Abstract: A tool, method and system for automatically managing risks including a processor configured to select an input characteristic, called a target characteristic, the contribution of which in the tolerance chain is greater than a predetermined contribution threshold, replace the value of the target characteristic with a test value, determine an output statistical distribution according to each test value, measure the portion of lack of compliance with the tolerances that are associated with the output requirements, evaluate a first indicator of the impact of the risk of lack of compliance with tolerances associated with the output requirements according to each test value, evaluate a second indicator of severity of the risk representing weighting of the first indicator of the impact of the risk with a probability of occurrence of the test value, and define a set of sorting criteria which are graduated on the basis of the first and second indicators.

Abstract: A system and method for using the system comprising a head mounted device (HMD), a remote maintenance server (RMS), and a control section operable to identify the system under test (SUT) using an image recognition function, to identify a plurality of subsystems (PLoS) within the SUT in a data library, to create three dimensional models of the PLoS and displaying the same on a visual interface of the HMD using an augmented reality function, to connect to the RMS using an encryption algorithm via streaming video or images sent to the RMS, to collect SUT data and external (to the SUT) sensor data, to conduct a prognostics and/or health, maintenance, and/or management (HMM) service on the collected data to determine system health and projected health of the SUT and/or PLoS, to authenticate remote user access to the RMS, to update the data library, and to insert a plurality of (HMM) designators on the visual interface.

Abstract: A system and method for using the system comprising a head mounted device (HMD), a remote maintenance server (RMS), and a control section operable to identify the system under test (SUT) using an image recognition function, to identify a plurality of subsystems (PLoS) within the SUT in a data library, to create three dimensional models of the PLoS and displaying the same on a visual interface of the HMD using an augmented reality function, to connect to the RMS using an encryption algorithm via streaming video or images sent to the RMS, to collect SUT data and external (to the SUT) sensor data, to conduct a prognostics and/or health, maintenance, and/or management (HMM) service on the collected data to determine system health and projected health of the SUT and/or PLoS, to authenticate remote user access to the RMS, to update the data library, and to insert a plurality of (HMM) designators on the visual interface.

Abstract: A system and method for using the system comprising a head mounted device (HMD), a remote maintenance server (RMS), and a control section operable to identify the system under test (SUT) using an image recognition function, to identify a plurality of subsystems (PLoS) within the SUT in a data library, to create three dimensional models of the PLoS and displaying the same on a visual interface of the HMD using an augmented reality function, to connect to the RMS using an encryption algorithm via streaming video or images sent to the RMS, to collect SUT data and external (to the SUT) sensor data, to conduct a prognostics and/or health, maintenance, and/or management (HMM) service on the collected data to determine system health and projected health of the SUT and/or PLoS, to authenticate remote user access to the RMS, to update the data library, and to insert a plurality of (HMM) designators on the visual interface.

Abstract: Secured remote maintenance, configuration management, and systems engineering apparatuses and methods including wearable augmented reality (AR) interface systems are provided. Embodiments can support secure and remote configuration setting changes (CSC) to a system or subsystem of interest (SSoI) using a head mounted device (HMD), a camera, a visual interface section, and a processing section including a plurality of processing instructions operable to operate a command input (CI) interface using one or more user command input CIs (e.g. voice or motion/gesture input recognition) using a secure user authentication systems. HMD machine vision and pattern recognition systems visually identify a SSoI, displaying a 3D model(s) of the SSoI on the HMD's visual interface using the AR interface system, obtaining a plurality of SSoI data, and displaying one or more of the SSoI data in relation to the 3D model on the HMD visual interface to support various tasks including CI directed CSCs.

Abstract: A system and method for using the system comprising a head mounted device (HMD), a remote maintenance server (RMS), and a control section operable to identify the system under test (SUT) using an image recognition function, to identify a plurality of subsystems (PLoS) within the SUT in a data library, to create three dimensional models of the PLoS and displaying the same on a visual interface of the HMD using an augmented reality function, to connect to the RMS using an encryption algorithm via streaming video or images sent to the RMS, to collect SUT data and external (to the SUT) sensor data, to conduct a prognostics and/or health, maintenance, and/or management (HMM) service on the collected data to determine system health and projected health of the SUT and/or PLoS, to authenticate remote user access to the RMS, to update the data library, and to insert a plurality of (HMM) designators on the visual interface.

Abstract: A method, apparatus and computer program product for modeling the non-linear structural response of a component. The non-linear structural response is modeled using a two-step global-local finite element analysis method, which employs a linear global analysis step, a linear intermediate analysis step and a non-linear local analysis step. The boundary conditions applied in the intermediate step are derived in part from the linear global analysis and the boundary conditions applied in the local analysis are derived in part from the global and intermediate analyses.

Abstract: Secured remote maintenance, configuration management, and systems engineering apparatuses and methods including wearable augmented reality (AR) interface systems are provided. Embodiments can support secure and remote configuration setting changes (CSC) to a system or subsystem of interest (SSoI) using a head mounted device (HMD), a camera, a visual interface section, and a processing section including a plurality of processing instructions operable to operate a command input (CI) interface using one or more user command input CIs (e.g. voice or motion/gesture input recognition) using a secure user authentication systems. HMD machine vision and pattern recognition systems visually identify a SSoI, displaying a 3D model(s) of the SSoI on the HMD's visual interface using the AR interface system, obtaining a plurality of SSoI data, and displaying one or more of the SSoI data in relation to the 3D model on the HMD visual interface to support various tasks including CI directed CSCs.

Abstract: A method, apparatus and computer program product is disclosed for determining the strain induced at a selected point in a stiffened panel structure in response to a load, taking into account one or more out of plane (OOP) effects.

Abstract: A method, apparatus and computer program product for modeling the non-linear structural response of a component. The non-linear structural response is modeled using a two-step global-local finite element analysis method, which employs a linear global analysis step, a linear intermediate analysis step and a non-linear local analysis step. The boundary conditions applied in the intermediate step are derived in part from the linear global analysis and the boundary conditions applied in the local analysis are derived in part from the global and intermediate analyses.

Abstract: A method, apparatus and computer program product is disclosed for determining the strain induced at a selected point in a stiffened panel structure in response to a load, taking into account one or more out of plane (OOP) effects.