DE202018105003U1 - System integration for the design and manufacture of apparel - Google Patents

Abstract

System based on a computer system for supplying ready-made or custom made or e-tailor made textile products made from synthetic or natural fibers, comprising:
Means for receiving a first set of a plurality of body measurement input variables, which are biometric metrics of a customer to be equipped with at least a first textile product,
Means for processing the first set of the plurality of body measure input variables in a predictive model to predict a second set of at least 2, 4, 6, or 8 estimated body measures, each of the estimated body measures being derived from two or more of the input variables;
Means for deriving a fit quality value for the first textile product which may be a ready-made or made-to-measure and e-tailor made textile product as a function of the first set of the plurality of body size input variables and the second set of at least two , 4, 6 or 8 estimated body measurements,
Means of rejecting all ready-made or made-to-measure textile products that do not conform to the fit quality standard,
and, when a ready-made or made-to-measure textile product conforms to the fit quality value, means for sending this finished or custom made textile product to the customer are provided while the customer is otherwise sent the e-tailor-made product.

Description

The present invention relates to system integration methods for the design, sale and manufacture of apparel in particular, as well as to the system itself, particularly for the online ordering of apparel articles, without the need for a tailor to measure in advance by a customer but through e-commerce platforms, portals and markets, customers can access the online sales of high quality, well-fitting apparel.

background

The demand among consumers for individually designed products, the z. For example, being purchased online and featuring higher quality or greater functionality, unlike ordinary off-the-shelf products, is durable. A recent study shows that while less than 10% of customers interested in fashion products have tried online customization options, between 25% and 30% of the total population would like to try it out.

The 2017 final report on the European Commission's e-commerce competition investigation shows that 64% of the surveyed manufacturers have opened their own Internet shop over the past 10 years. This means that custom-designed online fashion is currently only available through smaller web stores that are not integrated with the major B2C (e-commerce) platforms, portals and markets. This is a limitation because it is not possible for the mass clientele to buy well-fitting, personalized clothing over the Internet. In addition, one of the most annoying problems with the current online B2C platforms is that 75% of the menu filter searches result in inappropriate or unavailable stock unit proposals and most customers are given no further product or size recommendations. For example, if a (filtered) search is performed in the "Shirts" category, it may happen that only one shirt is suggested by the system for a dress shirt with 5 cm shorter sleeves; for a 5 cm longer striped leisure shirt size XL with tight fit only 3 shirts are proposed, of which 2 are short-sleeved. For wide-cut, large shirts XL size with long sleeves, the seller allegedly has nothing left in store. The main reason for this is that traders need to make an increasingly fragmented offer to many different audiences to meet the specific needs of customers: Wide & wide, slim / waisted / normal / very slim fit, dainty / plus sizes, different sleeve lengths (eg short / long / extra long / extra short) etc. Also, different materials can be used, such as non-iron Materials, synthetic fibers, silk or cotton materials, dyed and yarn-dyed patterns, striped and checkered, collars of different shapes and all these possibilities in different colors. Even shirts can easily be more than 1000 designs. The stocking of all these sizes, colors and materials does not make economic sense.

• Halsumfang: Zum Herstellen von Krägen und Halsausschnitten für Hemden wird der Hals gemessen. Zum Messen des Halsumfangs wird ein Maßband von vorne Mitte bis vorne Mitte um den Hals gelegt, wobei das Maßband faltenfrei und ohne zu ziehen senkrecht zum Ausschnitt gehalten wird.
• Schulterbreite: Es kann auf zweifache Art gemessen werden: zum Einen kann die Schulterlänge durch Messen von der hohen Schulter- oder Halsspitze bis zur Schulterspitze am Armanfang gemessen werden. Bei einer anderen Methode wird die Rückenbreite von einer Schulterspitze zur anderen gemessen.
• Armlochumfang: Das Armloch wird zur Ärmelherstellung gemessen. Das Armloch (das Loch in einem Hemd, durch das der Arm gehen muss) wird gemessen, indem das Maßband faltenfrei und ohne zu ziehen ausgehend von der Schulterspitze unter die Achselhöhle und zurück zum Ausgangspunkt gelegt wird.
• Oberweite oder Brustweite: Die Ober- oder Brustweite wird für Hemden, Blusen, Jacketts usw. gemessen. Das Maßband wird, faltenfrei und ohne zu ziehen, ausgehend von der vorderen Mitte um den breitesten Teil der Brust und zurück zum Ausgangspunkt gelegt.
• Apex oder Brustpunkt ist der höchste Punkt oder die Spitze der Brust. Das Messen des Brustpunkts dient zum Herstellen von Abnähern. Gemessen wird von der hohen Schulterspitze am Hals zum Apex, und die Breite des Brustpunkts ergibt sich aus dem Messen des Abstands zwischen zwei Brustpunkten.
• Vordere Mittellinie: ist eine Linie, die die vordere Körperseite in zwei gleiche Hälften unterteilt. Das Messen der vorderen Mittellinie dient der Bestimmung der Halshöhe. Gemessen wird von der Halsgrube in der Mitte der vorderen Körperseite bis zur Taille, wobei sichergestellt wird, dass das Maßband faltenfrei ist und nicht daran gezogen wird.
• Hintere Mittellinie: ist eine Linie, die die hintere Körperseite in zwei gleiche Hälften unterteilt. Das Messen der hinteren Mittellinie dient der Bestimmung der Halshöhe. Gemessen wird von der Halsgrube in der Mitte der hinteren Körperseite bis zur Taille, wobei sichergestellt wird, dass das Maßband faltenfrei ist und nicht daran gezogen wird.
• Seitennaht: ist eine Linie, die den Körper seitlich in zwei Hälften unterteilt, d. h. eine vordere und eine hintere. Das Messen der Seitennaht dient der Bestimmung der Armlochtiefe. Gemessen wird von der Achselhöhle bis zur Taille, wobei sichergestellt wird, dass das Maßband faltenfrei ist und nicht daran gezogen wird.
• Taillen- oder Bauchweite: Die Taille wird für Hemden, Blusen, Jacketts usw. gemessen. Die Taille ist der schmalste Teil der natürlichen Körpertaille. Die Taille wird gemessen, während die Person in natürlicher Haltung und ohne eingezogenen Bauch und normal atmend aufrecht steht, indem das Maßband faltenfrei und ohne zu ziehen ausgehend von der Mitte der vorderen Körperseite um die Taillenbiegung herum und zurück zur vorderen Mitte gelegt wird.
• Hüftweite: Die Hüftweite wird für Hemden, Jacketts usw. gemessen. Die Hüftweite wird gemessen, indem das Maßband faltenfrei und ohne zu ziehen ausgehend von der Mitte der vorderen Körperseite über den breitesten Teil der Hüfte und zurück zur vorderen Mitte gelegt wird.
• Ärmellänge: Die Ärmellänge wird ausgehend vom Oberarm an der Schulterspitze gemessen, indem die Länge bis zum Handgelenk oder weiter, je nach gewünschter Ärmellänge, gemessen wird, wobei sichergestellt wird, dass das Maßband faltenfrei ist und nicht daran gezogen wird.
• Bizepsumfang: Das Messen des Bizeps dient der Ärmelherstellung. Gemessen wird an der breitesten Stelle des Oberarms um diesen herum, wobei sichergestellt wird, dass das Maßband faltenfrei ist und nicht daran gezogen wird.
• Ellenbogenumfang: Das Messen des Ellenbogens dient der Ärmelherstellung. Gemessen wird um den gebogenen Ellenbogen herum, wobei sichergestellt wird, dass das Maßband faltenfrei ist und nicht daran gezogen wird.
• Handgelenkumfang: Das Messen des Handgelenks dient der Ärmelherstellung. Gemessen wird um das Handgelenk herum, wobei sichergestellt wird, dass das Maßband faltenfrei ist und nicht daran gezogen wird.

