Computer implemented method, system and computer program product for simulating the behavior of a woven fabric at yarn level. The method comprises: retrieving the layout of warp yarns (1), weft yarns (2) and yarn crossing nodes (3); describing each yarn crossing node (3) by a 3D position coordinate (x) and two sliding coordinates, warp sliding coordinate (u) and weft sliding coordinate (v) representing the sliding of warp (1) and weft (2) yarns; measuring forces on each yarn crossing node (3) based on a force model, the forces being measured on both the 3D position coordinate (x) and the sliding coordinates (u, y); calculating the movement of each yarn crossing node (3) using equations of motion derived using the Lagrange-Euler equations, and numerically integrated over time, wherein the equations of motion account for the mass density distributed uniformly along yarns, as well as the measured forces and boundary conditions.

A system allows a user to select designs for apparel and preview these designs before manufacture. The previews provide photorealistic visualizations in two or three dimensions, and can be presented on a computer display, projected on a screen, or presented in virtual reality (e.g., via headset), or augmented reality. The system can also include a projection system that projects the new designs onto garments on mannequins in a showroom. The garments and the new designs projected onto the garments have a three-dimensional appearance as if the garments having the new designs are worn by people. Software and lasers are used in finishing the garments to produce garments with the new designs and the finished garments have an appearance of the three-dimensional appearance of the garments and new designs on the mannequins with the new designs projected onto the garments by the projection system.

The present invention relates to a first computer-implemented method for embedding a manufacturing definition model into a first 3D garment model representing a first garment to be fabricated. Further, the invention relates to a second computer-implemented method for digitally approving a modified second 3D garment model representing a second garment to be fabricated. The invention also relates to a third computer-implemented method for automatically grading a third 3D garment model representing a second garment to be fabricated in at least one different size.

Computer based systems and methods for designing and manufacturing consumer products, including knit footwear uppers, and the like. The system provides digital controls for the customization of knitted components, including complex multi-structured knitted components. The system simulates deformations of knit structures and allows the user to control and visualize compensations in the structure(s) of the knitted component to better match between an intended knit design and the actual physical knitted component outcome. They system may manufacture/fabricate a knitted component based on the predicted/estimated deformation behavior of the knit.

A computer-aided design (CAD) system enables physical articles to be customized via printing or embroidering and enables digital content to be customized and electronically shared. A CAD user interface may be generated that includes an image of a model of an article of manufacture and a customizable template. The customizable template may include user customizable design areas. One or more defined rules associated with respective customizable areas may be accessed. In response to a user selection of a default content item and a corresponding rule, content items may be automatically used to populate other template design areas and/or change a color of one or content items. Manufacturing instructions corresponding to the user customizations may be transmitted to a printing system using a file that includes location, rotation, and/or scale data.

A computer-aided design system enables physical articles to be customized via printing or embroidering and enables digital content to be customized and electronically shared. A user interface may be generated that includes an image of a model of an article of manufacture and user customizable design areas that are graphically indicated on the image corresponding to the model. A design area selection may be received. In response to an add design element instruction and design element specification, the specified design element is rendered in the selected design area on the model image. Customization permissions associated with the selected design area are accessed, and using the customization permissions, a first set of design element edit tools are selected and rendered. User edits to the design element may be received and rendered in real time. Manufacturing instructions may be transmitted to a printing system.

A computer-aided design system enables physical articles to be customized via printing or embroidering and enables digital content to be customized and electronically shared. A user interface may be generated that includes an image of a model of an article of manufacture and user customizable design areas that are graphically indicated on the image corresponding to the model. A design area selection may be received. In response to an add design element instruction and design element specification, the specified design element is rendered in the selected design area on the model image. Customization permissions associated with the selected design area are accessed, and using the customization permissions, a first set of design element edit tools are selected and rendered. User edits to the design element may be received and rendered in real time. Manufacturing instructions may be transmitted to a printing system.

In an embodiment, a method for optimizing computer machine learning includes receiving an optimization goal. The optimization goal is used to search a database of base option candidates (BOC) to identify matching BOCs that at least in part matches the goal. A selection of a selected base option among the matching BOCs is received. Machine learning prediction model(s) are selected based at least in part on the goal to determine prediction values associated with alternative features for the selected base option, where the model(s) were trained using training data to at least identify weight values associated with the alternative features for models. Based on the prediction values, at least a portion of the alternative features is sorted to generate an ordered list. The ordered list is provided for use in manufacturing an alternative version of the selected base option with the alternative feature(s) in the ordered list.

This Invention Patent application refers to a smart process control system for continuous treatment of paper and cellulose machine clothing and parts, in which three machine learning methods are covered, comprising learning and predictive algorithms especially developed for constant evaluation of the knowledge base, aiming at operational optimizations, online monitoring of relevant parameters through use of IoT (Internet of Things) for detection of faults and opportunities, in addition to modeling of ideal operation conditions through directed statistical simulations. The synchronism of this artificial intelligence cycle enables automatic decision making on the best chemical and mechanical strategy for application, aiming at the best possible performance.

A computer-aided design system enables physical articles to be customized via printing or embroidering. A user interface may be generated that includes an image of a model of an article of manufacture and user customizable design areas that are graphically indicated on the image corresponding to the model. A design area selection may be received. In response to an add design element instruction and design element specification, the specified design element is rendered in the selected design area on the model image. Customization permissions associated with the selected design area are accessed, and using the customization permissions, a first set of design element edit tools are selected and rendered. User edits to the design element may be received and rendered in real time. Manufacturing instructions may be transmitted to a printing system.