Systems and methods for end-to-end inventory management

Abstract

Systems and methods for managing goods are described. The systems and methods described herein may include exemplary methods for manufacturing goods. The systems and methods provide an end-to-end manufacturing value chain as a closed system and feedback loop.

Description

[Background technology]

[0001] Conventional Fabric The manufacturing process can take a long time from conception of a garment to production of the garment. However, changes in consumer clothing trends can occur rapidly. Additionally, changes in manufacturing parameters, such as available resources, can affect whether a particular garment can be created. By the time the manufacturing process by which a garment is produced is changed to accommodate the new trend and take into account available resources, another new clothing trend may emerge. Adapting more efficiently to changing trends and real-time manufacturing parameters Fabric A manufacturing process is required.

[0002] As an example, U.S. Pat. No. 9,623,578 generally states: fabric printer, fabric The present invention describes a system for on-demand apparel manufacturing that includes a cutter, and a computing device, wherein the computing device aggregates product orders, organizes the orders according to productivity factors, and distributes panels of the ordered products to the aggregated cutter. fabric and aligning the panel template. However, improvements are needed.

[0003] As a further example, U.S. Pat. No. 9,782,906 generally describes: fabric A system for on-demand apparel manufacturing is described that includes a cutter and a computing device. fabric On the cutter fabric configured to perform a process including capturing an image of the sheet; fabric The sheet comprises a panel of the product. fabric Sheet fabric yarn, woven, napped, or knitted patterns, fabric On the sheet fabric Adjusting the position of the print pattern, or fabric On the cutter fabric To take into account the panel deformation of the seat, fabric using an image of the sheet to identify cutting control factors; raw material The change of fabric This may be done separately from the cutter or table. fabric Improvements in cutting and alignment are needed. Summary of the Invention

[0004] In one or more embodiments, the present disclosure relates to an end-to-end process for managing goods. Such goods may include clothing, apparel, accessories, Fabric In one or more embodiments, the present disclosure relates to producing articles within the tolerances of the design of such articles. Often, in conventional processes, article management steps are discrete and separate, and transitions between process steps result in errors or discrepancies from the intended design. The end-to-end process of the present disclosure can minimize such discrepancies and facilitate the production of articles, such as apparel, within tight tolerances of the intended design. In particular, the color of the finished product can be within a predetermined tolerance of the designed color. Alternatively or additionally, the methods and systems of the present disclosure can facilitate dynamic pricing, dynamic lead times, dynamic batching, dynamic delivery, and can provide a personalized or customized process for customers.

[0005] Traditional methods are locked into long, forecast-driven supply chains. The present disclosure provides a demand-driven apparel manufacturing process by moving process steps, such as coloring, closer to the consumer.

[0006] Fabric Manufacturing, etc. raw materialSystems and methods for managing a product are described. The systems and methods described herein may include an exemplary method for manufacturing an article. The exemplary method may include receiving consumer data including at least biometric information associated with one or more consumers. The exemplary method may include receiving design input indicating a design for the article, where the design for the article is based on the consumer data. The exemplary method may include causing output of interactive content to a user interface associated with the one or more consumers, where the interactive content includes at least a representation of the design for the article. The exemplary method may include outputting manufacturing data indicating instructions associated with manufacturing the article, where the instructions are based on the design for the article. These and other Fabric A manufacturing management method and system is described herein. [Brief explanation of the drawings]

[0007] The following drawings illustrate generally, by way of example, but not by way of limitation, various examples discussed in this disclosure. 。

[0008] [Figure 1A] 1 shows an exemplary diagram of a manufacturing process. [Figure 1B] 1 shows an exemplary diagram of a manufacturing process. [Figure 1C] 1 shows an exemplary diagram of a manufacturing process. [Figure 1D] 1 shows an exemplary diagram of a manufacturing process. [Figure 1E] 1 shows an exemplary diagram of a manufacturing process. [Figure 2] 1 shows an exemplary diagram of the design process. [Figure 3] 1 is a flow diagram of an exemplary method. [Figure 4] 1 is a flow diagram of an exemplary method. [Figure 5] 1 shows an exemplary diagram of nesting. [Figure 6] 1 shows an exemplary diagram of an item management process. [Figure 7A] 1 is exemplary data based on the processing of the present disclosure. [Figure 7B] 1 illustrates an exemplary treatment formulation. [Figure 7C] 1 illustrates an exemplary treatment formulation. [Figure 7D] 1 is a flow diagram of an exemplary method. [Figure 8] 1 is a flow diagram of an exemplary method. [Figure 9A] 1 is a flow diagram of an exemplary method. [Figure 9B] 1 illustrates an exemplary traceability mechanism. [Figure 9C] 1 illustrates an exemplary traceability mechanism. [Figure 9D] 1 illustrates an exemplary traceability mechanism. [Figure 9E] 1 illustrates an exemplary traceability mechanism. [Figure 10] This is a process diagram. [Figure 11] 1 illustrates an exemplary system. [Figure 12] 1 illustrates an exemplary system. [Figure 13] 1 illustrates an exemplary system. [Figure 14] 1 illustrates an exemplary process flow. [Figure 15] 1 is a flow diagram of an exemplary method. [Figure 16] 1 illustrates an exemplary system. [Figure 17] 1 illustrates an exemplary system. DETAILED DESCRIPTION OF THE INVENTION

[0009] Systems and methods are described for managing articles such as clothing / apparel, including but not limited to shirts, pants, shorts, footwear, and bags. The systems and / or methods may include end-to-end article management, such as manufacturing. The systems and / or methods may include all aspects of manufacturing, from apparel design to apparel delivery to customers. The systems and / or methods may incorporate information from one or more steps in the management or manufacturing process to affect other steps in the management or manufacturing process. Fabric or Textiles However, a broader range of Raw materials The present invention is intended to be applicable to a wide range of applications and therefore should not be limited to such descriptive terminology.

[0010] The systems and / or methods described herein may include: Fabric The system and / or method described herein may include one or more tools, units, or factories for managing articles, such as apparel or clothing, from a supplier to a customer. The systems and / or methods described herein may include one or more clothing manufacturing factories. The systems and / or methods described herein may include one or more computing devices associated with one or more clothing manufacturing factories associated with one or more respective clothing manufacturers. The systems and / or methods described herein may include one or more cloud computing environments associated with one or more clothing manufacturing factories. The systems and / or methods described herein may include one or more client devices, such as laptops, desktops, smartphones, wearable devices, tablets, etc. The one or more client devices may communicate with the one or more computing devices and / or one or more cloud computing environments over a network. The one or more client devices may include one or more applications executing on the one or more client devices.

[0011] The systems and / or methods described herein may include a business process. The business process may include a process for creating a job file (e.g., 110 of FIG. 1A). The job file may include authoring tool instructions, digital asset management instructions, and / or pattern and / or marker instructions. The authoring tool may include a 2D design tool, a 3D polygonal design tool, and / or a 3D parametric design tool. Digital asset management includes creating a digital asset. raw material ,Graphics, Images, 3D Assets, Color Profiles, Conformance Blocks, Design Library Management, raw material Development, line planning, raw material table, raw material This may include information regarding testing, vendor collaboration, and / or financial planning. As described herein, digital asset management includes: raw material The physical properties of raw material the spectral reflectance and refractive index properties of raw material performance characteristics of raw material may include or be based on data regarding origin of and associated resource consumption, batch serialization, etc. Patterns and / or markers may include patterns, reference points, cutting data, grading, graphic images, colors, cutting plans, job status management, and / or raw material May contain utilization information. Job files may contain options selected by a user. Job files may contain options selected by a user. Job files may contain options selected without user intervention.

[0012] A job file may be created by one or more computing devices ("job file creators"). The job file creators may communicate over a network with one or more computing devices configured to collect real-time and / or near-real-time production and / or consumer data ("data collection"). The job file and / or available parameters associated with the job file may be affected by the real-time data received from the data collection. The job file creators may communicate over the network with one or more computing devices ("controllers") configured to cause the execution of one or more manufacturing steps. The job file creators may provide the job file to the controllers. The controllers may cause the execution of one or more manufacturing steps according to the job file.

[0013] The systems and / or methods described herein may include a feedback loop for the designer. Biometric and / or consumer data may be captured and trends may be identified. Options available to the designer in their design tool may be influenced by the captured biometric and / or consumer data. The designer may design a garment based on the options available in their design tool. Biometric and / or consumer data associated with the designed garment may be captured and trends may be identified, thus restarting the feedback loop.

[0014] The systems and / or methods described herein may be used to raw material Nesting may be used to efficiently use the materials. Nesting is used to reduce waste from cutting. raw materialNesting may involve arranging patterns to be cut from. Nesting may involve arranging components having similar or the same color and / or pattern at their boundaries so that two such boundaries of two components are adjacent to one another. Nesting may involve using color overlap between two or more components. Nesting may involve dynamically batching orders.

[0015] The systems and / or methods described herein may include a foam pretreatment process. The foam pretreatment process may replace a traditional dipping process. The foam pretreatment process may reduce water. The foam pretreatment process may reduce energy. The foam pretreatment process may reduce chemical use. The foam pretreatment process may achieve darker and / or richer colors. The foam pretreatment process may dry more easily than a traditional dipping process.

[0016] The systems and / or methods described herein may include a plasma pre-cleaning / activation process. The atmospheric plasma pre-cleaning / activation process may include a corona plasma. The atmospheric plasma pre-cleaning / activation process may include: Fabric and / or raw material Wash the Fabric / fiber and / or raw material It may be used to increase the surface roughness of the surface and improve adhesion properties. Fabric and / or raw material Atmospheric pressure plasma pre-cleaning / activation steps may be used after and / or before the foam pre-treatment and / or pad step to vaporize and / or decompose contaminants (e.g., oils, waxes, etc.) from the surface. Fabric and / or raw material The atmospheric pressure plasma pre-cleaning / activation process may include: Fabric and / or raw material The plasma pre-cleaning / activation process reduces the use of dyes and / or chemicals while Fabric and / or raw materialDeeper and / or more saturated colors can be achieved. The plasma pre-cleaning / activation process does not require water and may be performed at ambient temperature. The plasma pre-cleaning / activation process may be applied with different carrier gases such as air, oxygen, nitrogen, helium, argon, hydrocarbon-based gases, fluorocarbon-based gases, and / or mixtures of different gases. Each gas has a different surface topography, chemistry, and surface energy. Fabric and / or raw material Some grafting reactions (functionalization reactions) are Fabric and / or raw material This can occur between the surface and the plasma carrier gas. Fabric and / or raw material The chemical composition of the plasma may be altered after the plasma process. The systems and / or methods described herein may include a color analysis process. The color analysis process may compare the intended color to the actual color. The color analysis process may determine the intended color from digital data, such as data from a job file. The color analysis process may determine the actual color using computer vision.