The human body has complicated geometrical shapes and leads to difficulties in producing tailor-made textile products. In most cases, 50% of online sales are currently being returned; sometimes the return rate is 70%. Manufacturers of tailored clothing typically insist on the need for relevant and correct measurements. For example, shirts measure:

• Neck circumference: The neck is measured to make collars and necklines for shirts. To measure the neck circumference, a tape measure is placed around the neck from the center front to the center front, with the tape measure kept wrinkle-free and perpendicular to the neckline without pulling.
• Shoulder width: It can be measured in two ways: on the one hand, the shoulder length can be measured by measuring from the high shoulder or toe peak to the shoulder tip at the beginning. Another method measures back width from one shoulder to the other.
• Armhole circumference: The armhole is measured for sleeve production. The armhole (the hole in a shirt through which the arm has to go) is measured by placing the tape measure under the armpit and back to the starting point, wrinkle-free and without pulling, starting from the top of the shoulder.
• Bust or bust: The top or bust is measured for shirts, blouses, jackets, etc. The tape measure is laid, wrinkle-free and without pulling, from the front center around the widest part of the chest and back to the starting point.
• Apex or breast point is the highest point or the top of the breast. Measuring the breast point is for making darts. It is measured from the high shoulder tip on the neck to the apex, and the width of the breast point results from measuring the distance between two breast points.
• Front midline: is a line dividing the front side of the body into two equal halves. The measurement of the anterior midline serves to determine the neck height. Measure from the neck pit in the middle of the front of the body to the waist, making sure the tape measure is wrinkle-free and not pulled at it.
• Rear midline: is a line that divides the back side of the body into two equal halves. The measurement of the posterior midline serves to determine the neck height. Measured from the neck pit in the middle of the back of the body to the waist, making sure that the tape measure is wrinkle-free and not pulled at it.
• Side seam: is a line dividing the body sideways into two halves, ie one front and one rear. The measurement of the side seam serves to determine the armhole depth. Measure from the armpit to the waist, making sure that the tape measure is wrinkle-free and not pulled at it.
• Waist or Waist: The waist is measured for shirts, blouses, jackets, etc. The waist is the narrowest part of the natural body waist. The waist is measured while the person is standing upright in natural posture and with no stomach in and breathing normally, by laying the tape measure around the waist bend and back to the front center, wrinkle-free and without pulling from the center of the front body side.
• Hip width: The hip width is measured for shirts, jackets, etc. The hip width is measured by placing the tape measure wrinkle-free and without pulling from the center of the front body side over the widest part of the hips and back to the front center.
• Sleeve Length: The sleeve length is measured from the upper arm at the tip of the shoulder by measuring the length to the wrist or further, depending on the desired sleeve length, ensuring that the tape measure is wrinkle-free and not pulled.
• Bicep girth: Measuring the bicep is used to make the sleeve. Measure around the widest part of the upper arm around it, making sure the tape measure is wrinkle-free and not pulled.
• Elbow circumference: Measuring the elbow is used to make the sleeve. Measure around the curved elbow, making sure the tape measure is wrinkle-free and not pulled at it.
• Wrist circumference: Measuring the wrist is used to make the sleeve. Measure around the wrist, making sure the tape measure is wrinkle-free and not pulled at it.

Experience has shown that the average online customer does not perform these measurements correctly or does not want to execute them.

• ein erfahrenes Team von Spezialisten
• persönliche Beratung und persönliches Maßnehmen
• bereits zur Verfügung stehende Kleidungsmuster
• einen umfangreichen Bestand, aus dem Kleidung ausgewählt werden kann
• einen internen maßgeschneiderten Design- und Herstellungsservice
• einen internen Service für die kundenspezifische Gestaltung.

Usually a custom tailor has:

• an experienced team of specialists
• personal advice and personal measures
• already available clothing samples
• an extensive inventory from which clothes can be selected
• an internal bespoke design and manufacturing service
• an internal service for custom design.

