Abstract: According to some embodiments, a system may include an additive manufacturing platform that provides additive manufacturing capability data. A customer platform, associated with a customer, may transmit an industrial asset item request for an industrial asset item. A digital transaction engine may receive the additive manufacturing capability data and the industrial asset item request. The digital transaction engine may then associate the industrial asset item request with an industrial asset definition file, and, based on the additive manufacturing capability data and the industrial asset definition file, assign the industrial asset item request to the additive manufacturing platform. The assignment of the industrial asset item request may be recorded via a secure, distributed transaction ledger. Responsive to the assignment, the additive manufacturing platform may create the industrial asset item (e.g., via an additive manufacturing printer) and provide the item to the customer.

Abstract: According to some embodiments, a system may facilitate collaborative transaction processing associated with a supply chain having a first entity and a second entity. In particular, a first entity database may store electronic records including information associated with at least a portion of the supply chain, and a first entity communication port may exchange information via a distributed computer system. A first entity computer processor may retrieve from the first entity database the information associated with the at least a portion of the supply chain. A subset of information about the supply chain may be identified by the first entity computer processor as being of interest to the second entity. The identified subset of information about the supply chain may then be recorded via a secure, distributed transaction ledger.

Abstract: According to some embodiments, a system may include an additive manufacturing platform that provides additive manufacturing capability data. A customer platform, associated with a customer, may transmit an industrial asset item request for an industrial asset item. A digital transaction engine may receive the additive manufacturing capability data and the industrial asset item request. The digital transaction engine may then associate the industrial asset item request with an industrial asset definition file, and, based on the additive manufacturing capability data and the industrial asset definition file, assign the industrial asset item request to the additive manufacturing platform. The assignment of the industrial asset item request may be recorded via a secure, distributed transaction ledger. Responsive to the assignment, the additive manufacturing platform may create the industrial asset item (e.g., via an additive manufacturing printer) and provide the item to the customer.

Abstract: According to some embodiments, a system may include an additive manufacturing platform that provides additive manufacturing capability data. A customer platform, associated with a customer, may transmit an industrial asset item request for an industrial asset item. A digital transaction engine may receive the additive manufacturing capability data and the industrial asset item request. The digital transaction engine may then associate the industrial asset item request with an industrial asset definition file, and, based on the additive manufacturing capability data and the industrial asset definition file, assign the industrial asset item request to the additive manufacturing platform. The assignment of the industrial asset item request may be recorded via a secure, distributed transaction ledger. Responsive to the assignment, the additive manufacturing platform may create the industrial asset item (e.g., via an additive manufacturing printer) and provide the item to the customer.

Abstract: According to some embodiments, a system may include an additive manufacturing platform that provides additive manufacturing capability data (e.g., a printer model number, a printer resolution, etc.) to a model customization platform. The model customization platform may receive the additive manufacturing printer capability data and retrieve, from an additive manufacturing model data database, a primary engineering model associated with an industrial asset item. The model customization platform may then create a customized version of the primary engineering model in accordance with the additive manufacturing printer capability data and the primary engineering model. The customized engineering model can then be transmitted to the additive manufacturing platform (e.g., to be printed to create the industrial asset item).

Abstract: According to some embodiments, a system may facilitate collaborative transaction processing associated with a supply chain having a first entity and a second entity. In particular, a first entity database may store electronic records including information associated with at least a portion of the supply chain, and a first entity communication port may exchange information via a distributed computer system. A first entity computer processor may retrieve from the first entity database the information associated with the at least a portion of the supply chain. A subset of information about the supply chain may be identified by the first entity computer processor as being of interest to the second entity. The identified subset of information about the supply chain may then be recorded via a secure, distributed transaction ledger.

Abstract: According to some embodiments, a system may include an additive manufacturing platform that provides additive manufacturing capability data (e.g., a printer model number, a printer resolution, etc.) to a model customization platform. The model customization platform may receive the additive manufacturing printer capability data and retrieve, from an additive manufacturing model data database, a primary engineering model associated with an industrial asset item. The model customization platform may then create a customized version of the primary engineering model in accordance with the additive manufacturing printer capability data and the primary engineering model. The customized engineering model can then be transmitted to the additive manufacturing platform (e.g., to be printed to create the industrial asset item).

Abstract: According to some embodiments, a system may include an additive manufacturing platform that provides additive manufacturing capability data. A customer platform, associated with a customer, may transmit an industrial asset item request for an industrial asset item. A digital transaction engine may receive the additive manufacturing capability data and the industrial asset item request. The digital transaction engine may then associate the industrial asset item request with an industrial asset definition file, and, based on the additive manufacturing capability data and the industrial asset definition file, assign the industrial asset item request to the additive manufacturing platform. The assignment of the industrial asset item request may be recorded via a secure, distributed transaction ledger. Responsive to the assignment, the additive manufacturing platform may create the industrial asset item (e.g., via an additive manufacturing printer) and provide the item to the customer.

Abstract: According to some embodiments, system and methods are provided, comprising a flow module to receive one or more objectives for a flow in the production of an object; a memory for storing program instructions; a flow processor, coupled to the memory, and in communication with the flow module and operative to execute program instructions to: receive a request from a user for a current state of a flow for the object; retrieve metadata and data from the physical world associated with the object; determine a current phase in the flow for the object; select an analytic model to determine the current state of the flow for the object; instantiate a digital twin for the current phase in the flow for the object; execute the selected analytic for the instantiated digital twin; generate a response to the request including the current state of the flow for the object based on the executed analytic; and display the response on a display. Numerous other aspects are provided.