[0017] The systems and / or methods described herein may be used to raw material For in-line inspection of FabricThe operation may include inserting and / or adding one or more sensors. The one or more sensors may include a spectrometer. The one or more sensors may include an optical spectrometer. The one or more sensors may include a spectrophotometer. At one or more steps in the manufacturing process, one or more sensors may be inspected to ensure quality. The one or more sensors may be inspected manually by a human. The one or more sensors may be inspected by one or more computing devices. Inspecting the one or more sensors by the one or more computing devices may include comparing an observed data set to an expected data set. Inspecting the one or more sensors by the one or more computing devices may include triggering an alert when a difference between the observed data set and the expected data set is greater than a predetermined threshold. In one aspect, an identifying indicia, such as a barcode, QR code, invisible marker, etc. raw material to enable the code to be read or detected by a reading device such as, for example, a spectrometer.

[0018] The systems and / or methods described herein may include an observation step. The observation step includes: Fabric This may involve observing patterns of Fabric The observation step may be performed after one or more manufacturing steps. Fabric The observing step may include observing the pattern before one or more manufacturing steps. Fabric The observed pattern of the Fabric The observing step may be performed by one or more computing devices ("observers"). The observers may include determining a delta between the observed pattern of Fabric The determined deltas may be provided to one or more computing devices in communication with the machine for slicing the data.

[0019] Digital Product Creation The traditional process of creating an article involves siloed manual steps / operations. The present disclosure allows consumers to customize products through an ordering system, which may include the ability for user-input data such as their measurements. Software may generate automatic patterns, and the solution selects an appropriate pattern based on established fitting rules. Such software may include custom selection of colors or graphics that may be used for automatic pattern generation or selection of an existing pattern. This pattern is then sent to the manufacturing site for design, including work instructions. raw material The system and method may be integrated with back-end systems that enable on-demand manufacturing.

[0020] Custom-made Today, front-end consumer systems offer the ability to customize a product from a list of options. These options are similarly limited because they are mapped to back-end manufacturing systems. The ability to customize to a specific size is limited. Additionally, options to personalize the product are limited. There is no option to do this on-demand. The present disclosure provides the ability to customize a product or add user-entered information to a product. The system and method can dynamically configure the product to fit an individual's requirements and create manufacturable packaging. The system and method can be further extended to automate much of the product creation.

[0021] Image Pre-Distortion Conventional fabric In processing, Textile materialsis processed in the form of a "web," whereby mechanical forces and / or mechanical forces combined with heat cause distortion of the entire "web." That is, while an image printed on a digital printer may be controlled to within nanometers of accuracy, subsequent processing can result in distortions that differ from those intended by the creator. This disclosure provides a method for "pre-distorting" the image applied to the web at the digital printing stage, allowing the unprocessed image to be distorted through downstream processing so that the final product matches the creator's intent. raw material The method receives information associated with the distortion of the web and then maps the distortion. As an example, the present disclosure can address one or more shortcomings of conventional processes using a feedback loop / verification, for example, as shown in FIG.

[0022] In the manufacturing process raw material manipulation (e.g., printing the upper around the final product) raw material ) creates curvature and bending of the image or pattern from the intended print. In accordance with the present disclosure, at least the example illustrated in FIG. 9A can produce a final product that is more faithful to the original shape by including pre-distortion in the print job file to account for downstream processes.

[0023] raw material Classification of Current industry practice is fragmented and does not consider the substrate and its respective impact on multispectral color refractive index, translucency, opacity, etc. Furthermore, substrate construction is practically Fabric Affects how the material covers and / or flows raw materialand additional input data such as one or more of whiteness index, pH, degree of mercerization, refractive index and reflectance index, thickness, compression, bending, roughness, friction, thermal properties, smoothness, softness, warmth, puckering, distortion, composite measurements thereof, or inherent observed performance history and variability. According to aspects of the present disclosure, by collecting substrate property and performance data (e.g., whiteness index, pH, etc.) and integrating these properties, key design and performance characteristics can be digitally recreated in digital form, i.e., a digital twin can be created, which means that a faithful reproduction of real life can be created.

[0024] Order Creation and Job Management 1A-1E illustrate exemplary diagrams of management (e.g., manufacturing) processes. While an exemplary sequence is shown, it is understood that various steps may be performed in any order and may be selectively performed or not. Feedback loops from one or more downstream processes may be received and used to update one or more upstream processes. As an example, data collected at any one of the manufacturing steps may be shared upstream or downstream in the end-to-end process and used to update other processes. As a further example, to provide complete end-to-end control, all manufacturing steps may be performed at a single facility. However, data shared between steps may also allow for one or more processes to be performed at different facilities without losing control or standardization. At 100, a project request and / or order may be received. The project request and / or order may be received at one or more computing devices associated with a garment manufacturer. The project request and / or order may be received in a cloud computing environment associated with the garment manufacturer. As used herein, manufacturing or manufacturer may refer to an operation or entity associated with any part of managing the production and delivery of goods. The project request and / or order may be received from a client device associated with the customer.

[0025] In response to received project requests and / or orders, a job (e.g., order, project, etc.) file 110 may be created. The job file 110 may include graphic design files 112, grading information 114, quantity / yardage requirements 116, kitting data 118, order data 120, pattern files 122, substrates 124, finishing data 126, assembly data 128, and / or tracking and / or routing data 130. The job file 110 may include: raw material Other information may be included in or referenced within / by the job file 110, which may include tables and / or serialized data.

[0026] In response to the received project request and / or order, at 102, Fabric A determination may be made whether one or more computing devices and / or cloud computing environments associated with the garment manufacturer have already created a project request and / or order. Fabric may determine whether a Fabric If not already created, the process may move to 106. Fabric If already created, the process may move to 104.

[0027] 104, associated with the project request and / or order Fabric A determination may be made whether one or more computing devices and / or cloud computing environments associated with the garment manufacturer are in stock. Fabric may determine whether the item is in stock. Fabric If is in stock, the process may move to 108. Fabric If is not in stock, the process may move to 106.

[0028] 106, associated with the project request and / or order Fabric One or more computing devices and / or cloud computing environments associated with the garment manufacturer may: Fabric of Fabric Orders may be placed with suppliers. Associated with project requests and / or orders Fabric After the order is placed, raw material The test database 134 may be updated and the process may move to 108 .

[0029] 108, associated with the project request and / or order Fabric may cause the processing of purchase orders and / or payment cycle procedures associated with the clothing manufacturer. One or more computing devices and / or cloud computing environments associated with the clothing manufacturer may process purchase orders and / or payment cycle procedures. One or more computing devices and / or cloud computing environments associated with the clothing manufacturer may cause another one or more computing devices to process purchase orders and / or payment cycle procedures.

[0030] Associated with project requests and / or orders Fabric After triggering processing of the purchase orders and / or payment cycle procedures associated with the garment manufacturer, inventory control may be performed at 132. One or more computing devices and / or cloud computing environments associated with the garment manufacturer may perform inventory control and / or trigger the performance of inventory control. Performing inventory control may include processing the purchase orders and / or payment cycle procedures associated with the garment manufacturer. Fabric This may include updating inventory to reflect the purchase order and / or payment cycle procedures associated with the transaction. Fabric This may include using inventory information as part of the intake step. FabricThe step of performing inventory control may include updating inventory information based on the intake step. Fabric This may include updating inventory information based on the pre-processing steps.

[0031] raw material The test database 134 is Fabric It may communicate with one or more computing devices associated with the supplier mill 136 . raw material The test database 134 is Fabric Supplier Mill 136 Fabric may cause an order. Fabric Supplier Mill 136 is at 138 Fabric As part of the adoption step, Fabric may cause delivery of

[0032] 138, clothing manufacturers, etc. raw material The operator or administrator: raw material (For example, at 138 Fabric As part of the intake step, Fabric From supplier Mill 136 Fabric ) may have or receive other raw material may be used. Fabric After the intake step, the process Fabric The process may proceed to a pre-processing step. It is understood that such a process is not limited to garment manufacturing, but is a non-limiting example. Other entities and operators may perform the same or similar operations. In one aspect, operational capacity, such as manufacturing capacity for a particular product, may be considered to determine an estimated lead time (e.g., in real time) and may enable surge pricing / priority pricing.

[0033] At 138 Fabric After the intake step, a laboratory and / or visual inspection may be performed at 142. The inspection may include human inspection. The inspection may include inspection using computer vision. The inspection may include: FabricThis may include testing one or more sensors in communication with the Fabric If the test fails, raw material The test database 134 may be updated (which results in Fabric More from Supplier Mill 136 Fabric The order, raw material The results of the laboratory and / or visual inspection may be passed to the laboratory and / or visual inspection at 144.

[0034] At 140 Fabric The pretreatment step may include a foam pretreatment process. The foam pretreatment process may replace a traditional dipping process. The foam pretreatment process may reduce water. The foam pretreatment process may reduce energy. The foam pretreatment process may reduce chemical use. The foam pretreatment process may achieve darker and / or richer colors. The foam pretreatment process may dry more easily than a traditional dipping process. Fabric is 146 Fabric It may be used in the adjustment step.

[0035] At 140 Fabric After the pre-processing step, laboratory and / or visual inspection at 144 may be performed. The inspection may include human inspection. The inspection may include computer vision, machine vision, and machine learning. The inspection may include: Fabric This may include testing one or more sensors in communication with the Fabric If the test fails, raw material The test database 134 may be updated (which results in Fabric More from Supplier Mill 136 Fabric The order, raw material (This may require the data to be included in the test database 134). Fabric If the test fails, the result is a failed raw materialNew orders may be generated to backfill the inventory. Estimated lead times may change as a result of the outage. Laboratory and / or visual inspection results may be used to Fabric It may be passed to one or more computing devices involved in the reconciliation step.

[0036] At 146 Fabric The conditioning step may include an atmospheric pressure plasma pre-cleaning / activation step. The atmospheric pressure plasma pre-cleaning / activation step may include a corona plasma. The atmospheric pressure plasma pre-cleaning / activation step may include: Fabric and / or raw material Wash the Fabric / fiber and / or raw material It may be used to increase the surface roughness of the surface and improve adhesion properties. Fabric and / or raw material Atmospheric pressure plasma pre-cleaning / activation steps may be used after and / or before the foam pre-treatment and / or pad step to vaporize and / or decompose contaminants (e.g., oils, waxes, etc.) from the surface. Fabric and / or raw material The atmospheric pressure plasma pre-cleaning / activation process may include: Fabric and / or raw material The plasma pre-cleaning / activation process may result in the use of fewer dyes and / or chemicals while Fabric and / or raw material Deeper and / or more saturated colors can be achieved. The plasma pre-cleaning / activation process does not require water and may be performed at ambient temperature. The plasma pre-cleaning / activation process may be applied with different carrier gases such as air, oxygen, nitrogen, helium, argon, hydrocarbon-based gases, fluorocarbon-based gases, and / or mixtures of different gases. Each gas has a different surface topography, chemistry, and surface energy. Fabric and / or raw material Some grafting reactions (functionalization reactions) are Fabric and / or raw materialThis can occur between the surface and the plasma carrier gas. Fabric and / or raw material The chemical composition of the plasma may be changed after the plasma process. Fabric may be used in the printing step at 158.

