting from a collection of templates, using a machine learning (ML) engine, a template matching the characteristic attributes of the input digital model. The ML engine may be trained on documentations of digital tools integrated into the digital platform, a resource-capability mapping of the digital platform, and sample digital thread orchestration scripts collected through past uses of the digital platform. Finally, the method includes generating the sharable script that implements the digital task, based on the selected template.

Abstract: Methods and systems for generating a sharable model splice of a digital engineering (DE) model are provided. The method comprises receiving a DE model file in a native file format; extracting model data; storing the model data in a storage area; generating external, commonly-accessible splice functions that enable external access to digital artifacts derived from the model data; and generating the sharable model splice, which comprises access to a selective portion of the digital artifacts, and access to at least one of the splice functions. The splice functions provide addressable API or SDK endpoints that enable access by third-party applications and users to the digital artifacts without access to an entirety of the DE model file and without requiring direct engagement with a DE tool associated with the DE model type. These endpoints also provide a unified programming interface to sharable model splices generated from DE models.

Abstract: Methods and systems for generating a sharable model splice of a digital engineering (DE) model are provided. The method comprises receiving a DE model file in a native file format; extracting model data; storing the model data in a storage area; generating external, commonly-accessible splice functions that enable external access to digital artifacts derived from the model data; and generating the sharable model splice, which comprises access to a selective portion of the digital artifacts, and access to at least one of the splice functions. The splice functions provide addressable API or SDK endpoints that enable access by third-party applications and users to the digital artifacts without access to an entirety of the DE model file and without requiring direct engagement with a DE tool associated with the DE model type. These endpoints also provide a unified programming interface to sharable model splices generated from DE models.

Abstract: Methods and systems for generating digital threads that connect models and software tools for an interconnected digital engineering and certification ecosystem are provided. In one embodiment, a process for generating a software-code-defined digital thread includes receiving a first model representation of a first engineering model, a second model representation of a second engineering model, and an intent input. Determining, using a machine learning (ML) model, one or more model endpoints in the first and the second model representations. Generating, using a script-generating ML model, a platform orchestration script that accomplishes the intent input by connecting the first model representation and the second model representation, using the one or more model endpoints. Finally, storing the platform orchestration script as the software-code-defined digital thread.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for securely certifying products in an ecosystem. In some implementations, a digital platform receives a user request to access digital models. The digital platform determines whether the user is authorized to access the digital models. In response, the digital platform generates a transaction request to send to a location of the digital models, wherein the transaction request comprises data identifying operations to perform using the digital models. The digital platform transmits, to the location of the digital models, the generated transaction request that causes execution of the operations. The digital platform receives data representative of a result of the operations performed. The digital platform provides, to a user interface of the user device, the data representative of the result. The digital platform audits the data related to the transaction request and the data representative of the result.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for securely certifying products in an ecosystem. In some implementations, a digital platform receives a user request to access digital models. The digital platform determines whether the user is authorized to access the digital models. In response, the digital platform generates a transaction request to send to a location of the digital models, wherein the transaction request comprises data identifying operations to perform using the digital models. The digital platform transmits, to the location of the digital models, the generated transaction request that causes execution of the operations. The digital platform receives data representative of a result of the operations performed. The digital platform provides, to a user interface of the user device, the data representative of the result. The digital platform audits the data related to the transaction request and the data representative of the result.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for securely certifying products in an ecosystem. In some implementations, a digital platform receives a user request to access digital models. The digital platform determines whether the user is authorized to access the digital models. In response, the digital platform generates a transaction request to send to a location of the digital models, wherein the transaction request comprises data identifying operations to perform using the digital models. The digital platform transmits, to the location of the digital models, the generated transaction request that causes execution of the operations. The digital platform receives data representative of a result of the operations performed. The digital platform provides, to a user interface of the user device, the data representative of the result. The digital platform audits the data related to the transaction request and the data representative of the result.