Abstract: A system and method is provided that facilitates threat impact characterization. The system may include a replica programmable logic controller (PLC) that corresponds to a production PLC in a production system and that may be configured to operate at an accelerated processing speed that is at least two times faster than a processing speed of the production PLC. The system may also include a data processing system configured to communicate with the replica PLC when executing malware infected PLC firmware and generate a simulation of the production system based on a virtual model of the production system operating at an accelerated processing speed that is at least two times faster than a processing speed of the physical production system. The simulation may include accelerated simulation of the production PLC based on communication with the replica PLC using the malware infected PLC firmware.

Abstract: Graph databases directly relate data items in the data store with edges that represent relationships between the data items. The relationships link the data items together and often permit complex sets of related data items to be retrieved with a single operation. New query systems and techniques for graph databases provide prediction of non-explicit connections between data items that further enhances the efficiency and utility of graph databases, as well as extend their industrial applications.

Abstract: A method of performing failover for programmable logic controllers (PLCs) in an automation environment and controlling a physical system includes an input/output module receiving sensor inputs from field devices and creating a copy of the sensor inputs for a first group of PLC in a first PLC bank. The input/output module transfers the copy the sensor inputs to each PLC in the first group of PLCs and receives processing results from each PLC in the first group of PLCs in response to transferring the copy of the sensor inputs. The input/output module determines whether there are any inconsistencies between the processing results received from each PLC in the first group of PLCs. If there are any inconsistencies between the processing results received from each PLC in the first group of PLCs, a failover control process is initiated by sending a failover control message to a second input/output module.

Abstract: A method for executing a machine learning model with a controller includes a processor within the controller writing input values to a process image within the controller. The term process image refers to a predefined address space within volatile memory of the controller. A co-processor connected to the controller reads the input values from the process image and applies a machine learning model to the input values to generate output values. The co-processor writes output values to the process image and the processor reads those output values from the process image. The process can then execute an application program that utilizes the one or more output values.

Abstract: A system for autonomous generative design in a system having a digital twin graph a requirements distillation tool for receiving requirements documents of a system in human-readable format and importing useful information contained in the requirements documents into the digital twin graph, and a synthesis and analysis tool in communication with the digital twin graph, wherein the synthesis and analysis tool generates a set of design alternatives based on the captured interactions of the user with the design tool and the imported useful information from the requirements documents. The system may include includes a design tool with an observer for capturing interactions of a user with the design tool, In addition to the observer, an insighter in communication with the design tool and with the digital twin graph receives design alternatives from the digital twin graph and present the receive design alternatives to a user via design tool.

Abstract: A model-based human machine interface (HMI) system is provided. The HMI system includes a plurality of output devices each having output capabilities that include at least one unique output capability level and a semantics library that is configured to receive SUC component models each having an output format and data. The semantics library is configured to analyze the data relative to the SUC component models and to transmit each of the SUC component models to one or more of the plurality of output devices. The one or more of the plurality of output devices are selected based on a correlation between the output capabilities of the plurality of output devices and the output format of the SUC component models.

Abstract: Systems (500) and methods (400) for an interactive system for automatic generation, analysis and exploration of composable system of systems based on knowledge graphs. A method (400) includes receiving (405) a scenario (110) and a domain ontology (111); determining (410) structures (132), attributes (133), and capabilities (131) from the domain ontology; generating (415) design alternatives (146) based on the scenario using the structures, attributes, and capabilities; performing (430) an evaluation (159) of the design alternatives based on the scenario; generating (445) an SoS design (300) based on the evaluation; and displaying the SoS design to a user.

Abstract: A method for programmable logic controller (PLC) program randomization, the method comprising an engineering system computer receiving source code corresponding to a PLC program and compiling the source code into a plurality of functionally equivalent intermediate representations of the PLC program. Program structure of the PLC program is randomized during compilation such that each intermediate representation is unique among the plurality of intermediate representations. The engineering system computer transmits the plurality of intermediate representations to one or more PLCs.

Abstract: A system for using digital twins for scalable, model-based machine predictive maintenance comprises a plurality of digital twins and a simulation platform. The plurality of digital twins correspond to plurality of remotely located physical machines. Each respective digital twin comprises: product nameplate data corresponding to a unique physical machine, one or more simulation models, and a database comprising run time log data collected from sensors associated with the unique physical machine. The simulation platform is configured to process simulation models corresponding to the plurality of digital twins using a plurality of multiprocessor computer systems.

Abstract: Graph databases directly relate data items in the data store with edges that represent relationships between the data items. The relationships link the data items together and often permit complex sets of related data items to be retrieved with a single operation. New query systems and techniques for graph databases provide prediction of non-explicit connections between data items that further enhances the efficiency and utility of graph databases, as well as extend their industrial applications.

Abstract: A system for checking security vulnerabilities for automation system design includes a security database, an Internet crawler application, and security service application. The security database stores descriptions of known software vulnerabilities related to an automation system. The Internet crawler application is configured to systematically browse the Internet to find new software vulnerabilities related to the automation system and index the new software vulnerability into the security database. The security service application retrieves, from the security database, potential software vulnerabilities related to a hardware/software configuration of the automation system. The security service application also identifies policies related to the potential vulnerabilities. Each policy describes a potential vulnerability and action to be performed in response to detection of the potential vulnerabilities.

