Systems for providing efficient manufacturing of paper, sheet, and/or box products of varying size and structure, often with pre-applied print (“pre-print”), are provided herein. One or more controllers can be used to aggregate upcoming orders and information needed to complete the manufacturing process for the order. A controller enables a user to prepare control plans (e.g., reel maps, reel plans, etc.) for processing rolls of web product through the manufacturing process. Criteria filtering and/or various features enable generation of efficient and effective control plans for rolls of web product, including, in some cases, multiple orders. The control plan may include a set of instructions for operating one or more systems within the manufacturing process to form the desired finished paper-based product. In such a regard, efficient manufacturing of various paper-based products, including corrugated boxes, folded carton, labels, flexible paper, industrial bags, plates, cups, décor, and many others, can be achieved.

The present invention discloses a space allocation system and a method for allocating space to objects with multi-variate characteristics. In the present invention, intra-container allocation and/or inter-container allocation is performed to generate a combination in which the objects can be placed in one or more pre-defined storage spaces in a plurality of storage containers. The generated combination is further optimized for efficient space allocation to objects with multi-variate characteristics.

In implementations of pattern filling in garment pieces, a pattern filling system represents a first garment piece as a first curve and a second garment piece as a second curve. The system determines a relationship between the first garment piece and the second garment piece by comparing the first curve and the second curve. The pattern filling system generates a visually pleasing fill pattern for the first garment piece and the second garment piece based on the determined relationship.

According to the present invention there is provided a method of projecting images of sewing patterns as templates onto fabrics. The contemplated application for the invention includes sewist making an article of clothing. As such, images of the patterns to be sewn are stored in a storage device for latter access from a computing device that sends them to a projecting device for projection. The projecting devices is then positioned, graduated, calibrated, and set for optimizing the cutting of the fabric. Thereafter, the operator may interactively modify the projected image, and as such initiates the cutting of the fabric, in accordance to the projected sewing patterns.

A method for optimizing production of sheet-metal parts, the production comprising cutting out and singularizing the sheet-metal parts and bending the sheet-metal parts, wherein the method includes: (A) training a neural network, which is executed on a Monte Carlo tree search framework, by means of supervised learning and self-play with reinforcement learning; (B) recording constraints for the sheet-metal parts, the constraints comprising geometric data of the sheet-metal parts; (C) creating an optimized production schedule by way of the neural network; and (D) outputting the production schedule.

A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more processors and perform receiving orders from physical stores for fulfillment from a distribution center, each of the orders comprising a set of items and a requested delivery date; generating a stack building plan for each of the orders using simulated annealing; obtaining routes for delivering the orders in trailers from the distribution center to the physical stores based at least in part on the stack building plan; and generating a load design for each of the routes to deliver in a trailer of the trailers a load for one or more of the orders, such that floor spot assignments for stacks for each of the one or more of the orders in the load carried by the trailer satisfy sequence-of-delivery constraints and center-of-gravity constraints. Other embodiments are disclosed.

An automated palletizer includes an automated package pick device capable of moving packages from a package deposit section to a pallet to form a pallet load from packages, a controller that is operably connected to the automated pick device, the controller having a pallet load generator configured to determine a pallet load structure of mixed packages, the pallet load generator being programmed so that it determines the load structure from mixed package layers overlaid over each other at least one of the mixed package layers being formed of stacks of mixed packages, top and bottom surfaces of the stacks corresponding to the at least one mixed package layer respectively forming top and bottom surfaces of the at least one mixed package layer that are substantially flat. The controller generates commands for the pick device to build the pallet load from the load structure determined by the pallet load generator.

An apparel patternmaking software that allows the user to select from a plurality of templates for a variety of slopers that can be used to create a customized, made to measure digital sewing pattern for various articles of clothing. The user is asked to provide measurements that can be manually measured or imported from a body scanner or both. Further, the user is prompted to review a list of default, pre-defined design choices for how to adjust a sloper based on the relationship of the inputted measurements with each other (e.g., if the waist is wider than the hip measurement or if the waist is narrower than the hip measurement). The user is allowed to add new conditions and default design choices to edit and alter the sloper. The sloper is automatically adjusted to accommodate the entered set of measurements.

A simulation-based framework for optimizing resource allocation and layout design is disclosed.

A dynamic optimization method for procurement specifications of BEF raw materials includes: obtaining finished product data; obtaining an initial feasible raw material size set; mapping the initial feasible raw material size set in length and width directions to obtain a complete feasible raw material size set; filtering an unreasonable raw material size out of the complete feasible raw material size set to obtain a final feasible raw material size set; and determining whether a scale of the final feasible raw material size set is larger than a threshold, if not, building and solving an integer programming model, and outputting results; and if yes, batchwise processing the final feasible raw material size set to obtain multiple subsets, and building an integer programming model for each subset, and solving the integer programming model, and outputting results. A dynamic optimization system of BEF is further provided.