Several of them are difficult to integrate into online shopping.

There are currently no "system integrators" for high-quality, individually designed, ie tailor-made fashion. The ICT systems integrators currently only serve the mass production market, using the Made to Stock (MTS) strategy, so that brand manufacturers and distributors are deployed existing software such as Hybris (SAP), Intershop, Amazon Services, Websphere (IBM), Magento, Prestashop, Amazon Services or Demandware can sell (online) their products.

Brief description of the present invention

It is an object of embodiments of the present invention to provide technical support to a creative industry, and particularly to the fashion industry, by utilizing digital processes under the control of digital processors. The technical tools are used for biometric sizing, product configuration, 3D product representation and manufacturing integration using APIs. Thanks to embodiments of the present invention, all sellers and customers are able to benefit from technical sizing and configuration resources. Consumers can benefit from a standardized fit that is as accurate as technically possible and from means of accessing inventory availability. Advantageous are fewer returns and less waste. There are resources available for ICT integration.

In embodiments of the present invention, a first API is used to assist in biometric sizing and fit prediction. Means are provided for forecasting biometric measures and sizes. Sizing tables of, for example, e-cutters are used to determine fit criteria in combination with a limited number of measurements made by the customer. Help is available for deciding whether a standard or custom-made or e-tailor-made product would work best. The decision support may be a derived fit quality value.

In embodiments of the present invention, an API is used for 3D configuration and display of garment items as well as custom biometrically tailored garments.

In embodiments of the present invention, an API is used for manufacturing integration that allows automatic generation of both CAD and CAM datasets.

Embodiments of the present invention may be configured as an API micro-service architecture, the APIs being accessible for easily incorporating new functionality into existing platforms.

• Empfangen von Produktdesigndaten, die Parameterwerte über mindestens ein erstes Textilprodukt und/oder eine begrenzte Anzahl biometrischer Messdaten eines Kunden, der das mindestens eine erste Textilprodukt tragen soll, umfassen, wobei die Produktdesigndaten von einer ersten Software eines ersten Verkäufers bereitgestellt werden,
• Mapping dieser Produktdesigndaten auf Werte einer zweiten Software eines Herstellers von Textilprodukten, wobei das Mapping durch Folgendes erfolgt:
  • eine erste API für biometrische Messdaten und Größenprognose auf der Grundlage einer Größentabelle, ferner umfassend Mittel zum Bestimmen, inwieweit die erste Textilproduktgröße zu den biometrischen Messdaten passt, und gestatten, dass der Kunde angeben kann, ob er ein fertig lieferbares oder ein nach Maß gefertigtes oder ein e-maßgeschneidertes Produkt kaufen will.

One aspect of the present invention is a process for producing ready-made and / or custom-made textile products of synthetic or natural fibers characterized by the following steps:

• Receiving product design data comprising parameter values about at least a first textile product and / or a limited number of biometric measurement data of a customer who is to carry the at least one first textile product, the product design data being provided by first software of a first seller,
• Mapping of this product design data to values of a second software of a textile product manufacturer, the mapping taking place by:
  • a first API for biometric measurement data and size prediction based on a sizing chart, further comprising means for determining how the first textile product size matches the biometric measurement data, and allowing the customer to indicate whether it is a finished or made to measure or wants to buy an e-tailor-made product.

A second API can serve the 3D configuration of ready-to-deliver or custom-made or e-tailor-made products, as an option, to allow fully customized, biometrically tailored textile products.

A third API may be provided for the manufacturing integration of textile products with a manufacturing process. This API allows not only CRM and ERP, but also the automatic generation of CAD and CAM data to enable production.

• - Eingang einer digitalen Designspezifikation eines Textilprodukts von einer Designprognoseeinheit über ein Weitverkehrsdatennetz bei einem Hersteller,
• - Erhalt eines virtuellen Prototyps des Textilprodukts aus der Verarbeitung der eingegangenen Designspezifikation und,
• - Erhalt einer Konvertierung des virtuellen Prototyps in einem Format, das mit einem additiven und subtraktiven Bearbeitungssystem kompatibel ist,
• - Erhalt eines Materials, aus dem das Textilprodukt zu fertigen ist, und
• - Erhalt des Textilprodukts durch Formen unter Einsatz des additiven und subtraktiven Bearbeitungssystems.

The method may include the following steps:

• - Receipt of a digital design specification of a textile product from a design prediction unit via a long haul data network at a manufacturer,
• - obtaining a virtual prototype of the textile product from the processing of the design specification received and,
• Obtaining a virtual prototype conversion in a format compatible with an additive and subtractive processing system,
• Obtaining a material from which the textile product is to be manufactured, and
• - Obtain the textile product by molding using the additive and subtractive processing system.

The textile product may be selected from woven, knitted or non-woven products made, for example, from a material selected from natural fibers, synthetic polymer fibers, metal fibers or the like.

The step of obtaining the textile product by molding using the additive and subtractive processing system may be performed by one, some or all of the following methods depending on the material selected and the design: cutting, stitching, crimping, folding, sewing, gluing, welding ,

The process may include a step of post-treating the textile product by ironing, starching, washing, pressing or the like.

In this processing step, any shrinkage of material may be taken into account as a result of the methods used during the manufacturing step.