[0037] At 146 Fabric After the adjustment step, a laboratory and / or visual inspection at 148 may be performed. The inspection may include human inspection. The inspection may include inspection using computer vision. The inspection may include: Fabric This may include testing one or more sensors in communication with the Fabric If the test fails, raw material The test database 134 may be updated (which results in Fabric More from Supplier Mill 136 Fabric The order, raw material The results of the laboratory and / or visual inspection may be passed to one or more computing devices involved in the printing step at 158.

[0038] At 150, the job file 110 may be used as part of a nested pattern step. One or more computing devices may use the job file 110 as part of the nested pattern step. The pattern file 122 of the job file 110 may be used as part of the nested pattern step. Other portions of the job file 110, such as the graphic design file 112, grading information 114, etc., may also be used. The nested pattern step is described in more detail with reference to FIG. 3. After the nested pattern step, the process may move to 152. As described herein, the nesting may be generated or updated based on upstream or downstream information. Alternatively or additionally, the nesting may be updated based on information received regarding downstream process or device performance. For example, in the case of a cutting process or machine, or raw material If a handling process or machine / system performs in a particular manner, the nesting may be updated based on such performance information.

[0039] At 152, a cutting file may be generated. The cutting file may be generated in response to nested pattern steps. One or more computing devices may generate the cutting file. The cutting file may be Fabric The cutting file may contain information for cutting components from the cutting file. The cutting file may be used in the cutting step at 182. After the cutting file is generated, the process may move to 154. For purposes of explanation, reference is made to various files. It should be understood that multiple files or a single file may be used.

[0040] At 154, a color separation step may be performed. One or more computing devices may perform the color separation step. The job file 110 may be used to perform the color separation step. After the color separation step, the process may proceed to 156.

[0041] At 156, a raster image processing step may be performed. One or more computing devices may perform the raster image processing step. The job file 110 may be used to perform the raster image processing step. After the raster image processing step, the process may move to 158.

[0042] At 158, a printing step may be performed. Although the term printing is used, drop-on-demand printing may also be performed, e.g. raw material It should be understood that the term "printing" refers to a general selective process including selective deposition of and digital printing. Fabric causing printing of colors and / or graphics to the one or more computing devices. Fabric The result of the raster image processing step at 156 may cause the printing of color and / or graphics to Fabric The job file 110 may be used to affect the printing of color and / or graphics to the Fabric May be used to affect the printing of color and / or graphics onto a printed product. Fabric may be used in the post-printing dyeing step at 166.

[0043] After the printing step at 158, a laboratory and / or visual inspection may be performed at 160. The inspection may include human inspection. The inspection may include inspection using computer vision. The inspection may include: Fabric The testing may include testing one or more sensors in communication with the printer. The testing may determine whether the expected color and the color are correct during the printing step at 158. Fabric It may be determined whether and to what extent there is a difference between the actual printed color at 160 and the color that was actually printed at 160. The results of the laboratory and / or visual inspection may be passed to one or more computing devices associated with the color control / printer calibration step at 162. The one or more computing devices associated with the color control / printer calibration step at 162 may provide information to assist in the inspection at 160. The results of the laboratory and / or visual inspection may be passed to one or more computing devices involved in the post-printing staining step at 166.

[0044] At 162, one or more computing devices associated with the color control / printer calibration step may communicate the expected colors and the FabricThe one or more computing devices associated with the color control / printer calibration step may determine and / or receive information indicating a discrepancy between the predicted color and the actual printed color. One or more computing devices associated with the color control / printer calibration step may determine a new paint color associated with the predicted color. The one or more computing devices associated with the color control / printer calibration step may determine that the new paint color requires more or less of a particular color, such as red, blue, and / or green, to approximate the predicted color. The one or more computing devices associated with the color control / printer calibration step may communicate with one or more computing devices associated with the update library of addressable color steps at 164.

[0045] At 164, one or more computing devices associated with the addressable color step update library may update the addressable color library based on information from one or more computing devices associated with the color control / printer calibration step. The one or more computing devices associated with the addressable color step update library may assign the determined new paint color to the predicted color. The one or more computing devices associated with the addressable color step update library may use the updated addressable color library to trigger the generation of a new project request and / or order at 110.

[0046] A post-printing drying step may be performed at 166. A post-printing dyeing step may be performed at 166. Fabric The one or more computing devices may include: Fabric This may cause drying of the product. Fabric may be used in the settling / steaming step at 170.

[0047] After a post-print drying step at 166, a laboratory and / or visual inspection at 168 may be performed. The inspection may include human inspection. The inspection may include inspection using computer vision. The inspection may include: Fabric This may include testing one or more sensors in communication with the Fabric If the test fails, raw material The test database 134 may be updated (which results in Fabric More from Supplier Mill 136 Fabric The order, raw material The results of the laboratory and / or visual inspection may be passed to one or more computing devices involved in the settling / steaming step at 170.

[0048] At 170, a fixing / steaming step may be performed. The fixing / steaming step may be performed on the printed and / or dyed Fabric The method may include steaming one or more computing devices. Fabric Steaming may be performed on the surface of the material after the settling / steaming step. Fabric may be used in a post-print cleaning step at 174.

[0049] After the settling / steaming step at 170, a laboratory and / or visual inspection at 172 may be performed. The inspection may include human inspection. The inspection may include inspection using computer vision. The inspection may include: Fabric The results of the laboratory and / or visual inspection may be passed to one or more computing devices involved in the post-printing cleaning step at 174.

[0050] At 174, a post-print cleaning step may be performed. The post-print cleaning step may include steam and / or fixed Fabric The one or more computing devices may include: FabricThis may cause cleaning of the print. Fabric may be used in the post-printing drying step at 178.

[0051] After the post-printing step at 174, a laboratory and / or visual inspection at 176 may be performed. The inspection may include human inspection. The inspection may include inspection using computer vision. The inspection may include: Fabric The results of the laboratory and / or visual inspection may be passed to one or more computing devices involved in the post-printing drying step at 178.

[0052] At 178, a post-printing drying step may be performed. Fabric The one or more computing devices may include: Fabric This may cause drying of the printed image. Fabric may be used in the cutting step at 182.

[0053] After a post-print drying step at 178, a laboratory and / or visual inspection at 180 may be performed. The inspection may include human inspection. The inspection may include inspection using computer vision. The inspection may include: Fabric This may include testing one or more sensors in communication with the Fabric If the test fails, raw material The test database 134 may be updated (which results in Fabric More from Supplier Mill 136 Fabric The order, raw material (This may be done through a testing database 134.) The results of the laboratory and / or visual testing may be passed to one or more computing devices involved in the cutting step at 182.

[0054] At 182, a cutting step may be performed. Fabricmay be cut into pieces. Fabric may be cut according to the cutting file generated at 152. Fabric may cause the cutting of the Fabric may be used in the batch processing step at 184.

[0055] At 184, a batch processing step may be performed. Fabric may be batch processed. Fabric This may cause a batch process. Fabric may be used in the kitting step at 186.

[0056] At 186, a kitting step may be performed. Fabric may be packaged as a kit. Fabric The kitting step may be carried out. Fabric may be used in the assembly step at 188.

[0057] At 188, an assembly step may be performed. Fabric may be assembled. One or more computing devices may Fabric may cause the assembly of the Fabric may be shipped to the customer.

[0058] Other steps and processes may be performed. Steps may be selectively performed or not. Data may be shared between processes, and processes may be updated based on shared data regarding upstream and / or downstream processes and equipment performance.

[0059] Design / Product Development Current design and product development tools are not digitally linked to actual production methods. According to this disclosure, digital product creation may include manufacturing (print) instructions created from a design platform. The color feasibility has a feedback loop to inform the design platform and define the designer's choices for the product.

[0060] 2 shows an example diagram of a design process. At 200, consumer data may be received (e.g., collected, etc.). The consumer data may include biometric data. The consumer data may be collected from one or more consumers. The consumer data may be collected from one or more wearable devices. The consumer data may be collected from one or more e-commerce websites. The consumer data may be collected from a feedback loop. The consumer data may be collected from a repository.

[0061] At 202, the designer's user interface may be influenced by the consumer data. The color and / or design options within the design tool may be influenced by the consumer data. The color and / or design options within the design tool may be influenced by the consumer data. The color and / or design options within the design tool may be influenced by the preferred color and / or design options that are prominently displayed in the designer's user interface. raw material The designer's user interface may be associated with two-dimensional and / or three-dimensional design and / or development tools.

[0062] At 204, the visualization tool may be influenced by the two-dimensional and / or three-dimensional design and / or development tool. The visualization tool may be influenced by the consumer data. Optionally, and / or the colors and / or designs displayed in the visualization created by the visualization tool may be influenced by the consumer data.

[0063] At 206, an interactive consumer experience may be presented to the consumer via the e-commerce website. The interactive consumer experience presented to the consumer may be influenced by visualization tools. The interactive consumer experience presented to the consumer may be influenced by two-dimensional and / or three-dimensional design and / or development tools. The interactive consumer experience presented to the consumer may be influenced by consumer data. Colors and / or designs that are optional and / or displayed in the interactive consumer experience may be influenced by the consumer data. Feedback from the interactive consumer experience may be new consumer data at 200.

[0064] At 208, drop-on-demand (e.g., digital) and / or traditional manufacturing may be influenced by visualization tools. Digital and / or traditional manufacturing may be influenced by 2D and / or 3D design and / or development tools. Digital and / or traditional manufacturing may be influenced by consumer data. Colors and / or designs that are optional and / or displayed in digital and / or traditional manufacturing may be influenced by consumer data. Feedback from digital and / or traditional manufacturing may be new consumer data at 200.

[0065] At 210, rapid manufacturing may be influenced by visualization tools. Rapid manufacturing may be influenced by 2D and / or 3D design and / or development tools. Rapid manufacturing may be influenced by consumer data. Colors and / or designs that are optional and / or displayed in rapid manufacturing may be influenced by consumer data. Feedback from rapid manufacturing may be new consumer data at 200.

[0066] The design and development of fashion trends is currently fragmented and not directly driven by consumer demand, i.e., designers. Creators make their best guess as to what the trend will be and hope for the best. This traditional approach is suboptimal. According to the present disclosure, an improved on-demand feedback loop can enable data-driven prediction of needed color combinations and designs.