Abstract: A computer-implemented method for generating a deployment for an automated system based on system knowledge includes receiving user inputs comprising engineering documents and records of human-computer interactions and extracting knowledge data from the user inputs. A knowledge representation is generated based at least in part of the knowledge data. This knowledge representation comprises facts and rules related to the automated system. An automated reasoning engine is used to generate a set of actions executable by an automation engineering system based on the knowledge representation. An automated system deployment is generated based at least in part on the set of actions and the automated system deployment is implemented on the automated system.

Abstract: A method and system is disclosed for modeling product data related to lifecycle of a product, including an application program interface configured to connect with one or more data sources of different types via one or more computer based product management tools. A digital twin graph is constructed to include a plurality of graphical models of product data with related nodes inter-linked by edges via a linking algorithm. Models of the digital twin graph include an ontological model having nodes of ontological information related to the product data, an instance model having instance nodes related to the product data, and a probabilistic model having conditional probability distribution nodes from which causal and predictive reasoning information is generated.

Abstract: A system for managing a plurality of digital twins using a graph-based structure, the system includes one or more databases storing a digital twin graph comprising a plurality of subgraphs. Each sub-graph comprises a plurality of nodes associated with a distinct physical object. The system further includes one or more sensor interfaces that are configured to receive data corresponding to one or more remote physical objects. Additionally, the system includes a computing system which is configured to modify the plurality of sub-graphs and edge connections between the plurality of sub-graphs based on the data received via the one or more sensor interfaces.

Abstract: Methods and systems for dynamic network link prediction include generating a dynamic graph embedding model for capturing temporal patterns of dynamic graphs, each of the graphs being an evolved representation of the dynamic network over time. The dynamic graph embedding model is configured as a neural network including nonlinear layers that learn structural patterns in the dynamic network. A dynamic graph embedding learning by the embedding model is achieved by optimizing a loss function that includes a weighting matrix for weighting reconstruction of observed edges higher than unobserved links. Graph edges representing network links at a future time step are predicted based on parameters of the neural network tuned by optimizing the loss function. dynamic graph representation learning that includes receiving, by a processing device, graphs, each of the graphs having a known graph link between two vertices, each of the graphs being associated with one of a plurality of previous time steps.

Abstract: A method of performing failover for programmable logic controllers (PLCs) in an automation environment and controlling a physical system includes an input/output module receiving sensor inputs from field devices and creating a copy of the sensor inputs for a first group of PLC in a first PLC bank. The input/output module transfers the copy the sensor inputs to each PLC in the first group of PLCs and receives processing results from each PLC in the first group of PLCs in response to transferring the copy of the sensor inputs. The input/output module determines whether there are any inconsistencies between the processing results received from each PLC in the first group of PLCs. If there are any inconsistencies between the processing results received from each PLC in the first group of PLCs, a failover control process is initiated by sending a failover control message to a second input/output module.

Abstract: A method of performing cognitive engineering comprises extracting human knowledge from at least one user tool, receiving system information from a cyber-physical system (CPS), organizing the human knowledge and the received system information into a digital twin graph (DTG), performing one or more machine learning techniques on the DTG to generate an engineering option relating to the CPS, and providing the generated engineering option to a user in the at least one user tool. The method may include recording a plurality of user actions in the at least one user tool, storing the plurality of user actions in chronological order to create a series of user actions, and storing historical data relating a plurality of stored series of user actions.

Abstract: A system for interacting with humans in an automation environment includes an automation system machine, one or more processors and a non-transitory, computer-readable storage medium in operable communication with the processors. The computer-readable storage medium comprises one or more programming instructions that, when executed, cause the processors to select a human from a plurality of humans working in the automation environment; retrieve information related to the human using a human programming interface (HPI); and perform one or more actions with the automation system machine based on the information related to the human.

Abstract: A computer-implemented method for quantifying assurance of a software system includes collecting artifacts of the software system generated during phases of the software system's engineering lifecycle. A graph of graphs (GoG) is constructed encoding the artifacts. Each subgraph in the GoG is a semantic network corresponding to a distinct assurance requirement. The GoG is used to calculate a component assurance value for each software component for each distinct assurance requirement. A system assurance value is calculated based on the component assurance values. An architectural view of the software system is presented showing at least one of the component assurance values and the system assurance values.

Abstract: A system and method is provided that facilitates threat impact characterization. The system may include a replica programmable logic controller (PLC) that corresponds to a production PLC in a production system and that may be configured to operate at an accelerated processing speed that is at least two times faster than a processing speed of the production PLC. The system may also include a data processing system configured to communicate with the replica PLC when executing malware infected PLC firmware and generate a simulation of the production system based on a virtual model of the production system operating at an accelerated processing speed that is at least two times faster than a processing speed of the physical production system. The simulation may include accelerated simulation of the production PLC based on communication with the replica PLC using the malware infected PLC firmware.