• Empfangen eines ersten Satzes einer Vielzahl von Körpermaßeingabevariablen, bei denen es sich um biometrische Messdaten eines Kunden handelt, der mit mindestens einem ersten Textilprodukt ausgestattet werden soll,
• Verarbeiten des ersten Satzes der Vielzahl von Körpermaßeingabevariablen in einem Prognosemodell zur Prognostizierung eines zweiten Satzes von mindestens 2, 4, 6 oder 8 geschätzten Körpermaßen, wobei jedes der geschätzten Körpermaße von zwei oder mehr der Eingabevariablen abgeleitet wird,
• Ableiten eines Passformqualitätswerts für das erste Textilprodukt, bei dem es sich um ein fertig lieferbares oder nach Maß gefertigtes und e-maßgeschneidertes Textilprodukt oder um jedes davon handeln kann, als Funktion des ersten Satzes der Vielzahl von Körpermaßeingabevariablen und des zweiten Satzes von mindestens 2, 4, 6 oder 8 geschätzten Körpermaßen,
• Zurückweisen von allen fertig lieferbaren oder nach Maß gefertigten Textilprodukten, die dem Passformqualitätswert nicht entsprechen,
• und, wenn ein fertig lieferbares oder nach Maß gefertigtes Textilprodukt dem Passformqualitätswert entspricht, Schicken dieses fertig lieferbaren oder nach Maß gefertigten Textilprodukts an den Kunden, während dem Kunden sonst das e-maßgeschneiderte Produkt geschickt wird.

Embodiments of the present invention provide a method for providing ready-made or custom made or e-tailor made textile products made from synthetic or natural fibers, the method comprising the steps of:

• Receiving a first set of a plurality of body measurement input variables that are biometric measurement data of a customer to be equipped with at least a first textile product,
• Processing the first set of the plurality of body measure input variables in a predictive model to predict a second set of at least 2, 4, 6, or 8 estimated body measures, each of the estimated body measures being derived from two or more of the input variables;
• Deriving a fit quality value for the first textile product which may be a ready-made or made-to-measure and e-tailor made textile product as a function of the first set of the plurality of body size input variables and the second set of at least 2, 4 , 6 or 8 estimated body measurements,
• Rejection of all ready-made or made-to-measure textile products that do not conform to the fit quality standard
• and, if a ready-made or made-to-measure textile product conforms to the fit quality value, sending that finished or custom-made textile product to the customer while otherwise sending the e-tailor-made product to the customer.

The first set of a plurality of body measure input variables may be provided by a first vendor software.

This first set may be mapped to a third set of values of second software of the forecast model, the mapping being done by transferring the plurality of body measure input variables through a first API.

The fit quality value may be derived for any or all ready-made or made-to-measure and e-tailor made textile product from a size prediction based on a sizing chart, thereby allowing the customer to indicate whether a finished or custom made textile product or an e-tailor-made product is acceptable.

A 3D configuration for the finished, custom-made or custom-made product can be provided through a second API.

Both CAD and CAM data for enabling manufacturing can be automatically generated via a third API for manufacturing integration of the custom-made or custom-made product using a manufacturer's manufacturing process.

The manufacturer may obtain a digital design specification of a textile product from a design unit via a long haul data network.

The obtained design specification can be processed to obtain a virtual prototype of the textile product.

The virtual prototype can be converted to a format that is compatible with an additive and subtractive editing system.

A material may be obtained from which to make the textile product (eg, the customer may indicate a particular material), and the textile product may be obtained by molding using the additive and subtractive processing system.

The step of obtaining the textile product by molding using the additive and subtractive processing system may be performed by one of the following methods, depending on the material selected: cutting, stitching, flanging, sewing, etc.

A step of finishing the textile product by ironing, starching, washing, pressing, etc. may be performed.

The variety of body size input variables may be selected from weight, height, girth, and additional input variables, age and gender.

The second set of at least 2, 4, 6, or 8 estimated body measurements can be selected from KMI, chest circumference, waist circumference, arm circumference, wrist circumference, shoulder length, arm length, back length, and abdominal or waist circumference.

The customer may be provided with a representation of the three-dimensionally displayed virtual prototype.

The customer may be provided with a representation of a three-dimensional (3D) virtual person according to the estimated body measurements carried by the textile product.

• Mittel zum Empfangen eines ersten Satzes einer Vielzahl von Körpermaßeingabevariablen, bei denen es sich um biometrische Messdaten eines Kunden handelt, der mit mindestens einem ersten Textilprodukt ausgestattet werden soll,
• Mittel zum Verarbeiten des ersten Satzes der Vielzahl von Körpermaßeingabevariablen in einem Prognosemodell zur Prognostizierung eines zweiten Satzes von mindestens 2, 4, 6 oder 8 geschätzten Körpermaßen, wobei jedes der geschätzten Körpermaße von zwei oder mehr der Eingabevariablen abgeleitet wird,
• Mittel zum Ableiten eines Passformqualitätswerts für das erste Textilprodukt, bei dem es sich um ein fertig lieferbares oder nach Maß gefertigtes und e-maßgeschneidertes Textilprodukt oder um jedes davon handeln kann, als Funktion des ersten Satzes der Vielzahl von Körpermaßeingabevariablen und des zweiten Satzes von mindestens 2, 4, 6 oder 8 geschätzten Körpermaßen,
• Mittel zum Zurückweisen von allen fertig lieferbaren oder nach Maß gefertigten Textilprodukten, die dem Passformqualitätswert nicht entsprechen,
• und, wenn ein fertig lieferbares oder nach Maß gefertigtes Textilprodukt dem Passformqualitätswert entspricht, sind Mittel zum Schicken dieses fertig lieferbaren oder nach Maß gefertigten Textilprodukts an den Kunden bereitgestellt, während dem Kunden sonst das e-maßgeschneiderte Produkt geschickt wird.

Another aspect of the present invention is a computer-based system for providing ready-made or custom made or e-tailor made textile products made from synthetic or natural fibers, comprising:

• Means for receiving a first set of a plurality of body measurement input variables, which are biometric metrics of a customer to be equipped with at least a first textile product,
• Means for processing the first set of the plurality of body measure input variables in a predictive model to predict a second set of at least 2, 4, 6, or 8 estimated body measures, each of the estimated body measures being derived from two or more of the input variables;
• Means for deriving a fit quality value for the first textile product which may be a ready-made or made-to-measure and e-tailor made textile product as a function of the first set of the plurality of body size input variables and the second set of at least two , 4, 6 or 8 estimated body measurements,
• Means of rejecting all ready-made or made-to-measure textile products that do not conform to the fit quality standard,
• and, when a ready-made or made-to-measure textile product conforms to the fit quality value, means for sending this finished or custom made textile product to the customer are provided while the customer is otherwise sent the e-tailor-made product.