[0067] Referring to Figure 3, a method for manufacturing an article is illustrated. The method may allow for customization. The method may allow for dynamic pricing. The method may allow for dynamic lead time determination. The method may allow for dynamic delivery.

[0068] At step 310, consumer data including at least biometric information associated with one or more consumers may be received. One or more computing devices may receive the consumer data including at least biometric information associated with one or more consumers. The consumer data may include consumer preference information.

[0069] At step 320, design input indicating a design for an article may be received. One or more computing devices may receive the design input indicating a design for the article. The design for the article may be based on consumer data. The design input indicating a design for the article may be consumer-directed, such as a made to measure article, or a personalized and / or custom article. The design input indicating a design for the article may be used in product design for mass-produced articles. The design input indicating a design for the article may include automated pattern creation. The design input indicating a design for the article may be provided directly by a manufacturer. The design input indicating a design for the article may be fitted to a design model. A "fit model" is a model utilized by a brand to design sizing parameters for a product line, i.e., a standard collection of dimensions scaled for each available size.

[0070] At step 330, output of interactive content to a user interface associated with one or more consumers may be triggered. One or more computing devices may trigger output of interactive content to a user interface associated with one or more consumers. The interactive content may include at least a representation of a design of the article.

[0071] At step 340, manufacturing data indicative of instructions associated with manufacturing the article may be output. One or more computing devices may output manufacturing data indicative of instructions associated with manufacturing the article. The instructions may be based on a design of the article. Outputting the manufacturing data may include outputting at least a portion of the manufacturing data to a digital printing system. The manufacturing data may be provided directly from a designer to a manufacturer. The manufacturing data may be provided directly from a customer to a manufacturer.

[0072] Coloring data indicating the feasibility of coloring may be received. One or more computing devices may receive the coloring data indicating the feasibility of coloring. The design of the article may depend on the coloring data.

[0073] Sensors on the garment may detect when the garment is being worn. The sensors may communicate with an application running on the client device. The application may relay information from the sensors to a centralized server. The centralized server may then determine which color, pattern, and / or Fabric The centralized server may include an application for determining trend information, such as which items are most frequently worn. The centralized server may provide the determined trend information to a server associated with the e-commerce website or to a browser running on a user device accessing the e-commerce website. The e-commerce website may make suggestions based on the determined trend information.

[0074] Referring to Figure 4, a method for product development is illustrated. At step 410, consumer data including at least biometric information associated with one or more consumers may be received. One or more computing devices may receive the consumer data including at least biometric information associated with one or more consumers. The consumer data may include consumer preference information.

[0075] Trend data indicating trends in one or more of article design or article coloring may be received at step 420. One or more computing devices may receive the trend data indicating trends in one or more of article design or article coloring.

[0076] At step 430, output of one or more design options may be triggered via a user interface based on at least the consumer data and the trend data. One or more computing devices may trigger output of one or more design options via a user interface based on at least the consumer data and the trend data.

[0077] Design inputs indicating a design for the article may be received at step 440. One or more computing devices may receive the design inputs indicating a design for the article.

[0078] In response to receiving design input, Fabric The designer may then select the type of Fabric You may select one or more of the types. Fabric In response, an integrated technology package may be created for the designer. The integrated technology package incorporates the design input and the selected one or more types of Fabric may be adapted. raw material A table may be generated for the integrated technology package. raw materialThe table may be generated on demand.

[0079] Sensors on the garment may detect when the garment is being worn. The sensors may communicate with an application running on the client device. The application may relay information from the sensors to a centralized server. The centralized server may then determine which color, pattern, and / or Fabric The centralized server may include an application for determining trend information, such as which items are most frequently worn. The centralized server may provide the determined trend information to a server associated with the remotely accessible designer tool or to a browser running on a user device accessing the remotely accessible designer tool. The designer tool may make suggestions based on the determined trend information. A user may create a design based on the suggestions. A user may create an order based on the design. raw material The table may be automatically generated based on the order.

[0080] As an example, a method for article management may include receiving consumer data including at least biometric information associated with one or more consumers. The consumer data may further include consumer preference information. The method may include receiving design input indicating a design for the article. The design for the article may be based on the consumer data and / or other input. The method may include causing output of interactive content to a user interface associated with the one or more consumers. The interactive content may include at least a representation of the design for the article. The method may include outputting article data including at least manufacturing data indicating instructions associated with manufacturing the article. Outputting the manufacturing data may include outputting at least a portion of the manufacturing data to a drop-on-demand system (e.g., a digital printing system). The instructions may be based on the design of the article. The article data may be configured to be received by one or more computing devices associated with one or more manufacturing processes, where the one or more manufacturing processes are updated based at least on the article data. The method may include receiving coloring data indicating feasibility of a color, where the design for the article depends on the coloring data. The method may include outputting the design for the article and Fabric generating a tech pack based on the selection of Fabric Based on the design of raw materialThe method may include outputting a table. Other steps may be used. As a further example, one or more methods may include the article data including nesting information indicating a spatial arrangement of one or more portions of the article, the nesting information being derived at least in part from one or more of the following: a material used to form at least a portion of the one or more portions of the article, one or more treatments applied to the material used to form at least a portion of the one or more portions of the article, a desired web speed, or an operation performed by a pick-and-place system configured to move one or more portions of the article separated from the material. The nesting information may be derived at least in part from a feedback loop associated with the operation of the pick-and-place system. Data may be collected from any number of systems, subsystems, or devices and shared upstream and / or downstream to effect updates in one or more processes.

[0081] Order aggregation and batch processing Traditional order fulfillment for digital printers does not consider the entire manufacturing process of a single order fulfillment system. This is primarily driven by a fragmented value chain, where each process considers its own efficiency but not the entire manufacturing process and its associated overall costs. The present disclosure provides dynamic nesting optimization. As an example, dynamic nesting optimization may involve batching order components to maximize individual consumer orders (specifically, one theoretical minimum order quantity (MOQ)) and speed of production and delivery to the end customer within business-oriented production performance, unit cost / margin, and sustainability parameters.

[0082] In a single-unit order run, individual components may have significantly different levels of ink applied. During a subsequent cleaning process, components with higher levels of ink may cross-contaminate adjacent components with lower levels of ink (e.g., a bright red component adjacent to a white component), potentially resulting in a loss of quality. According to the present disclosure, by analyzing the levels of ink required to print each individual component, a nested pattern may be created, starting with the lowest level of ink and building up to the highest level of ink. Thus, a dark, saturated component (e.g., a bright red component) will be adjacent to a component that is darker in color, thereby avoiding cross-contamination from dark to light colors. The above raw material As the colors move through the washing process, the lightest colors go first (when the washer water is at its cleanest) and the darkest colors go last. This allows less water and chemicals to be used on the lighter colors, making the entire process more efficient and sustainable.

[0083] Traditional production planning processes do not consider optimizing small (as small as a single unit) batches for large runs that utilize both digital manufacturing processes (e.g., digital printing) and traditional "continuous" production processes (e.g., drying, washing). According to the present disclosure, rules may be used to aggregate and organize small batches into larger batches while considering different downstream routings, whereby small batches may be aggregated into a common process and then split again into smaller batches for separate routings in a manner that may be efficiently scheduled in production.

[0084] nesting Current processes for creating RIP and print job files do not consider separate throughput speeds for actual printing or downstream processing. The present disclosure may integrate considerations for printing, finishing, assembly, and other manufacturing processes into batch throughput for greater efficiency and overall speed.

[0085] Nesting optimization in currently used digital printing processes is around 60%-70%, compared to 80%-95% in traditional apparel manufacturing. raw material optimization( raw material 5% to 20% of the total waste) raw material Nesting optimization needs to be improved in the digital printing space to make the process sustainable and feasible at a commercial scale. This disclosure demonstrates the use of optimized nesting of components produced on demand to achieve 80% to 95% waste reduction. raw material Utilization rates can approach the efficiency of conventional manufacturing.

[0086] FIG. 5 shows an example set of clothing items illustrating nesting. A first clothing item 500 may include two sets of colors. The first color may comprise the top half of the first clothing item 500. The second color may comprise the bottom half of the first clothing item 500. A second clothing item 502 may include two sets of colors. The top right half of the second clothing item 502 may include the second color. The bottom left half of the second clothing item 502 may include the third color. A third clothing item 504 may include one color, i.e., the second color. A fourth clothing item 506 may include one color, i.e., the first color. A fifth clothing item 308 may include one color, i.e., the third color.

[0087] Nesting may include arranging the clothing items 500, 502, 504, 506, 508 so that adjacent borders of the clothing items 500, 502, 504, 506, 508 may be similar in color. The third clothing item 506 may be arranged adjacent to the top half of the first clothing item 500. The lower left half of the second clothing item 502 may be arranged adjacent to the fifth clothing item. Two or more of the bottom half of the first clothing item 500, the upper right half of the second clothing item 502, and the third clothing item 504 may be arranged adjacently.

[0088] In an illustrative example, garment parts may be transferred and / or stacked (aggregated) using a mechanical arm (or robot). A plurality of such mechanical arms with corresponding end effectors may comprise a pick-and-place production line. The pick-and-place process (which involves transferring and stacking) is typically much slower than other processes in the envisioned system and may be considered a "bottleneck." However, the process may be improved using a nesting protocol that takes into account the specific arrangement and transfer characteristics of the mechanical arms to maximize throughput. Nesting arrangements may be, for example, Fabric properties (e.g., porosity, stiffness, etc.), fabric The nesting arrangement may be varied depending on the type of processing to be applied, the desired web speed, and any additional operations performed by the mechanical arm. Initiating the nesting arrangement may be performed by a human or by nesting software. As the pick-and-place operation is performed, the mechanical arm may send feedback to the computer, which may result in a modified nesting arrangement that maximizes overall throughput and / or pick-and-place speed.

[0089] As an example, garment parts may be grouped into sizes, e.g., small and large, etc. The grouping threshold and number of groups may be determined for a particular operation or desired output. textile raw materialsAs far as pick and place is concerned, different pick and place approaches may be used for small parts compared to the approaches used for larger parts. Special nesting can be created to account for the various time delays associated with any particular mechanical arm (e.g., adjusting the size and arrangement of the grippers so that a large part can be picked up immediately after a small part). The pick and place systems described above may be configured with nesting optimization to allow the system to handle multiple smaller parts at once or in series in a timely manner. The pick and place system may be configured with nesting optimization to handle individual large parts or a mixture of small and large parts. The pick and place system may be configured with nesting optimization to handle individual large parts or a mixture of small and large parts. The pick and place system may be configured with nesting optimization to handle throughput speed and fabric To maximize utilization, it may be configured using nesting optimization. Other optimizations may also be used.