Abstract: An industrial part modeling system may include a digital twin industrial part modeling platform containing a plurality of learning models, each learning model describing characteristics of an industrial part available to be incorporated into an industrial asset. The system may also include an application server platform and a user interface platform to receive an industrial part search or analysis requests from a user. The application server platform may receive information about the industrial part search or analysis request and execute at least one search or analysis algorithm to evaluate learning models in the digital twin industrial part modeling platform. Based on said evaluation, the application server platform may provide an industrial part search or analysis result report to the user. Moreover, the application server platform may automatically arrange for at least one of a search or analysis algorithm and a learning model to be updated based on interaction with the user.

Abstract: An optimum order quantity (OOQ) of the material or component using received data is dynamically determined in real-time. An optimum proposed fulfillment timing for filling open purchase orders of the material or component using the received data is determined. The OOQ and optimum proposed fulfillment timing are rendered to a supply chain owner/materials manager at a graphical electronic display. The OOQ and the optimized proposed fulfillment timing are re-determined as additional data is received and by utilizing the new order quantity.

Abstract: A method of generating an output vector to identify a character-of-interest using a sparse distributed memory (SDM) module. The method includes obtaining a feature vector having a vector address. The feature vector is based on a character-of-interest in an acquired image. The method also includes identifying activated locations from hard locations by determining relative distances between the vector address and the stored vector location addresses. Stored content counters of the activated locations include first and second stored sub-sets of counters. The method also includes combining the counters of the first stored sub-sets of the activated locations using a first summation thread to provide a first combined sub-set of values. The method also includes combining the counters of the second stored sub-sets of the activated locations using a second summation thread to provide a second combined sub-set of values. The first and second summation threads are run in parallel.

Abstract: A system and method for identifying characters using a processor and a sparse distributed memory (SDM) module. The system and method are configured to receive image data relating to an object having a surface with physical markings thereon. The physical markings include characters-of-interest. The system and method are also configured to analyze the image data to convert at least one of the characters-of-interest in the image data into a corresponding feature vector. The system and method are also configured to identify the characters-of-interest using the feature vector and the SDM module. A suggested identity for the characters-of-interest is provided.

Abstract: A system and method for identifying characters-of-interest from markings on a surface of an object. The system includes a vector-generating module configured to receive and analyze an image of the markings to provide a feature vector having a vector address. The system also includes a sparse distributed memory (SDM) module. The SDM module includes hard locations having stored vector location addresses within an address space and stored content counters. The location addresses form multiple concentrated groups within the address space. The concentrated groups are associated with different characters of an identification system. The system also includes an identification module that is configured to identify the character(s)-of-interest using the SDM module.

Abstract: A system and method of processing an acquired image to identify characters-of-interest in the acquired image. The method includes obtaining image data of a surface of an object. The image data includes a plurality of image pixels having corresponding light intensity signals. The light intensity signals are based on whether the corresponding image pixel correlates to a morphological change in the surface of the object. The method also includes determining a line section of the image data. The line section includes one of the character lines and has character image portions. The method also includes analyzing the light intensity signals of the image pixels in the character image portions to determine a common height of the characters-of-interest. The method also includes removing extraneous areas of the character image portions based on the common height of the characters-of-interest to provide trimmed image portions.

Abstract: A method of generating an output vector to identify a character-of-interest using a sparse distributed memory (SDM) module. The method includes obtaining a feature vector having a vector address. The feature vector is based on a character-of-interest in an acquired image. The method also includes identifying activated locations from hard locations by determining relative distances between the vector address and the stored vector location addresses. Stored content counters of the activated locations include first and second stored sub-sets of counters. The method also includes combining the counters of the first stored sub-sets of the activated locations using a first summation thread to provide a first combined sub-set of values. The method also includes combining the counters of the second stored sub-sets of the activated locations using a second summation thread to provide a second combined sub-set of values. The first and second summation threads are run in parallel.

Abstract: A system and method for identifying characters using a processor and a sparse distributed memory (SDM) module. The system and method are configured to receive image data relating to an object having a surface with physical markings thereon. The physical markings include characters-of-interest. The system and method are also configured to analyze the image data to convert at least one of the characters-of-interest in the image data into a corresponding feature vector. The system and method are also configured to identify the characters-of-interest using the feature vector and the SDM module. A suggested identity for the characters-of-interest is provided.

Abstract: A comprehensive method and system is provided for managing bulk and non-bulk material and assets using radio frequency and other asset identification devices, distributed mobile computing systems, centralized data storage environments, and client-server based computing. In particular, a process has been designed and to manage shipment items from businesses and third parties to customer designated locations. Components of this system include electronic asset identification devices, a central data repository, a mobile computing environment and associated software applications supporting a client-server system or n-tiered computer system. The mobile computing environment includes software which enables users to physically locate assets, view asset information, and modify such information to reflect current asset status. This information may then be exchanged and synchronized across the n-tiered computer system.

Abstract: Briefly, in accordance with one or more embodiments, a sensor assembly may measure in a mechanical device and communicate an indication of the measured to a remote device via a wireless link.

Abstract: A system that includes a device is provided in which the device includes a piezoelectric substrate; a sensor layer disposed on the substrate and operable to interact with, or react with, a target species; a first and a second electrode that are spaced from each other and in communication with the substrate; a first detector operable to detect the interaction or the reaction of the sensor layer with the target species based on a change in an optical characteristic of electromagnetic radiation propagated through the substrate; and a second detector operable to acoustically detect the interaction or the reaction of the sensor layer with the target species. Associated methods are provided.