• Mittel zum Empfangen von Produktdesigndaten, die Parameterwerte über mindestens ein Textilprodukt und/oder biometrische Messdaten eines Kunden, der das mindestens eine erste Textilprodukt tragen soll, umfassen, wobei die Produktdesigndaten von einer ersten Software eines ersten Verkäufers bereitgestellt werden,
• Mittel zum Mapping dieser Produktdesigndaten auf Werte einer zweiten Software eines Herstellers von Textilprodukten, wobei die Mittel zum Mapping eine erste API für biometrische Messdaten und Größenprognose auf der Grundlage einer Größentabelle umfassen,
• ferner umfassend Mittel zum Bestimmen, inwieweit die erste Textilproduktgröße zu den biometrischen Messdaten passt, sowie Mittel zum Gestatten, dass ein Kunde angeben kann, ob er ein fertig lieferbares oder ein nach Maß gefertigtes oder ein e-maßgeschneidertes Produkt kaufen will.

Another aspect of the present invention is a computer-based system for providing ready-made or custom made or e-tailor made textile products made from synthetic or natural fibers, comprising:

• Means for receiving product design data comprising parameter values about at least one textile product and / or biometric measurement data of a customer who is to carry the at least one first textile product, the product design data being provided by first software of a first seller,
• Means for mapping this product design data to values of a second software of a textile product manufacturer, the mapping means comprising a first API for biometric measurement data and size prediction based on a sizing chart,
• and further comprising means for determining how the first fabric product size matches the biometric measurement data, and means for allowing a customer to indicate whether to buy a ready-made or custom-made product or a custom-made product.

Further embodiments of the present invention will be apparent from the appended claims.

Embodiments of the present invention may utilize an assembly for the manufacture of custom-made or customized clothing comprising a controller controlled by a processor and operatively coupled to a non-volatile memory and input means, the input means being is configured to provide the controller with input variables specific to a particular customer and the controller is adapted to process the input variables to predict a set of at least estimated body measurements, each derived from one or more of the input variables, and serve to derive garment pattern data, wherein one of the input variables comprises a representation of the age of the customer. The age can be a number of years, but it can also be any representation, such as the date of birth. This data does not need to be entered by the customer but can be entered by other means; For example, the age indication may be obtained from a provided date of birth or from electronically stored medical records. The age is preferably shown as a number of years.

The input variables may further include input of one or more or all of the following: weight, size, collar, sleeve length, and waist of the customer.

The predicted body measurements may further include at least one, some, or all (eg, 2, 4, 6, or 8) of the following: KMI, chest circumference, waist circumference, arm circumference, wrist circumference, shoulder length, arm length, and back length (B: KMI, CC : Chest circumference, WC: Waist circumference, AC: Arm circumference, WR: Wrist circumference, SL: Shoulder length, AL: Arm length and BL: Back length and optionally BC: Belly or waist circumference and any other measurements necessary to make the clothing.

The body measures may be predicted by reference to a plurality of the input variables and to a set of predictor rules that are applied under the control of the processor and the controller.

The predictor rules may associate the input variables with the customer body measures that are unknown to the controller and generate the estimated body measures for use in place of the unknown body measures.

The predictor rules may include the use of a regression technique, preferably a multiple linear regression technique.

The predictor rules may be derived from a database of body dimensions of a population cross-section, the cross-section being composed of a number of cases that is at least twenty times the variables to be entered and the body dimensions to be predicted.

The predictor rules may vary between at least two applications thereof, for example to account for cross-sectional changes over time between target markets or between geographic areas. The set of predictor rules can be generated whenever an order comes in, or whenever a reference database of body dimensions of the population cross section changes.

The custom-made or tailor-made clothing may include a shirt and may include a blouse or a jacket.

The custom-made or e-tailor-made clothing may include a pair of trousers, and the input variables may preferably include one or more of the following: foot size, shoe size, stride length, and seam size. At least in this case, the custom-made or e-tailor-made clothing may further include a jacket and optionally a vest in combination with the pants to form, for example, a suit.

The customer may enter an instruction relating to the structure of at least a portion of the garment, such as the type of material, color, fit, collar, cuff, or sleeve design, preferably by the customer Verification of a predicted or simulated finished garment can be changed.

The input means may comprise an input stage performed using at least one of the following: wide area network (WAN), local area network (LAN), mobile telecommunications network, Internet ordering, and interactive mail order, which are interactively performed by the customer in response to prompts from the supplier, for example become.

The assembly may further comprise a clothing manufacturing facility adapted to receive the pattern data from the controller and to fabricate the custom-made or customized clothing based thereon.

The assembly may further include an invoicing and distribution arrangement for sending invoices to customers and sending them customized or tailor-made clothing.

The customer may be provided with an illustration of the ready-to-wear, custom-made or custom-made clothing, wherein the virtual image is preferably displayed in three dimensions and is movable to show how the clothing may look from different angles or perspectives. The customer may also be provided with a representation of a virtual person, preferably having the body shape of the customer based on the estimated body measurements, wearing the ready-to-wear, custom-made or e-tailed garment according to the pattern data, preferably the three-dimensional person is shown and preferably movable to demonstrate how the clothing may look in use. This representation may be available to the customer in a variety of different postures and backgrounds, such as static or mobile in urban or rural environments, preferably with the possible presence of additional virtual figures. In this presentation, the customer may wear extra clothing beyond the custom-made or tailor-made clothing, such as in a case where the custom-made clothing includes a shirt; In this case, the extra clothing includes different trousers so that the customer can judge the clothes made according to specific instructions in various combinations and styles as an overall picture. The 3D configuration can be provided via an API.