[0090] Component Manufacturing FIG. 6 shows an exemplary diagram of a component manufacturing process. At 600, a printed fabric But it may be accepted. fabric may have been printed in the printing step at 158 ​​in FIG. fabric may have been dried in a post-printing drying step at 166 in FIG. fabric may include a custom upper portion of the shoe. fabric may contain rows and / or columns, where each row and column combination may contain identical prints. fabric May contain cotton canvas.

[0091] 602, Fabric may be finished. fabric Finishing the fabric This may include steaming the fabric may be steamed in a fixing / steaming step at 170 in FIG. fabric Finishing the fabricThis may include cleaning the fabric may be cleaned in a post-printing cleaning step at 174 in FIG. fabric Finishing the fabric This may include drying the fabric may be dried in a post-printing drying step at 178 in FIG.

[0092] 604, liner fabric The liner may be applied to fabric The back of the device may be glued to the back of the device. fabric may be a printed and finished cotton canvas. Alternative or additional methods may be used.

[0093] 606, and the components are fabric It may be judged by. fabric A laser, router, or knife may be used to cut the components. Partial chads may remain on the cut components. Each row and column combination may be cut completely.

[0094] 608, completely cut off fabric Combinations (rows and columns) may be stacked. fabric Yes, there is fabric Partially cut components of layers stacked on top and / or bottom fabric The stacked layers may be aligned with the corresponding partially cut components of the layers. fabric may be sent to an assembler for assembly.

[0095] Color Control Traditional coloring methods rely primarily on manual processes involving multiple, time-consuming iterations of trial and error. The present disclosure combines precise substrate property data, chemical profiles from inks by color, and precise wet finishing data to anticipate the extensive trial and error process.

[0096] Traditional design tools are fragmented, incompatible, and in many ways completely disconnected from the manufacturing process, requiring an extended trial and error process to produce a design, creating the need to create modifications to the original design in order to manufacture. This disclosure provides customers, designers, and other end users with feasible designs and raw material Includes an integrated manufacturing job file creation feature that presents only the attributes and filters out colors and characteristics that are not acceptable within the acceptable performance attributes and standards, thereby seamlessly creating a manufacturing job file directly from the input design.

[0097] Typically, this is done as a separate, ad-hoc step, as a post-processing QA / QC function, which is too time-consuming and too far removed from the coloring process. Other manufacturers fail to integrate upstream and downstream data in the value chain: desired final color, substrate construction, and subsequent wet processing and lamination processes. This disclosure integrates this into our in-line coloring and fixing process to proactively inform color match and repeatability.

[0098] Pretreatment Forms Application fabric Industry Direct-to- fabric In digital printing, pre-treatment chemicals are applied in the form of open widths through a process called padding. fabric This applies to fabric The entire surface is immersed in the chemicals and the excess is squeezed out before the chemicals dry / set. fabric The amount of water absorbed by fabric ranges from 70% to >100% by weight (known in the industry as "wet pick-up") before further processing. fabric All of this moisture must be evaporated during drying, an energy-intensive process. Another problem with traditional padding of pretreatment chemicals is that in most cases the chemicals are only needed on the surface to be printed. fabricTherefore, traditional processes require the use of more energy, water, and chemicals than are needed to add value in subsequent steps. fabric The industry is the second largest consumer of freshwater in the world and one of the largest polluters of surface water after agriculture. The industry is exploring new ways to reduce its consumption of water, energy and chemicals.

[0099] Chemical foam applications have been used commercially for decades. Fabric In the nascent digital printing industry, production rates have increased to a level that has caused the industry to grow rapidly and attract attention from the investment community. In this disclosure, the process provides benefits such as reduced energy consumption, reduced water consumption, reduced chemical consumption, more precise application of chemicals as needed, and reduced chemical loads on wastewater treatment systems. fabric It involves pre-treatment chemistry applied via a foam applicator which has several advantages that are important to the industry: It has also been demonstrated that darker, richer colors can be achieved with the foam application process compared to traditional processes.

[0100] Figure 7A shows positive results from foam application pretreatment across four preliminary chemical formulations. These preliminary formulations demonstrate higher average results in many categories compared to the average results of the control case or conventional process. R is the decimal reflectance at the wavelength of maximum absorption (20% R = 0.20 R).

[0101] All four samples (3C, 5B, 2B, and 2D) were foam-applied, and the results were compared to the corresponding conventional padded or padded samples. For example, samples 3C and 5B were compared to a padded sample (Pad 1 below), and 2B and 2D were compared to another padded sample (Pad 2 below).

[0102] An SWL value >100% associated with a foamed sample means that a higher color yield was achieved with that foam formulation and conditions, at least compared to the conventional sample.

[0103] Figure 7B illustrates the positive results for four different chemical formulations, where 2B and 2D demonstrate similar performance results to the baseline control case, and 3C and 5B demonstrate improved performance over the control and other formulation variable results.

[0104] The present disclosure includes formulations for treating foam such as (although other chemicals may be used): [Table 1]

[0105] Durable water repellent (DWR) foam treatments may be used. As an example, Figure 7C shows a DWR formulation with specific parameters for foam application to a polyester substrate, demonstrating improved performance with a 50% reduction in chemical savings and an 80-85% reduction in chemical consumption.

[0106] Referring to Figure 7D, fabric 7 illustrates a method for preprocessing the image data. fabric may be accepted. raw material The manufacturer, fabric Step 138 of FIG.

[0107] In step 720, it is printed. fabric A selection region of may be determined. raw material The manufacturer prints fabric Step 140 of FIG.

[0108] In step 730, the applicator fabricThis may be caused by application of a foam chemical to the selected area. raw material The manufacturer has fabric A foam chemical may be applied to the selected area of ​​the fabric The application of foam chemicals to the area may be minimized. Step 140 of FIG.

[0109] In step 740, fabric The selected areas may be dried so that the surface of the selected areas can be printed. raw material The manufacturer may then select areas of the surface to be printed on. fabric The selected area may be dried. Step 140 of FIG.

[0110] raw material The manufacturer: fabric and a corresponding job file. The job file may include: fabric The user may indicate that a particular area of ​​the image needs to be printed. raw material The manufacturer: fabric Form pre-processing may be performed on specific areas of the raw material The manufacturer: fabric A specific area of ​​the surface may be dried. raw material The manufacturer will follow the instructions in the job file. fabric This may cause printing of specific areas of the image.

[0111] Plasma pre-cleaning / activation To optimize chemical wetting and adhesion, textile raw materials These applications require thorough cleaning (e.g., durable water-repellent finishes, stains, polymer coatings, laminations, etc.). Due to increasing environmental regulations surrounding the use of solvents and surfactants, it is becoming increasingly difficult to achieve the same level of cleanliness obtained with the harsh chemicals of the past (e.g., solvents). fabricMost cleaning in the world is water-based, using large amounts of heat energy and the most benign detergent chemicals possible. Unfortunately, modern cleaning systems, while environmentally friendly, fabric Contaminants that may interfere with the color and finish of fabric It is not possible to maintain a contaminated state. fabric Applying chemicals to the surface can result in a loss of performance, a decrease in the durability of the functional finish, or a decrease in the pass rate. fabric This often leads to the need to use more chemicals than would be necessary if the surface were completely clean. fabric and / or raw material By varying the surface chemistry and topography of raw material Each plasma carrier gas can provide a different surface chemistry and surface topography.

[0112] According to the present disclosure, the corona plasma process uses an ionized gas to: fabric Contaminants (oil, wax, etc.) on surfaces can be vaporized (decomposed). This is a water-free process and can be done with water-based chemicals. fabric and / or raw material By modifying the surface chemistry and surface energy of the surface, a cleaner surface is obtained that is easier to "wet out." Corona plasma units improve chemical penetration (wettability) and fabric It can be placed before a chemical application step to help activate the surface. Plasma can be used to improve the performance of some chemical applications (e.g., DWR) as well as achieve darker, more saturated colors using fewer dyes and chemicals.

[0113] Referring to Figure 8, fabric 8 illustrates a method for preprocessing a fabric may be accepted. raw material The manufacturer, fabric Step 138 of FIG.

[0114] In step 820, fabric At least part of this is done using plasma fabric may be conditioned to remove one or more contaminants from at least a portion of the raw material Manufacturers use plasma to fabric to remove one or more contaminants from at least a portion of fabric At least a portion of the above may be adjusted. fabric Adjusting at least a portion of fabric The surface of the substrate may be activated. The plasma may include corona plasma. Step 140 of FIG. 1 may include step 820. Step 146 of FIG. 1 may include step 820.

[0115] In step 830, one or more chemicals are fabric may be applied to at least a portion of raw material The manufacturer, fabric 1 may include step 830. Step 146 of FIG. 1 may include step 830. fabric Surface activation is achieved by applying one or more chemicals to the same surface. fabric The activated surface may improve the performance of one or more chemicals compared to the non-activated surface.

[0116] raw material The manufacturer, fabric Contaminants are present in certain areas of fabric You may receive: raw material Manufacturers may use plasma to remove contaminants in specific areas. raw material The manufacturer: fabric To activate specific areas of fabric One or more chemicals may be applied to a specific area of ​​the skin.

[0117] Digital coloring Drop-on-demand (e.g., digital printing) In the apparel industry, traditional products are currently manufactured under a predictive model where wholesalers and retailers order apparel and footwear against forecasts before consumers actually purchase the final product. In this scenario, products are produced in large batches of inputs (e.g., fabric etc. raw material ), which are successively broken down into smaller and smaller batches until the final step, whereby the final product is completed as a "single batch" unit. An illustrative example is shown in Figure 9B. In this system, the unique identifier of the final product is not assigned until the very last step in the process. In one scenario where products are manufactured under a "mass customization" model, a consumer may purchase the final product before it is manufactured. In this model, it is important to identify each component of the final product throughout the manufacturing process in order to track the order from inception to delivery. Identifying each component can occur in a digital printing step using a unique identifier such as a barcode or QR code. However, most consumers do not want the unique identifier to be visible on the final product. An illustrative example is shown in Figure 9B. Furthermore, raw material Utilization rate is raw raw material is a key driver of efficient and sustainable use of raw material To solve the identification problem without using a unique identifier, a unique identifier needs to be placed on each component in a way that is legible but not visible to the consumer.

[0118] In the present disclosure, quality control may be performed through invisible registration points, such as using invisible ink that is visible via computer vision or some other process. Current systems and methods may embed data through unique dithering patterns. For example, the present disclosure includes the application of unique identifiers using methods that are readable during the manufacturing process from digital printing to the point of sale, yet are “invisible” to consumers (e.g., barcodes, QR codes, illustrative examples shown in FIG. 9B). The present disclosure includes the use of unique identifiers that are applied to each component using invisible ink that is readable by machine vision, but that uses ink that is outside the visible spectrum of human perception (e.g., ultraviolet, infrared, etc.).

