Adaptive additive manufacturing for value chain networks

A distributed manufacturing network comprising:

• an additive manufacturing management platform configured to manage process and production workflows for a set of distributed manufacturing network entities in a distributed manufacturing environment including at least one of:
• an additive manufacturing unit, a manufacturing node, or another type of manufacturing unit;
• an artificial intelligence system configured to train a set of machine-learned models using learn on a training set of outcomes, parameters, and data collected from the set of distributed manufacturing network entities;
• a digital twin system configured to build manufacturing digital twins of the set of distributed manufacturing network entities and an environment digital twin based on the distributed manufacturing environment and the trained set of machine-learned models,
• wherein each manufacturing digital twin is configured to provide a substantially real-time representation of a corresponding distributed manufacturing network entity through data from one or more sensors positioned in, on, or near the corresponding distributed manufacturing network entity;
• a control system configured to adjust the data and one or more parameters collected from the set of distributed manufacturing network entities in real time;
• wherein each manufacturing digital twin is configured to include a set of supported manufacturing capabilities, including at least one of:
• a manufacturing type, a material selection, a material utilization, a throughput, or an energy utilization, and
• wherein the artificial intelligence system is configured to generate an order fulfillment option by executing a simulation using the manufacturing digital twins and the environment digital twin, wherein the order fulfillment option includes an impact on the distributed manufacturing environment;
• a distributed ledger configured to store details of a set of customer orders, wherein each of a subset of the set of customer orders includes a corresponding digital thread including more than one instruction set to facilitate manufacturing of a component of a corresponding customer order using a distinct form of additive manufacturing equipment, or a hybrid combination of manufacturing equipment;
• and
• a job management system configured to receive a new customer order, wherein the new customer order includes at least one digital thread,
• wherein the artificial intelligence system generates a set of order fulfillment options by executing a set of simulations, the set of simulations including simulations of alternative scheduling sequences based on the more than one instruction set, across the set of distributed manufacturing network entities and the distributed manufacturing environment, and
• wherein the additive manufacturing management platform schedules manufacturing of a component of the new customer order based on the new customer order and the generated set of order fulfillment options and manufactures the component of the new customer order based on at least one of the manufacturing schedules.

A method for managing a distributed manufacturing network, the method comprising:

• receiving, by a processor executing an additive manufacturing management platform, production process data and production workflow data from a set of distributed manufacturing network entities including at least one of an additive manufacturing unit or a manufacturing node;
• training, by a processor executing an artificial intelligence system, machine-learned models for each of the set of distributed manufacturing network entities and the distributed manufacturing network, using a training set of parameters and data collected from the set of distributed manufacturing network entities and corresponding outcomes;
• creating a set of manufacturing digital twins, each of the set of manufacturing digital twins corresponding to one of the set of distributed manufacturing network entities, and an environment digital twin for the distributed manufacturing network using the machine learned models,
• wherein each of the set of manufacturing digital twins is configured to include a capacity and a set of supported manufacturing capabilities, including at least one of:
• a manufacturing type, a material selection, or a throughput, and
• wherein each of the set of manufacturing digital twins is configured to provide a substantially real-time representation of the corresponding one of the set of distributed manufacturing network entities through data from one or more sensors positioned in, on, or near the corresponding one of the set of distributed manufacturing network entities,
• receiving a customer manufacturing order, wherein the customer manufacturing order is part of a digital thread in a distributed ledger, wherein the digital thread includes more than one instruction set for manufacturing a component of the customer manufacturing order, each instruction set is configured to facilitate manufacturing of the component using a distinct form of additive manufacturing equipment, or a hybrid combination of manufacturing equipment;
• updating each of the set of manufacturing digital twins and the environment digital twin based on inventory and real-time data collected from the set of distributed manufacturing network entities;
• generating a set of manufacturing options by simulating different manufacturing strategies for fulfilling the customer manufacturing order using the set of manufacturing digital twins and the environment digital twin, including simulating manufacturing strategies based on the more than one instruction set of the digital thread;
• coordinating manufacture of the component of the customer manufacturing order across the distributed manufacturing network;
• scheduling the manufacture of the component of the customer manufacturing order based on the set of generated manufacturing options and their respective impacts on the distributed manufacturing network and a set of existing customer orders;
• adjusting the data and one or more parameters collected from the set of distributed manufacturing network entities in real time;
• and
• manufacturing the component of the customer manufacturing order based on the scheduled manufacturing of the component.