Embodiments of the present invention further provide an assembly for the manufacture of garments made to a particular instruction comprising a controller operatively coupled to a non-volatile memory and input means, the input means being adapted to provide the controller with input variables suitable for are specific to a particular customer, and the controller is adapted to process the input variables to a set of predict at least estimated body measurements, each derived from one or more of the input variables, for deriving garment pattern data, wherein the input variables include only age, weight, height, and collar size of the customer.

Embodiments of the present invention further provide an information carrier, such as a CD-ROM, on which at least one program is encoded to facilitate implementation of an inventive arrangement.

The program may include, for example, a website interface and / or database of clothing options or dimensional information and / or a web browser and / or an ordering / billing system and / or a mapping program to enable display of an image of the custom-made clothing ,

Embodiments of the present invention further provide a method of making clothes made to specific instructions, comprising the steps of: a) inputting input variables specific to a particular customer into a controller, one of the input variables comprising a representation of the age of the customer, b ) Processing the input variables; and c) predicting a set of at least estimated body measurements from the processing, each of the body measurements being derived from one or more of the input variables and used in deriving clothing pattern data.

Embodiments of the present invention may also provide an arrangement in which, for example, in a database, a record of confirmations made in connection with orders placed using the invention is made.

These responses may be in the form of return guarantee information or customer feedback and may include positive or negative results or both. These records can also be used to record cases in which a customer could not or only with difficulty be satisfied. Such collected data could also serve to protect a supplier of clothing made according to particular instructions using the invention from customers who are difficult to satisfy, for example, by recording customers who often return goods for whatever reason.

list of figures

• 1 eine Schemazeichnung einer Anordnung nach einer Ausführungsform der vorliegenden Erfindung,
• 2 bis 5 grafische Darstellungen von bei der Entwicklung der Anordnung von 1 verwendeten Informationen,
• 6 und 7 weitere Schemazeichnungen einer Anordnung nach weiteren Ausführungsformen der vorliegenden Erfindung.

The present invention will now be described by way of example only with reference to the accompanying drawings. Show it:

• 1 a schematic drawing of an arrangement according to an embodiment of the present invention,
• 2 to 5 graphical representations of in the development of the arrangement of 1 used information,
• 6 and 7 further schematic drawings of an arrangement according to further embodiments of the present invention.

definitions

1. 1. "off the shelf" or "ready made" = ready-to-deliver items Off-the-rack clothing = ready-to-wear clothing is finished and manufactured in standard sizes in one plant and has a wide range of quality standards depending on the manufacturer.
2. 2. "Made to measure" Clothing made according to specific instructions based on a set block pattern. A paper cut pattern is usually not made. Rather, existing patterns that match the required ones are collected and compiled. Unlike bespoke clothing, no new patterns are made. All records can be kept for future orders.
3. 3. "tailor-made" e-tailor-made clothing refers to the use of customized paper cut patterns rather than the reuse of existing patterns. Custom made clothing can be made from a wide selection of fabrics, styles and accessories.

Preferably, all records for future orders are kept.

Description of the embodiments

Embodiments of the present invention relate to bringing customization and average mode together, thereby increasing current product diversity by incorporating biometric measurement data and size prediction technology into multi-channel e-commerce platforms and Internet shops of manufacturers, e-retailers, e-malls, e Markets, outlets and portals, with customization options embedded in the e-commerce platform software.

Embodiments of the present invention employ ICT system integration technology which enables consumers to purchase ready-to-go, custom-made or e-tailor-made fashion online, e.g. Over the Internet, anywhere, both online and multi-channel, as well as, for example, from their preferred mass-production manufacturers, allowing a seamless flow of information. Embodiments of the present invention provide central access points and avoid a lengthy logon process for accessing the various Web sites on which each platform module is developed. While there is keen consumer interest, the technical barriers to offering custom clothing to the public are still high. Embodiments of the present invention also utilize an API platform that allows consumers to benefit from standardized, readily available products while allowing consumers to do so, using technology currently available only in the sub-segment of custom-made and custom-designed apparel to get a good fit. Consumers can benefit from a standardized fit that is as accurate as technically possible. This approach will have a strong impact on the sector by bridging the distance to the correct size measurement and allowing the necessary move to a fashion industry without (hopefully) or with little waste, and in particular an improvement in the rate of returns after the online sale (which currently stands at an unacceptable 50% in most cases and 70% in some cases). Due to a lack of technical means, an improvement was not possible. Embodiments of the present invention implement more complex types of apparel using biometric sizing (such as shirts, blouses, jackets, etc.), further including a size prediction for each garment, e.g. B. legwear and upper body clothing, d. H. Shirts and pants, while at the same time also ready-to-deliver, tailor-made and e-tailor made garments are provided as alternatives. Embodiments of the present invention provide for system integration of multiple APIs. Embodiments of the present invention utilize operations via a web platform specific to the custom-made or e-tailor-made online textile products. In embodiments of the present invention, a manufacturer of custom-made online textile products or e-tailor-made online textile products is integrated into a collaborative API environment. Presently, unattainable levels of customer satisfaction and waste reduction can be achieved with embodiments of the present invention by guaranteeing an almost perfect fit for standardized (eg, ready-to-go) online products, custom-made online products, or e-tailor-made online products. which mitigates the problem that standard measures differ more than 25% from country to country.