[0119] Attributes and Traceability In the apparel industry, "large-scale" industrial production does not support digital custom manufacturing driven by consumer-generated or aggregated content. Managing unique single-unit workflows that can be used to make and prove product and component provenance claims requires a complete set of data that can be traced from the point of creation to the point of sale. fabric A digitally generated marking system is required for components so that the markings can be linked to the entire value chain through manufacturing integration and intelligence systems. In this disclosure, systems and methods may embed customer order data with visible and non-visible attributes via digital printing using visible and / or non-visible codes.

[0120] A method for attribution and / or traceability may include receiving order data associated with one or more original consumer orders, wherein one or more unique identifiers (UIDs) are identified as: raw materialThe one or more unique identifiers may be invisible to the human eye and may be visible with the aid of a predetermined vision method. The one or more unique identifiers may represent item data including at least a portion of the order data. The one or more methods may include, for forming at least a portion of the item through one or more manufacturing processes, raw material The article data, represented by one or more unique identifiers, may be updated based on each manufacturing process to include information associated with the respective manufacturing process. Each of the manufacturing processes (or one or more of the manufacturing processes) may include reading the article data and adjusting one or more actions associated with the respective manufacturing process based on the article data. The article data may indicate the origin of the article. As used herein, article data may be or include other data, such as nesting data, order data, color data, etc.

[0121] The method for attribution and / or traceability may include receiving order data associated with one or more original consumer orders, wherein one or more unique identifiers are: raw material The one or more unique identifiers may be configured to be visible to the human eye and hidden through one or more manufacturing processes. The one or more unique identifiers may represent item data, including at least a portion of order data, or other data. One or more methods may be used to form at least a portion of an item through one or more manufacturing processes and to hide at least a portion of the one or more unique identifiers. raw material The item data, represented by the one or more unique identifiers, may be updated based on each manufacturing step to include information associated with the respective manufacturing step. Each of the manufacturing steps (or one or more of the manufacturing steps) may include reading the item data and adjusting one or more actions associated with the respective manufacturing step based on the item data. The item data may indicate the origin of the item.

[0122] Digital marking of apparel / footwear components requires unique and / or serialized unique markers (e.g., FIG. 9B ) that are large enough to be legible via machine vision (guaranteed legibility) to enable automated manufacturing. The size of the digital markers varies depending on the substrate; for example, very flat substrates can be marked with smaller markers due to the physical composition of the flat surface, while substrates with a high degree of Z-texture (e.g., sucker weave, waffle knit) require relatively larger markers due to the physical composition of light reflected from the substrate surface. In the present disclosure, a manufacturing integration and intelligence system (MII) may generate a unique digital identifier (e.g., QR code, barcode) that is generated to be reliably legible according to data collected about a given substrate. The present disclosure may automatically select an appropriately sized marker based on the substrate data and the size of the printed component.

[0123] Current product storytelling requires months or years of planning in the upstream supply chain, whereby proving the provenance of inputs (e.g., organic content, recycled content) is controlled through underwriting or legal documentation to manage risk against predetermined, digital chains of custody. As the market moves toward smaller batch sizes and greater customization, tracking the inputs and steps to make marketing claims becomes increasingly difficult. The disclosed systems and methods generate digitally accessible unique identifiers (e.g., QR codes, barcodes) to connect consumers to the history and provenance of end products, whereby the inputs and "ingredients" are compiled as the product moves through the supply chain and become accessible to the end consumer through interaction with the unique identifier (e.g., via mobile devices, scanners, digital cameras, etc.).

[0124] In the apparel and footwear industry, fabric The substrate is "designed" raw material However, there can be significant variations in the dimensional changes of the substrate through the manufacturing process steps, especially the finishing stages of processing. raw material Wetness of raw material Dimensional changes can be the result of a variety of factors, including mechanical forces during wet and dry processing, such as stretching or forming, thermal fixing, and permanent / semi-permanent changes in the thermoplastic substrate as a result of chemical application (e.g., coatings). Dimensional changes manifest not only at the macro level (batch to batch) but also at the micro level within a single yard or meter of substrate, making local predictions of dimensional changes unpredictable. Because of the aforementioned dimensional changes, the relationship of registration marks (applied in a previous process, e.g., by a digital printer) to the cutting process of individual components can change significantly throughout processing, resulting in cutting based on initial design dimensions resulting in out-of-specification components. To solve this problem, a much more robust process is needed to identify dimensional changes before cutting, providing accurate cutting and also providing a data feedback loop to improve dimensional change predictions and / or using machine vision to identify quality issues. fabric It is important to add dimensional reference points across the width and length of the web. Placing a high density of fiducial marks on the final product is not commercially acceptable to consumers, so marks that are invisible to consumers (outside the visual spectrum) but visible to machine vision are used. fabric This is important for high-speed single-layer cutting of apparel / footwear. Markers large enough to be reliably detected may be objectionable to the average consumer if said markings are visible on all components of the apparel / footwear product. In the present disclosure, invisible ink may be used to create registration points that track changes to the original pattern as a quality control measure. This is corrected during the cutting process, or the order is returned to the queue of pre-formatted job files and reproduced.

[0125] Conventional components are generally cut from monolithic prints, which creates wasted ink, finishing, and unused raw material (for example, fabric This disclosure provides a method for recycling unused materials (e.g., refrigerated vehicles, automobiles, and other components) that is difficult to recycle. fabric Precision application of finishes to enable recycling.

[0126] Adhesives are traditionally applied in a monolithic analogue manner, which creates high levels of waste in both cost and unused chemicals. raw material (for example, fabric or other components). The present disclosure may utilize digital printing / extrusion of adhesives using proprietary formulations to apply chemicals only when needed. The platform may identify visual alignment points, reference layers in a digital technology pack database, and use precision application of chemicals only to the required areas of each component-level (or designed) print.

[0127] Figure 9A presents an illustrative example of component-level printing combined with precision laser cutting for ease of assembly and automation. Demonstration of component-level engineered printing, nested as a pair and batched according to downstream processing, provides flexibility for downstream sewing and assembly, where custom printing offers advantages while downstream sewing and assembly are primarily commoditized in practice. Figure 9B demonstrates an example for QR codes for upstream and downstream traceability. The QR codes represent dithering patterns and are "invisible" in the formulation to contain underlying data for supply chain sustainability and CSR purposes, facilitate manufacturing through the shipping process, and create marketing and attribution opportunities. Figure 9C illustrates the incremental improvements demonstrated in the diagram. For example, precision cutting to leave chads uncut reduces direct labor costs while improving the quality and integrity of the underlying product compared to existing manufacturing methods. raw materialSavings. Figures 9D-E demonstrate an example of a traditional manufacturing process that was eliminated through the operational implementation of large-scale engineered print and digital manufacturing documentation. In this case, simply replacing the tag (with appropriate care and sizing information and necessary country of origin data) with digitally printed information eliminates the direct labor costs associated with manufacturing the item while simultaneously presenting an opportunity to prevent counterfeiting and the distribution of counterfeit goods.

[0128] Alternatively, or in addition to being used as a carrier of information, UIDs may be used to "screen" or evaluate process steps or processes. For example, if a particular UID has reflective properties, measuring the reflectance before application of the PU coating (the "process") and again after completion of the process will provide "local" or garment part-specific information regarding the thickness and / or quality of the applied PU coating. In other examples, the UID itself is modified (e.g., a color change or visibility change corresponding to the maximum and / or minimum temperatures used in the process or indicating a particular temperature range). Evaluation of other production process characteristics may be envisioned. These UIDs may be used to determine the seam allowance tolerance and / or seam tolerance of each garment part. fabric May be applied within the gutter area of ​​a role.

[0129] Wet Finish Traditional finishing processes are generally fragmented processes, physically and digitally separated from the printing process. The current state exhibits very long feedback loops. Currently, it is performed manually (especially from one site to another) with a high degree of variability. In this disclosure, an in-line spectrophotometer may be implemented to measure variability and create algorithms to optimize settings for on-premise and networked manufacturing. For example, the system and method may use the aggregated data to create a baseline recipe that can be adjusted for other manufacturing sites and their respective conditions, i.e., water quality, chemicals, ambient conditions, etc., reading data from previous processes and settings and writing conditions from this part of the process.

[0130] 10 shows an example diagram of a wet finishing process. The wet finishing process may include a process data collection 1000 and a product data collection 1050. The process data collection 1000 may receive and / or extract data from digital inputs and / or orders 1040. The process data collection 1000 may be in communication with the product data collection 1050.

[0131] The process data collection 1000 may include a process recipe database 1010. The process recipe database 1010 may include substrate data 1012, coloring data 1014, hand feel data 1016, finishing data 1018, etc. The process data collection 1000 may include data regarding various process steps, such as a substrate preparation step 1020, a substrate coloring step 1022, a substrate steaming step 1024, a substrate cleaning step 1026, a substrate curing step 1028, a substrate drying step 1030, a substrate functional finishing step 1032, and a substrate tumbling step 1034. The data regarding the various process steps may be obtained from a sensor. The data regarding the various process steps may be obtained from a spectrometer. The data regarding the various process steps may be obtained from an in-line spectrophotometer. The in-line spectrophotometer may measure the variation in the data regarding the various process steps. The measured variation in the data regarding the various process steps may be used to create an algorithm to obtain more optimal settings. The process data collection 1000 may include settings and / or conditions. The settings and / or conditions may result from direct performance outputs. The settings and / or conditions may be associated with in-line dryers, steamers, washers, stutter frames, etc.

[0132] The product data collection 1050 may include a product feedback collection 1060. The product feedback collection 1060 may include data regarding various aspects of the product, such as non-metameric color match feedback 1070, substrate hand feedback 1072, substrate breathability feedback 1074, substrate water permeability feedback 1076, substrate light reflectance feedback 1078, substrate heat absorbency feedback 1080, and substrate heat retention feedback 1082. The data regarding various aspects of the product may be obtained from a sensor. The data regarding various aspects of the product may be obtained from a spectrometer. The data regarding various aspects of the product may be obtained from an in-line spectrophotometer. The in-line spectrophotometer may measure variations in the data regarding various aspects of the product. The measured variations in the data regarding various aspects of the product may be used to create algorithms to obtain more optimal settings. The product data collection 1050 may include settings and / or conditions. The settings and / or conditions may result from direct performance outputs. The settings and / or conditions may be associated with an in-line dryer, steamer, washer, stunter frame, etc.

[0133] Digital Finishing Component-level application of DWR (e.g., fluoride-free or conventional fluoride) Traditional DWR processes are done in batches with a monolithic application of chemicals, whereby the chemicals are applied at the same level across the entire surface. textile raw materials The problem with this approach is that it ultimately becomes waste. raw materialThe challenge is that chemicals are used throughout the fabric and there is no way to control the level of water repellency with an "designed" approach to creating new performance applications. In this disclosure, digital application of DWR at the component level and in a roll-to-roll process allows for engineered patterns of moisture management that can be digitally enabled. This leads to a more sustainable process, thereby using fewer chemicals to create performance. It also reduces the waste generated after the cutting process. fabric are more easily recycled due to the waste being free of chemical contaminants, and the digital application of chemicals may enable new performance capabilities through engineered placement of chemicals that can be scaled across components of different sizes to allow customization of single units.

