An autonomous additive manufacturing platform includes sensors positioned in, on, and/or near a part and configured to collect sensor data related to the part. An adaptive intelligence system is configured to receive the sensor data from the sensors. The adaptive intelligence system includes a machine learning system configured to input the sensor data as training data into one or more machine learning models. The machine learning models are configured to transform the sensor data into simulation data. A digital twin system is configured to create a part twin based on the simulation data. The part twin provides for representation of the part and simulation of a possible future state of the part via the simulation data. An artificial intelligence system is configured to execute simulations on the digital twin system. The machine learning models are utilized to make classifications, predictions, and other decisions relating to the part.

An information technology system for a distributed manufacturing network includes an additive manufacturing management platform with an artificial intelligence system configured to learn on a training set of outcomes, parameters, and data collected from a set of distributed manufacturing network entities and execute simulations on digital twins of the set of distributed manufacturing network entities to make classifications, predictions, and optimization-related decisions for the set of distributed manufacturing network entities. The information technology system includes a distributed ledger system integrated with a digital thread and configured to provide unified views of workflow and transaction information to the set of distributed manufacturing network entities.

Systems and methods dynamically assess energy efficiency by obtaining a minimum energy consumption of a system, receiving in a substantially continuous way a measurement of actual energy consumption of the system, and comparing the minimum energy consumption to the measurement of actual energy consumption to calculate a substantially continuous energy performance assessment. The system further provides at least one of a theoretical minimum energy consumption based at least in part on theoretical performance limits of system components, an achievable minimum energy consumption based at least in part on specifications for high energy efficient equivalents of the system components, and the designed minimum energy consumption based at least in part on specifications for the system components.

The technology relates to portable personal monitor device and associated methods. In particular, the technology provides for improving the capability of personal monitor device systems by enabling functions such as two-way communications from the personal monitor; associating possible threats with one or more locations; and dynamically determining safe locations and potential evacuation routes. Also described herein are monitors which improve the detection of possible threats or risks by allowing a base unit to be used with various replacement sensor modules.

A system and method may determine the carbon emissions risk to an institution through its lending and investment activities to a plurality of counterparties by, for example, determining carbon emissions data for a number of counterparties and, for each counterparty, determining the carbon emissions risk to the institution. A system and method may determine the proportion of total capital of a counterparty that is being financed by a bank, and multiply this by a carbon emissions measure for the counterparty. Embodiments may be applied to determine optimal investment strategies for managing an institution's exposures to carbon risk over time. Such measures may be altered or projected using scenarios describing future emissions data.

System and methods for producing verifiable environmental attributes for a transaction on an online platform, by calculating item project emissions for a selected item and item baseline emissions for a substitute item, calculating project and baseline final delivery transport emissions to the user's specified destination, and extracting net emissions reductions based on the baseline and project emissions. The net emissions reductions are communicated to a system for aggregation with net emissions reductions from other transactions, and aggregated net emissions reductions are delivered to an independent system for validation and verification. Ownership of net emissions reductions may be assigned to the platform provider. Emissions may include GHG emissions generated during the product life cycle, including raw materials sourcing, production and manufacturing, supply-chain transport from factory to warehouse/distribution centre or retail store, warehouse and retail handling, customer delivery, product use and disposal and recycling process (end of life).

An industrial plant operation management platform integrating a set of executive digital twins that take data from an intelligent data and networking pipeline to provide role-specific features, including AI-enabled expert agent features and enhanced collaboration features, and salient views of the entities and workflows of an industrial plant operation, thereby enabling executives to monitor and control entities and workflows to an unprecedented degree at appropriate levels of granularity and using familiar taxonomies and decision-making frameworks.

In one aspect, there is disclosed a computer-implemented method that includes extending an existing first data model of an enterprise resource planning system to include a second data model, wherein the first and second data models provide a greenhouse gas emissions model; providing the extended greenhouse gas emissions model to enable a calculation that allocates to the product or the service an amount of greenhouse gas emissions; and causing display of a user interface including the amount of greenhouse gas emissions allocated to the product or the service. Related systems, methods, and articles of manufacture are also disclosed.

A platform for updating one or more properties of one or more digital twins including receiving a request for one or more digital twins; retrieving the one or more digital twins required to fulfill the request from a digital twin datastore; retrieving one or more dynamic models corresponding to one or more properties that are depicted in the one or more digital twins indicated by the request; selecting data sources from a set of available data sources based on the one or more inputs of the one or more dynamic models; obtaining data from selected data sources; determining one or more outputs using the retrieved data as one or more inputs to the one or more dynamic models; and updating the one or more properties of the one or more digital twins based on the one or more outputs of the one or more dynamic models.

A customer may wish to purchase products with a lower associated carbon footprint when shipped, or may wish to know the cost associated with offsetting a product's carbon footprint in order to make informed decisions, while browsing and making purchases online. The computer is faced with the computational challenge of trying to determine a value indicative of the carbon emissions associated with shipping a package, before the package has even shipped. The computation may need to be performed during interactive scenarios, such as while browsing. A system and method are provided in order to present a customer with a carbon emissions indication relating to the shipment of a product without disrupting typical online activity.