A distributed manufacturing network information technology system includes a cloud-based additive manufacturing management platform with a user interface, connectivity facilities, data storage facilities, and monitoring facilities. The distributed manufacturing network information technology system includes a set of applications for enabling the additive manufacturing management platform to manage a set of distributed manufacturing network entities. The distributed manufacturing network information technology system includes an artificial intelligence system configured to learn on a training set of outcomes, parameters, and data collected from the distributed manufacturing network entities to optimize manufacturing and value chain workflows.

A distributed manufacturing network includes a distributed ledger system and an artificial intelligence system. The distributed ledger system is integrated with digital threads of a set of distributed manufacturing network entities for storing information on event, activities and transactions related to the distributed manufacturing network entities. The artificial intelligence system is configured to learn on a training set of outcomes, parameters, and data collected from the distributed manufacturing network entities to optimize manufacturing and value chain workflows.

Physical Internet (PI) dynamic principal interface node (PIN) port selection includes selecting a primary maritime port as a PIN in a routing of freight aboard a sea going vessel from an origin node to a destination node in a PI model and receiving a disruption event in the PI model indicating an inability of the vessel to berth at the primary maritime port. A cluster of alternative PINs is determined in connection with the destination node of the PI model and a routing score computed for each alternative PIN based upon a cost of routing the freight through each alternative PIN. Finally, a new routing is established in the PI model utilizing an optimal alternative PIN in lieu of the selected PIN based upon a corresponding routing score, and a message is transmitted to the vessel to divert to a secondary maritime port associated with the optimal alternative PIN.

Physical Internet (PI) dynamic principal interface node (PIN) port selection includes selecting a primary maritime port as a PIN in a routing of freight aboard a sea going vessel from an origin node to a destination node in a PI model and receiving a disruption event in the PI model indicating an inability of the vessel to berth at the primary maritime port. A cluster of alternative PINs is determined in connection with the destination node of the PI model and a routing score computed for each alternative PIN based upon a cost of routing the freight through each alternative PIN. Finally, a new routing is established in the PI model utilizing an optimal alternative PIN in lieu of the selected PIN based upon a corresponding routing score, and a message is transmitted to the vessel to divert to a secondary maritime port associated with the optimal alternative PIN.

A system and related methods for executing and managing international trades, particularly in goods and commodities, makes use of blockchain- or other security-based architecture. The system architecture is able to be implemented so as to be compliant with regulations and regulatory authority to minimize potential fraud, forgery, or other security breaches which may affect the integrity of the associated trading transactions. The computer-implemented system, programming, and associated methods process data related to all phases of international goods and commodities trades, including drafting, negotiation, and execution of contracts as digitally negotiated instruments or electronic transferable records, as well as electronic bills of lading. The system includes features to limit access, verify and authenticate users, and provides limited access to databases and various templates to facilitate the generation, execution, and management of trading transactions from inception to completion. 224004323v3

A system and related methods for executing and managing international trades, particularly in goods and commodities, makes use of blockchain- or other security-based architecture. The system architecture is able to be implemented so as to be compliant with regulations and regulatory authority to minimize potential fraud, forgery, or other security breaches which may affect the integrity of the associated trading transactions. The computer-implemented system, programming, and associated methods process data related to all phases of international goods and commodities trades, including drafting, negotiation, and execution of contracts as digitally negotiated instruments or electronic transferable records, as well as electronic bills of lading. The system includes features to limit access, verify and authenticate users, and provides limited access to databases and various templates to facilitate the generation, execution, and management of trading transactions from inception to completion. 224004323v3

Provided are systems and methods for determining an estimated time of arrival for one or more vessels based on vessel tracking data, and systems and methods for generating an estimated time of arrival model. This includes providing, at a memory, an estimated time of arrival model and a plurality of port boundaries; receiving, at a processor in communication with the memory, vessel data corresponding to at least one vessel, the vessel data comprising vessel location data and secondary data; receiving, at a network device in communication with the processor, an estimated time of arrival request; in response to the estimated time of arrival request, determining an estimated time of arrival corresponding to at least one vessel based on the vessel data and the estimated time of arrival model; and outputting, at an output device in communication with the processor, the estimated time of arrival for the at least one vessel.

Provided are systems and methods for determining an estimated time of arrival for one or more vessels based on vessel tracking data, and systems and methods for generating an estimated time of arrival model. This includes providing, at a memory, an estimated time of arrival model and a plurality of port boundaries; receiving, at a processor in communication with the memory, vessel data corresponding to at least one vessel, the vessel data comprising vessel location data and secondary data; receiving, at a network device in communication with the processor, an estimated time of arrival request; in response to the estimated time of arrival request, determining an estimated time of arrival corresponding to at least one vessel based on the vessel data and the estimated time of arrival model; and outputting, at an output device in communication with the processor, the estimated time of arrival for the at least one vessel.

A computer-implemented method for complying with customs regulations for overseas shipments. The customs compliance systems and methods rely on current data to timely and accurately submit (or correct and resubmit) an “Importer Security Filing” or “ISF” to a U.S. Customs and Border Protection (“U.S. CBP”) authority. In particular, the present systems retrieve (e.g., using various APIs) and rely on current data from the most accurate or up-to-date sources of such data. Moreover, each ISF record is handled independently, retrieving the current data as needed rather than in sequential, batched requests. As a result, errors and time for processing ISF submissions are reduced because accurate data is more readily and promptly available.

A computer-implemented method for complying with customs regulations for overseas shipments. The customs compliance systems and methods rely on current data to timely and accurately submit (or correct and resubmit) an “Importer Security Filing” or “ISF” to a U.S. Customs and Border Protection (“U.S. CBP”) authority. In particular, the present systems retrieve (e.g., using various APIs) and rely on current data from the most accurate or up-to-date sources of such data. Moreover, each ISF record is handled independently, retrieving the current data as needed rather than in sequential, batched requests. As a result, errors and time for processing ISF submissions are reduced because accurate data is more readily and promptly available.