[0134] Designed application of chemicals The traditional application of chemicals is fabric covers a wide range of chemical waste and creates a large amount of unused fabric This disclosure demonstrates that precise digital application of chemicals, such as adhesives, reduces chemical usage, saves costs, and prevents the recycling of unused materials. fabric This may enable recycling of

[0135] Cutting Typical conventional methods cut pre-programmed patterns from monolithic prints, requiring repetition of set component patterns, leading to wasted ink and hindering scaled customization. In this disclosure, dynamic recognition of cutting patterns enables increased overall throughput, reduced waste, and mass customization.

[0136] textile raw materialsCurrent automated single layer cutting in the industry does not have sufficient throughput to scale in the apparel / footwear industry. Conventional techniques generally utilize gantry-driven X / Y axis instruments with mechanical knives and sometimes laser energy. The systems and methods of the present disclosure may utilize high speed galvanometer-driven lasers that have two orders of magnitude higher throughput than gantry-driven systems. Figure 11 shows an example of an existing conventional fabric 1 illustrates the design of an early high-speed single-layer galvanometer-driven laser cutting prototype that goes far beyond cutting methods.

[0137] Traditional wet finishing processes, such as post-print steaming, washing, and stenting, are nonlinear and difficult to consistently predict. fabric These distortions create distortions in the part, especially in knits. These distortions hinder the ability to print both patterns and components precisely and consistently. The disclosed system and method can match a database of pre-selected component shapes and patterns and make cutting adjustments to correct observed shape distortions while adjusting recipe changes for the next print iteration. Figure 12 is the feed portion of Figure 11, where vision recognition and real-time job file correction data is collected and transmitted.

[0138] Printing at the component level creates inefficiencies in downstream sorting and handling where the designed printed components cannot be deciphered from the waste. The systems and methods of the present disclosure may nest prints and cut components so that the unused substrate remains attached as a web. This web of unused substrate is reeled off the belt, and the associated cut components are sorted, kitted, and assembled, effectively batching and recycling the waste. Figure 13 illustrates nip rollers for waste removal and subsequent downcycling or recycling.

[0139] Traditional cutting methods involve manually cutting components with analog mechanical tools, or using gantry-driven knives, routers, or lasers. raw material This labor-intensive process creates significant inefficiencies, especially with regard to customization. The disclosed system and method provides unique customized ordering, batch processing, and nesting with precision laser cutting, leaving connecting chads to hold them together and allow manual separation from the block.

[0140] A method for cutting registration uses computer vision to raw material The one or more methods may include analyzing the first pattern configuration disposed on the printed raw material The method may include performing a finishing process on the printed pattern, resulting in a second pattern configuration that is different from the first pattern configuration. raw material The one or more methods may include analyzing a second pattern configuration disposed on the printed surface. The one or more methods may include determining cutting control information based on the first pattern configuration and the second pattern configuration. raw material The finishing process may include transmitting cutting control information to a cutting system to facilitate cutting of the. The cutting system may include a high speed single layer galvanometer driven laser cutting system. raw material and raw material and raw material and drying the finished product. The finishing process may include a digital finishing process. The cutting control information includes: raw material One or more methods may be used to batch one or more customer orders. In units Batching and printing based on batches raw material and nesting multiple article components within the item component.

[0141] Cutting method: batch one or more customer orders In unitsThe method may include batching, nesting a plurality of article components based on the batch, and cutting the nested components from the substrate such that one or more tabs connect the cut components to a portion of the substrate. Prior to the cutting step, the method may include analyzing a first pattern configuration disposed on the substrate using computer vision, performing a finishing process on the substrate, resulting in a second pattern configuration different from the first pattern configuration, analyzing the second pattern configuration disposed on the substrate using computer vision, and determining cut control information based on the first pattern configuration and the second pattern configuration. The cutting step may be performed based at least on the cut control information. The cutting step may be performed using a high-speed galvanometer-driven laser cutting system to cut a single layer. The finishing process may include: raw material Steaming raw material or raw material or drying. The finishing process may include one or more of belt forming, mechanical forming, decatizing, sponging, sandhorizing, mitigation drying, continuous tumbling, or batch tumbling. The finishing process may include one or more of sueding, shearing, raising, open width forming, tubular forming, calendering, vaporizing, sponging, atmospheric plasma finishing, continuous secatizing, semi-continuous decatizing, clubbing, coating, laminating, embossing, tension-free drying, mitigation drying, tentering, stentering, napping, brushing, singing, beetling, heat setting, heat fusing, filling, digital printing, roller printing, scutching, sputtering, or burnishing. The cutting control information may include one or more of: raw material Type of raw material thickness of raw material mass per unit area of, raw material porosity, or yarn properties raw material It may depend on the characteristics.

[0142] FIG. 14 shows an exemplary diagram of the laser cutting process. At 1400, fabricmay be observed. fabric is digitally printed fabric It may be digitally printed. fabric may include a pattern. Robot vision may be used to capture the pattern dimensions. The captured pattern dimensions may include original pattern dimensions. The captured pattern dimensions may include unfinished pattern dimensions.

[0143] At 1402, fabric The finishing process is fabric may be carried out. fabric The finishing process is fabric This may include steaming the fabric may be steamed in a fixing / steaming step at 170 in FIG. fabric The finishing process is fabric This may include cleaning the fabric may be cleaned in a post-printing cleaning step at 174 in FIG. fabric The finishing process is fabric This may include drying the Fabric The print may be dried in a post-print drying step at 178 in FIG. fabric may undergo conventional and / or digital finishing processes. fabric The finishing process involves modified pattern dimensions. fabric This may result in:

[0144] At 1404, fabric The change in the robot vision can be observed. fabric After the finishing process fabric may be used to capture the pattern dimensions. fabric After the finishing process fabric The captured pattern dimensions may include modified pattern dimensions. fabric After the finishing process fabricThe captured pattern dimensions may include the finished pattern dimensions. The modified pattern dimensions may be compared to the original pattern dimensions to obtain deltas (e.g., changes, modifications, etc.). The deltas may be provided to a laser control system. The laser control system uses the deltas to perform more accurate and precise laser control. Fabric You can cut the pattern from

[0145] Referring to Figure 15, a method for cut registration is illustrated. In step 1510, a printed fabric The first pattern configuration arranged on the surface may be analyzed using computer vision. raw material Manufacturers use computer vision to fabric A first pattern configuration disposed on the

[0146] In step 1520, the finishing process is printed. fabric may be performed, resulting in a second pattern configuration that is different from the first pattern configuration. raw material The manufacturer printed fabric A finishing step may then be performed, resulting in a second pattern configuration that is different from the first pattern configuration.

[0147] In step 1530, the printed fabric The second pattern configuration arranged on the may be analyzed using computer vision. raw material Manufacturers use computer vision to fabric A second pattern configuration disposed on the

[0148] In step 1540, cutting control information may be determined based on the first pattern configuration and the second pattern configuration. raw material The manufacturer may determine the cutting control information based on the first pattern configuration and the second pattern configuration.

[0149] In step 1550, the printed fabric Cutting control information may be sent to the cutting system to facilitate cutting. raw material The manufacturer printed fabric Cutting control information may be sent to the cutting system to facilitate cutting.

[0150] raw material The manufacturer will fabric may be received. raw material The manufacturer: fabric Computer vision may be used to capture the original printed design. fabric may undergo a finishing process. raw material The manufacturer: fabric Computer vision may be used to capture the modified print design. raw material The manufacturer may use the original print design and the modified print design to determine the delta. raw material The manufacturer may provide the deltas to the cutting system, which may use the deltas to cut the modified print design. fabric may be cut.

[0151] raw material handling fabric Traditional automation methods for handling and kitting functions within the apparel industry are highly specialized to specific product applications. Traditional apparel and footwear assembly lines are capital intensive and product specific, requiring low labor costs and high volume and throughput to justify the investment. This investment threshold is prohibitively steep for most businesses and generally prevents manufacturing operations in high-cost developed markets.

[0152] In this disclosure, as illustrated in Figures 16-17, the automated kitting and assembly design creates a flexible platform that can be reconfigured for different product types and categories, as well as the ability to adjust to variations in throughput speed and volume for each. For example, pick-and-place robot types (e.g., SCARA vs. Delta) at variable density and overlap radii by using an overhead rail system. Throughput speed / volume can be adjusted by using a tray and sorting system, which allows pieces to be dynamically sorted into stacks of similar components or as batched orders in a manner that simplifies the problem set navigated through vision recognition and minimized mechanical travel distances. Other examples of the platform's agility can be found in interchangeable end effectors (electrostatic, water, vacuum, etc.) that account for substrate types, expanded conveyors to manage larger cut components, and trays that can be swapped into envelopes for off-site assembly of custom orders elsewhere.

[0153] Traditional material management processes remain siloed and disconnected from printing, nesting, and batch processing considerations. This creates extreme cost inefficiencies, especially when printing at the component level. This disclosure addresses the end-to-end manufacturing value chain as a closed system and feedback loop.

[0154] Web defect tracking method In current systems, there may be multiple "subsystems" (printers, steamers, cutters, etc.). Each of the subsystems may produce defects in certain instances. For example, one of the printers may misprint, or ink may smear by physical contact with an object. Another example is a steamer configured to run the wrong recipe, rendering it unusable. fabric In another example, the operator may create a segment of the role. fabric A user might choose to cut a segment of a garment and then reconnect it (via stitching). Such alterations can be recorded and communicated to designated subsystems so that, for example, a cutter accurately and precisely cuts garment parts from the web and / or a mechanical arm knows which and where the expected parts are.

[0155] Therefore, if the nesting program (e.g., after running the nesting protocol) fabric A UID may be applied along the "gutter" area of ​​the roll. The UID may be a scannable barcode, data matrix, or equivalent. fabric Other UIDs may be used. For example, a unique identifier may be created every 5 inches (using identical copies of the UIDs contained in other parallel gutters); alternatively, these UIDs may be spaced in any other regular pattern along the gutter. Each UID (virtual fabric The spaces between virtual segments (slices) are sometimes called "segments" and contain printed garment parts or graphic designs. The nesting program may record the specific garment parts or graphic designs contained within each virtual segment (i.e., between two consecutive UIDs). Note that some of the parts in a particular segment may not be "all" because portions of the parts are contained in the segments immediately following or immediately preceding the current segment.