1. 1) Daten von A holen
2. 2) Parameterwerte von Software B gleich Parameterwerte von Software A setzen
3. 3) Daten in B platzieren

API stands for "Application Programming Interface", and is used to integrate various software applications. A user uses a user interface to interact with the software and direct what actions to take. However, if one software application is to interact with another application, then an API can be used. In embodiments of the present invention, parameters are used to design clothing; the clothes can be further designed and manufactured with these parameters. If a multi-channel system is to be used then there must be a way disparate systems can communicate with each other. Suppose that information about biometric data entered by one customer and stored in a first non-volatile memory under the control of a first processor running Software A should be transmitted to another company and, in a second non-volatile one Memory under the control of a second processor running Software B, are stored. Since Software B is from another seller, it is extremely unlikely that the two applications have exactly the same fields and / or interpret them in the same way. To achieve this integration, therefore, the following is necessary: (a) a way to get the data easily and programmatically from A, (b) a way to get the data easily and programmatically from B, (c) a small program in the middle to prompt A to provide the data, stop it if necessary, and place it in B. A first API program running on A reads the contents of A (in the context in which it is stored in the first non-volatile memory in A), sends it to B, after which a second API program running on B puts it in the second non-volatile memory in B (in the way B expects to enter data). This process is called data mapping. To do this through APIs (assuming that both A and B and their respective applications have APIs and support), one would use the first API in A to fetch the data and then the second API in B to convert the data and write the data in B based on the mapping:

1. 1) Get data from A.
2. 2) Set parameter values of software B equal to parameter values of software A.
3. 3) Place data in B

After writing these conversion programs, the two software applications maintain communication. An important advantage of the API approach is that because of the writing of a small dedicated program, it is possible to validate and cleanse the data from the source software A before placing it in the destination software B, which makes it very easy known problem of dealing with corrupted data is eliminated. Finally, the API approach also allows any software to communicate with any other software, not just the one or two applications a vendor has chosen to support. This includes software that might not have existed at the time the application was created.

Therefore, APIs can be used to cause a company's software, e.g. For example, from large B2C (e-commerce) platforms, portals and markets such as Amazon, communicates with software from other smaller web shops. This is technically important because the specification data for making clothes must be exact. In embodiments of the present invention, APIs for collecting data from customers shopping through the large B2C (e-commerce) platforms, portals, and markets may be used to convey definitions of 3D objects so that they may can be viewed by the customer to collect data on sample designs, collect inventory and production plan data, provide data for billing and invoicing, etc.

Some APIs belonging to embodiments of the present invention are the following:

One or more APIs 22 . 26 biometric size transfer and size forecasting: A s-tailor's size chart tells a customer in advance how much a given size fits their measurements, and can decide whether to use a standard or bespoke or an e-tail tailor-made product buys.

An API 24 for 3D configuration for tailor-made or e-tailor-made products. This is a technical solution for resellers (e-tailors) who manufacture ready-to-go, mass-produced clothing to open their fully custom-fit biometric-fit garment platforms as an additional service on their existing platforms, without any New development of existing implementations would be necessary. This makes it possible to send the data required for 3D images to the seller's websites and / or to a customer for a 3D display.

One or more APIs 28 . 29 for manufacturing integration. This is a technical solution for seamlessly integrating the design and configuration results for the custom-made or custom-made products into a manufacturing process, for example, to allow automatic generation of both CAD and CAM to facilitate production.

A microservice API architecture 30 , which is a centralized or decentralized overall platform, using the APIs 22 . 24 . 26 . 28 . 29 for software developers to easily integrate new functionality into existing platforms (see 6 ). The microservice can be centralized, localized or decentralized.

The API environment of the microservice 30 allows third-party developers to add value to the fashion chain. In addition, embodiments of the present invention utilize historical size determination information (of the products themselves), biometric information (sizes of customers), custom-made and custom-tailored online product configuration systems, body mass index rating systems, etc., to an API SDK (Software Development Kit) Develop to create a library of interfaces that enable third-party developers to enable fashion manufacturers and consumers to enjoy less time-consuming shopping and better end-user shopping experiences.

Embodiments of the present invention assist customers in online shopping, even though i) the customer's personal taste is subjective and increasingly varied in fit and style, ii) apparel collection ranges and / or brand sizes are not the same for different collections, posing major problems in sizing caused.

Embodiments of the present invention may be based on the definition of a microservice architecture 30 (please refer 1 . 6 and 7 ) to integrate new functionality into the web shop of large e-retailers 32-35, regardless of the platform on which they were developed, solving the problem of proprietary software. Embodiments of the present invention provide a configuration and sales method after a size-fit predictor 40 has identified the best fit for each customer. Next, the system can run using the ERP and CRM APIs 29 check whether the article is in stock at the e-tailor; if not, the system suggests a manufacturer 16 commission the delivery of tailor-made or tailor-made textile products using, for example, the results of biometric sizing and predictor size prediction 40 , Embodiments of the present invention utilize ICT technologies in the area of size prediction, product configuration, custom-made and / or custom-made products, and industrialization (ie, manufacturing) for the provision of innovative products and services with high commercial potential in a creative industry. Embodiments of the present invention utilize mass data and semantics to analyze and update real-time size data and biometric formulas with resulting improved size table recommendations. Embodiments of the present invention allow the production of standard fashion products (MTS) and custom-made (MtM) and e-tailor-made products on a single platform 30 , Embodiments of the present invention allow the purchase of fashion brands in large ecommerce portals / websites and platforms 32-35 and lead multi-channel e-commerce (see 6 ) for standard fashion products (MTS) and bespoke (MtM) and e-tailor-made fashion products using existing platforms 32 - 35 one.

Embodiments of the present invention use an API 22 for the biometric size forecast. Thanks to the API 22 may be a limited set of biometric data in the website of a seller 32 - 35 can be entered, and this data can be sent to a size prediction service 40 be transferred. The size prediction service 40 can enter the biometric data into a size prediction model.

With reference to 1 to 7 For example, an assembly for the manufacture and distribution of custom-made clothing includes an input stage that is performed by a customer who has an interactive interface 10 under the control of a first processor 11 used by communicating through the internet with a web server 12 an online program (for example, on an internet or mail order basis) implemented and under the control of a second processor 13 an ecommerce portal / ecommerce web site or ecommerce portal 32 provides a factory of readily available and / or custom made and / or e-tailor-made articles as well as their invoicing, manufacturing and distribution. The ecommerce portal / site or platform facility may be located in different locations in different countries, such as Amazon.com, Amazon.us, Amazon.uk, etc.

