Various embodiments of the teachings herein include a method for building a graph-based industrial flow model. The method may comprise: importing a set of entities based on an industrial flow including a user-defined entity and a system-defined entity; querying the model for the user-defined entity, and if found, obtaining a connection of the user-defined entity, otherwise generating a new implementation layer; querying the model for an implementation layer of the user-defined entity, and if found, obtaining a connection of the implementation layer of the user-defined entity, otherwise generating a new implementation layer; querying the model for the system-defined entity, and if the system-defined entity is found, obtaining a connection of the system-defined entity, otherwise generating a new implementation layer; and iteratively performing the above queries until a final graph-based model for the industrial flow results.

Various embodiments described herein relate to management of industrial process optimization related to batch operations. In this regard, an optimization request to optimize an industrial process that produces an industrial process product is received. In response to the optimization request, product spent characteristics for one or more blending components of a batch operation subprocess are determined. Also in response to the optimization request, demand data for one or more feed products associated with the one or more blending components is updated based on the product spent characteristics and inventory data indicative of an inventory level for the one or more feed products. Furthermore, a control signal configured based on the demand data is transmitted to a controller configured for optimization associated with the industrial process that produces the industrial process product.

Methods and In an aspect a method of generating an instantaneous quote of any part without toolpathing, the method includes receiving, using a computing device, a geometric model of a part, constructing, using the computing device, at least a rotation-invariant feature as a function of the geometric model, predicting, using the computing device, a manufacturing time as a function of the at least a rotation-invariant feature and a manufacturing time machine learning model, selecting, using the computing device, a stock as a function of the at least a rotation-invariant and a stock selection machine learning model feature, and estimating, using the computing device, a quote as a function of the manufacturing time and the stock.

A system and method for making made-to-order architectural millwork of custom dimensions; including the design of wood joints and a system for deploying them within the overall structural design of individual architectural millwork units, as well as methods for online design and ordering, automated writing of machine code, robotic part preparation, and simplified on-site installation. With the automation and generation of digital code for manufacturing custom architectural components, this method makes the formation of distributed manufacturing centers possible. Through this method and with minimum re-tooling and/or training, these centers are able to produce custom millwork more efficiently and effectively than traditional custom millwork woodshops.

A method to simulate operations of a manufacture plant comprising a plurality of machines, the method including receiving a capacity function and an elapsed time function associated with a first machine of the plurality of machines, wherein the capacity function and elapsed time function is defined by one or more parameters characterizing the first machine, receiving a record of historical production data associated with the first machine, calculating, based on the capacity function and the record of historical production data, an augmented capacity function and an augmented elapsed time function that is defined by the one or more parameters and a quantity relating to parts waiting for processing (WIP), and simulating the operations of the plant based on the augmented capacity function and augmented elapsed time function.

The present disclosure describes transaction-enabling systems and methods. A system can include a facility including a core task including a customer relevant output and a controller. The controller may include a facility description circuit to interpret a plurality of historical facility parameter values and corresponding facility outcome values and a facility prediction circuit to operate an adaptive learning system, wherein the adaptive learning system is configured to train a facility production predictor in response to the historical facility parameter values and the corresponding outcome values. The facility description circuit also interprets a plurality of present state facility parameter values, wherein the trained facility production predictor determines a customer contact indicator in response to the plurality of present state facility parameter values and a customer notification circuit provides a notification to a customer in response.

Systems and methods for data collection for an industrial heating process are disclosed. The system according to one embodiment can include a plurality of data collectors, including a swarm of self-organized data collector members, wherein the swarm of self-organized data collector members organize to enhance data collection based on at least one of capabilities and conditions of the data collector members of the swarm, and wherein the plurality of data collectors is coupled to a plurality of input channels for acquiring collected data relating to the industrial heating process, and a data acquisition and analysis circuit for receiving the collected data via the plurality of input channels and structured to analyze the received collected data using a neural network to monitor a plurality of conditions relating to the industrial heating process.

Various aspects of the disclosure relate to a virtual assistant factory that supports back office operations within a computing system. Various internal services (e.g., banking services, user management services, and the like) may be accessible to external application via an application programming interface. In some cases, a virtual assistant factory computing platform may expose services that call on and/or are tied to various back office computing operations. The virtual assistant factory platform may spin up and host robots, controls, and/or processes that may supplement computing operations and other associated back office operations. The application interface may call API functions that may cause the virtual assistant factory to spin up a virtual assistant to perform various functions and interact with both the user and the appropriate back office operations and/or third-party computing systems.

Apparatuses and methods of operating the same are described. An apparatus including a display, an input device, and a processing device coupled to the display and the input device. The processing device may send an output to the display. The output may include a graphical object associated with a first step of a user-implemented procedure. The processing device may receive an input from the input device. The input may indicate a progress on an execution of the first step by an operator. The processing device may determine whether the input indicates that the operator has completed the first step. The processing device may determine whether the first step is a final step in the user-implemented procedure. The processing device may identify a second step in the user-implemented procedure when the input indicates that the operator has completed the first step and the first step is not a final step.

Method, apparatus and computer program product for detecting vulnerability in an industrial control system, predicting maintenance in an industrial control system, and defining authorization rules for peripheral devices based on peripheral device categorization are described herein.