[0156] As an illustrative example, when a defect is detected, one of the following actions is performed: 1) The operator: fabric The defective segment is cut off and two UIDs are scanned (one before the defective area and one immediately after the defective area), fabric Reconnect the device. 2) fabricNo cutting is performed. An operator (or camera) scans two UIDs containing the defect area (which may span multiple segments). Other operations may be performed. Information from the scanned UIDs may be communicated to a computer system that makes appropriate adjustments to the main nesting file to exclude the cut segments in subsequent operations (e.g., cutting). Additionally or alternatively, information about the parts (and / or graphic designs) contained within the defect area may be saved. The saved information may be used to Fabric raw materials Further defect data may be added along with other defect data from other rolls. At the end of the production process (or at any time), the saved information may be sent back to the nesting software, which collects and re-nests the "missing" parts. Once the parts are nested, the production process (i.e., printing, steaming, cutting, etc.) continues until all required parts have been produced. Alternatively or additionally, the same process as above may be performed, but with the UIDs placed between the nested parts instead of in the gutter.

[0157] The present disclosure includes at least the following aspects.

[0158] Aspect 1: A method for item management, comprising: receiving consumer data including at least biometric information associated with one or more consumers; receiving design input indicating a design of an item, where the design of the item is based on the consumer data; triggering output of interactive content to a user interface associated with the one or more consumers, where the interactive content includes at least a representation of the design of the item; and outputting manufacturing data indicating instructions associated with manufacturing the item, where the instructions are based on the design of the item.

[0159] Aspect 2: The method of aspect 1, wherein the consumer data further includes consumer preference information.

[0160] Aspect 3: The method of aspect 1, further comprising receiving coloring data indicating coloring feasibility, wherein the design of the article depends on the coloring data.

[0161] Aspect 4: The method of aspect 1, wherein outputting the manufacturing data includes outputting at least a portion of the manufacturing data to a digital printing system.

[0162] Aspect 5: A method for direct-to-manufacturer item management, comprising: receiving consumer data including at least biometric information associated with one or more consumers; receiving design input indicating a design of an item, where the design of the item is based on the consumer data; automatically generating a pattern including one or more components of the item and one or more components of a second item; and outputting manufacturing data indicating instructions associated with manufacturing the item, where the instructions are based on the pattern.

[0163] Aspect 6: The method of aspect 1, wherein automatically generating the pattern includes performing nesting optimization.

[0164] Aspect 7: A method for product development, comprising: receiving consumer data including at least biometric information associated with one or more consumers; receiving trend data indicating trends in one or more of product design or product coloration; triggering output of one or more design options via a user interface based on at least the consumer data and the trend data; and receiving design input indicating a design for the product.

[0165] Aspect 8: The method of aspect 7, wherein the consumer data further includes consumer preference information.

[0166] Aspect 9: One or more design options are fabric The method of embodiment 7, comprising the type:

[0167] Aspect 10: One or more design options are available fabric 8. The method of embodiment 7, wherein the method is limited based on:

[0168] Aspect 11: Design of articles and fabric 8. The method of embodiment 7, further comprising generating a technology pack based on the selection of.

[0169] Aspect 12: fabric Based on the design of raw material The method of embodiment 7, further comprising outputting an invoice in the case of

[0170] Embodiment 13: A method for color control, the method comprising: receiving data indicative of one or more characteristics of a substrate for use in forming an article; selecting a chemical profile or a finishing process, or both, based on the data indicative of the one or more characteristics of the substrate; and forming at least a portion of the article using the selected chemical profile or finishing process, or both.

[0171] Embodiment 14: The method of embodiment 13, wherein the article exhibits a color within the acceptable range of the design color.

[0172] Aspect 15: A method of color control, comprising: performing a first step of a plurality of article management steps to output a first-stage article; capturing color data associated with the first-stage product using an in-line spectrophotometer; comparing the color data to expected data; and performing remediation based at least on comparing the color data to the expected data.

[0173] Aspect 16: fabric A method for pretreating fabric and printed fabric Determine the selected area and apply it to the applicator. fabric applying a foam chemical to the selected area of ​​the fabricThe application of foam chemicals to the selected areas is minimized so that the surface can be printed on in selected areas. fabric and drying the selected area of ​​said substrate.

[0174] Aspect 17: fabric A method for pretreating fabric and fabric using a plasma to remove one or more contaminants from at least a portion of fabric Adjust at least a portion of fabric modifying one or more of the surface chemistry and topography of at least a portion of fabric and applying one or more chemicals to at least a portion of the surface.

[0175] Aspect 18: fabric adjusting at least a portion of the fabric Activates the surface of fabric surface activation by applying the same one or more chemicals fabric 20. The method of embodiment 17, wherein the activated surface of the substrate is activated with one or more chemicals to improve performance compared to a non-activated surface of the substrate.

[0176] Aspect 19: A method for attribution and / or traceability, comprising placing one or more unique identifiers on at least a portion of an article, wherein the one or more unique identifiers are invisible to the human eye and become visible with the aid of a predetermined vision method, and wherein the one or more unique identifiers are referenced during a manufacturing process, including digital printing, to provide quality control data for one or more steps in the manufacturing process.

[0177] Embodiment 20: The method of embodiment 19, wherein the one or more unique identifiers indicate one or more alignment mechanisms for one or more components of the article.

[0178] Aspect 21: A method for attribution and / or traceability, comprising placing one or more unique identifiers on an item, the one or more unique identifiers comprising an invisible component that is invisible to the human eye and becomes visible with the aid of a predetermined vision method, and a visible component that is visible to the human eye, the one or more unique identifiers indicating at least attribute data.

[0179] Aspect 22: The method of aspect 21, wherein the attribute data includes information indicative of the origin of the item.

[0180] Embodiment 23: A method for component level application of a surface of an article, comprising: raw material and then use digital printing or digital extrusion to apply the product only to that location. raw material and selectively disposing the raw material is not disposed on at least a portion of the article.

[0181] Aspect 24: raw material The method of embodiment 23, wherein the adhesive comprises an adhesive.

[0182] Aspect 25: The method of aspect 23, wherein the selectively positioning is based on alignment points associated with the article.

[0183] Aspect 26: A method for cutting registration, comprising: fabric analyzing a first pattern configuration disposed on the printed fabric and implementing a finishing process to produce a second pattern configuration different from the first pattern configuration, and using computer vision to fabric analyzing a second pattern configuration disposed on the printed surface; determining cutting control information based on the first pattern configuration and the second pattern configuration; fabric and transmitting cutting control information to a cutting system to facilitate cutting of the

[0184] Aspect 27: A method of cutting one or more customer orders into a batch In units 1. A method comprising: batch processing; nesting a plurality of article components based on the batch; and cutting the nested components from the substrate such that one or more tabs connect the cut components to a portion of the substrate.

[0185] Aspect 28: raw material 1. A method of handling, comprising: raw material arranging the trays and sorting system with an overhead rail system configured for handling; raw material Receives components and distributes them to multiple locations based on component type and / or batched orders using an arrayed tray and sorting system and overhead rail system. raw material and reordering the components.

[0186] Aspect 29: A system for implementing any one of the methods of aspects 1 to 28.

Claims

1. 1. A system-implemented method for component pattern cut registration, the system including a textile laser cutter, a computer network, a vision system, and one or more of a textile printer and a textile pick and place unit, the method comprising: batching one or more customer order batches; arranging a pattern of a plurality of components of one or more articles based on the batch unit, including arranging two or more components of the plurality of components having similar or the same color and / or pattern at a boundary such that boundaries of the patterns of the two or more components are adjacent to each other; using computer vision to analyze a first pattern configuration of a component pattern of the plurality of component patterns printed on a printed textile material, the printed textile material comprising a fabric; performing a finishing process on the printed textile material, resulting in a second pattern configuration of the component patterns that is different from the first pattern configuration; and analyzing the second pattern configuration printed on the printed textile material using computer vision; and determining cut control information based on analyzing the first pattern configuration and the second pattern configuration, the cut control information being dependent on a difference between the second pattern configuration and the first pattern configuration, and the difference between the second pattern configuration and the first pattern configuration being at least partially due to a distortion of a pre-distorted print pattern or image on the printed textile material, depending at least on a finishing process; transmitting the cutting control information to a cutting system to facilitate cutting of the printed textile material; and causing the cutting system to cut the printed textile material based on the cutting control information.

2. 1. A system-implemented method for cut registration, the system including a textile laser cutter, a computer network, a vision system, and one or more of a textile printer and a textile pick and place unit, the method comprising: batching one or more customer orders in batches; arranging a pattern of a plurality of components of one or more articles based on the batch, including arranging two or more components of the plurality of components having similar or the same color and / or pattern at a boundary such that boundaries of the patterns of the two or more components are adjacent to each other; using computer vision to analyze a first pattern configuration of a component pattern of the plurality of component patterns printed on a printed textile material, the printed textile material comprising a fabric; performing a finishing process on the printed textile material, resulting in a second pattern configuration different from the first pattern configuration; and analyzing the second pattern configuration printed on the printed textile material using computer vision; and determining cut control information based on analyzing the first pattern configuration and the second pattern configuration, the cut control information being based on a difference between the second pattern configuration and the first pattern configuration, and the difference between the second pattern configuration and the first pattern configuration being at least partially due to distortion of a pre-distorted print pattern or image on the printed textile material, depending at least on a finishing process; and transmitting the cutting control information to a cutting system to facilitate cutting of the printed textile material.

3. The method of claim 2 , wherein the cutting system comprises a laser cutting system.

4. 3. The method of claim 2, wherein the finishing step comprises steaming the feedstock.

5. 3. The method of claim 2, wherein the finishing step comprises washing the raw material.

6. 3. The method of claim 2, wherein the finishing step comprises drying the raw material.

7. The method of claim 2 further comprising arranging a plurality of article components on the printed textile stock based on the batch unit.

8. 1. A method of cutting implemented by a system including a textile laser cutter, a computer network, a vision system, and one or more of a textile printer and a textile pick and place unit, comprising: analyzing a first pattern configuration of a pattern of components printed on a textile material using computer vision; subjecting the textile material to a finishing process that results in a second pattern configuration that is different from the first pattern configuration; and analyzing the second pattern configuration printed on the textile material using computer vision; and determining cut control information based on the first pattern configuration and the second pattern configuration, the cut control information being based on a difference between the second pattern configuration and the first pattern configuration, and the difference between the second pattern configuration and the first pattern configuration being at least partially due to distortion of a pre-distorted print pattern or image on the printed textile material, depending at least on a finishing process; batching one or more customer orders in batches; and arranging components of a plurality of articles based on the batch, including arranging a pattern of the plurality of components, wherein two or more components of the plurality of components having similar or the same color and / or pattern at their boundaries are arranged so that boundaries of the patterns of the two or more components are adjacent to each other.

9. 9. The method of claim 8, wherein the finishing step comprises one or more of steaming the feedstock, washing the feedstock, or drying the feedstock.

Images