A system optimizes the organization of components for the manufacture of wood products. The system includes memory devices and processing devices operatively coupled to the memory device, wherein the one or more processing devices are configured to execute computer-readable computer program code to receive a plurality of job orders for distinct wood products having varying components; optimize cutting of all components for the plurality of job orders to minimize waste of source materials, thereby resulting in a plurality of components for the plurality of job orders; track each component electronically in order to identify each component at a final cutting machine location; and affix a unique indicator on each component indicating both a receptacle and a receptacle portion corresponding to each component, thereby optimizing organization of all the components by at least one of job, distance from machine to receptacle, and distance from receptacle to assembly location.

Techniques for manufacturing optimization using a multi-tenant machine learning platform are disclosed. A method for manufacturing optimization includes: obtaining physical sensor data, by a manufacturing device associated with a tenant of a multi-tenant machine learning platform; determining, by a machine learning spoke system associated with the tenant, a machine learning parameter based on at least the physical sensor data; preventing exposure of the first physical sensor data of the first manufacturing device to any other tenant of the multi-tenant machine learning platform; transmitting the machine learning parameter from the machine learning spoke system to a machine learning hub system of the multi-tenant machine learning platform; and updating, by the machine learning hub system, a multi-tenant machine learning model based at least on the machine learning parameter.

A system for monitoring cutting devices in a packaging production line having a line for supplying a material to be cut, an area of a predetermined type of cutting device, and a packaging output line is provided. The system includes means for counting cutting actions of the cutting device, configured to provide a time series of cutting action counting data, a video camera to frame an area of the output line, the video camera configured to provide video data of packaging elements in the output line, first code means, configured to run, on a computer, a first algorithm for recognizing cutting defects starting from video data, the first algorithm providing defect recognition data, and second code means, configured to run, on the computer, a trained expert algorithm to predict cutting performance degradation based on historical defect recognition data, time series of cutting action counting data, and type of cutting device.

A method includes obtaining data associated with operation of a model-based industrial process controller. The method also includes identifying at least one estimated impact of at least one operational problem of the industrial process controller, where each estimated impact is expressed in terms of a lost opportunity associated with operation of the industrial process controller. The method further includes presenting the at least one estimated impact to a user. The at least one estimated impact could include impacts associated with noise or variance in process variables used by the industrial process controller, misconfiguration of an optimizer in the industrial process controller, one or more limits on one or more process variables, a quality of at least one model used by the industrial process controller, a quality of one or more inferred properties used by the industrial process controller, or one or more process variables being dropped from use by the industrial process controller.

A method of designing and manufacturing a replica composite object based on an original object. The method identifies the structure and physical properties of an original object. Base materials, bodies, and structural templates, each of which includes associated physical properties, are utilized to generate a 3-dimensional model. The 3-dimensional model is discretized and tested to determine if the selected combination of base materials and bodies have physical properties that substantially equal the physical properties of the original object. If the physical properties do not equate, the 3-dimensional model is optimized by adjusting the combination of base materials, bodies, and structural templates. When the difference between the measured physical properties of the 3-dimensional model and the identified physical properties of the original object is less than a tolerance value, the method instructs an additive manufacturing system to generate a replica composite object based on the original object.

A supply chain model generation system independently uses a business entity code and an item code representing an item related to a transaction in result information on a supply chain operation of a plurality of business entities; transaction information is extracted from the result information and a transaction time series information table is generated; a relationship in the transaction time series information table in each business entity is analyzed and a virtual business entity code on a supply side and a virtual business entity code on a demand side are assigned for each business entity code; and further a logical model information table where a virtual item code is assigned with respect to an item code related to the transaction of a business entity of the virtual business entity code on the supply side and a business entity of the virtual business entity code on the demand side is generated.

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.

The invention provides a decision-making method of comprehensive alumina production indexes based on a multi-scale deep convolutional network. The method mainly consists of several sub-models: a multi-scale deep splicing convolutional neural network prediction sub-model reflecting the influence of bottom-layer production process indexes on the comprehensive alumina production indexes, a full connecting neural network prediction sub-model reflecting the influence of upper-layer dispatching indexes on the comprehensive alumina production indexes, a full connecting neural network prediction sub-model reflecting the influence of the comprehensive alumina production indexes at a past time on current comprehensive alumina production indexes, and a multi-scale information neural network integrated model for collaborative optimization of sub-model parameters. According to the method, through an integrated prediction model structure, a memory capacity of a superficial-layer network and a feature extraction capacity of a deep-layer network, a precise decision-making for the comprehensive alumina production indexes is realized.

An apparatus for manufacturing a three-dimensional article by additive manufacturing includes a processor and an information storage device storing software instructions. In response to execution by the processor, the software instructions cause the apparatus to: receive initial data defining the three-dimensional article having an outer surface, define a shell having the outer surface of the three-dimensional article and an opposing inner surface that defines an inner cavity, define a transition zone between the inner surface of the shell and a boundary that is inside the inner cavity and generally follows the inner surface of the shell, define a lattice of arrayed unit cells that fill the inside of the boundary, the lattice is defined by connected lattice segments, and define transition segments that couple the lattice to the inner surface of the shell.

An information technology system for supporting additive manufacturing and value chain workflows includes a cloud-based metal additive manufacturing management platform including an artificial intelligence system configured to learn on a training set of outcomes, parameters, and data collected from one or more additive manufacturing nodes to optimize additive manufacturing and value chain processes and workflows. The information technology system includes a distributed ledger system configured to store data related to the manufacturing nodes.