A user of the interface 10 responds to requests for information and input variables that include specific information for a particular customer to order a ready-made or custom-made or e-tailor-made garment. In this embodiment, the ordered garment is a shirt or a blouse 18 for which the following input variables are provided: gender (female or male) G, age A, weight W, height H, and collar width C of the customer, where collar width is also referred to artificially as neck length N in the art.

At this stage, the customer gives under the control of the first processor 11 a command regarding its choice of the structure of at least a portion of the ordered clothing, such as material type, color, fit, collar, cuff or sleeve design.

Under the control of a second processor 13 captured the web server 12 the custom input variables and the choice made and stores them in a first nonvolatile memory 15 , Using an API system 22 for biometric measurements and size forecasting, the custom input variables and choice are made with any necessary conversion, addition, reduction or enhancement to a controller 14 a forecasting service provider 30 passed the customer's choice and the input variables G, A, W, H, C in a second non-volatile memory 17 under the control of a third processor 19 stores and processes rules in a forecasting model according to a set.

Using this set of rules says the controller 14 under the control of the processor 19 and using non-volatile memory 17 stored information is preceded by a set of body measurements, which is an estimate of the customer's unknown body measurements. The predicted body measurements include: B: KMI, CC: chest circumference, WC: waist circumference, AC: arm circumference, WR: wrist circumference, SL: shoulder length, AL: arm length and BL: back length, and optional BC: abdominal or waist circumference and any other measurements necessary for the production of clothing.

Under the control of the processor 19 can the controller 14 the complete set of body measurements into a set of clothing pattern data 25 convert. At this stage, the customer can be under the control of the processor 19 a depiction 20 of a virtual garment prototype that is under the control of the processor for the customer 11 according to the model chosen by the customer. The properties of the representation 20 of the virtual garment prototype are preferably interactively updatable to simultaneously reflect changes that could result in the customer's choice of structure and options. The representation is preferably carried out in three dimensions under the control of the processor 11 ; it is also movable so that it can be viewed from different angles.

The virtual representation 20 may be extended to the rendering of a virtual person who preferably represents the predicted body shape of the customer according to the estimated body measurements and who wears selected ready-to-wear clothing according to the choice made by the customer. Under the control of the processor 11 the virtual person is preferably three-dimensional ( 3D ) and is preferably movable to demonstrate how the clothing may look in use. Such virtual representations are known in the art, and a suitable example of this technology is taken from the EP0933728 out. Such a 3D configuration can be embedded in a multi-channel e-commerce platform that provides configuration sizing as a service. Thanks to the API 24 For example, the advantage can be exploited that proprietary 3D configurators provide details of 3D representations through the use of plug-ins 36, which are operated, for example, by the web services of the platform. The customer has the option of rejecting unwanted clothing, reducing costs and reducing returns. As explained below, this not only makes it possible to offer state-of-the-art, ready-to-go mass-produced products, but the customer also has the option of choosing fully tailored biometric-fit clothing as an advancement advantage over existing platforms product is not satisfied without the need to further develop existing implementations. This is already available at the tender stage, reducing the amount of bad-fitting clothing and reducing the number of returns.

Under the control of the processor 11 can the virtual representation 20 be available to the customer in a variety of different postures and backgrounds, such as static or mobile in urban or rural environments, preferably with the possible presence of additional virtual figures. Under the control of the processor 11 It may also be possible for the customer to use the shirt made according to special instructions 18 in addition to wearing additional clothing, such as a selection of pants. In this way, the customer can judge the shirt in various environments, combinations and styles as an overall picture. At this stage, the customer may change their choice in style or even in terms of fit by, for example, requesting another fit. After the selection made and the changes made to the simulation have been taken into account, the customer is asked to confirm or reject the order.

Under the control of the processor 19 then checks the controller 14 whether the shirt 18 is in stock or can be delivered as a custom-made or as an e-tailor-made shirt. Under the control of the processor 19 compares the controller 14 the set of body data such as A, W, H, C, B, CC, WC, AC, WR, SL, AL and BL and optionally also BC and optionally any other dimensions used to make the ready-to-wear garment, as the case may be Whether the customer is male or female, and any of the customer-made choices that were possible for the ready-to-deliver products offered by the ecommerce portal / ecommerce web site or platform, with those of the controller 14 provided predicted body data values such as A, W, H, C, B, CC, WC, AC, WR, SL, AL and BL and optionally also BC. This comparison is used to determine if the finished product is good enough and that of the controller 14 under the control of the processor 19 generated values are used as reference. Sizing tables 38 for standard finished products and block patterns may be used to obtain the data necessary for the comparison. This data, which includes the size tables 38, may be from an API 26 from the ecommerce portal / ecommerce web site or platform 32-35 if the data is stored there. The British standard BS3666, for example, sets the size determination system for the British clothing industry. All shops or vendors selling clothing in the United Kingdom market or manufacturers making clothing for the market adhere to BS3666. The suffix S or T at a size indicates whether the clothing is for a small or a tall person.

wobei E eine Fehlerschätzung ist und Δ sich auf eine Differenz zwischen den vorausgesagten Werten und den für die Größen von fertig lieferbarer Kleidung verwendeten biometrischen Abmessungen bezieht. Ein Beispiel wäre eine einfache Summe der Absolutwerte der Abweichungen für einen männlichen oder weiblichen Kunden: $$\begin{array}{l}\text{E}={\text{w}}_1\left|\mathrm{\Delta }\text{A}\right|+{\text{w}}_2\left|\mathrm{\Delta }\text{W}\right|+{\text{w}}_3\left|\mathrm{\Delta }\text{H}\right|+{\text{w}}_4\left|\mathrm{\Delta }\text{C}\right|\mathrm{+}{\text{w}}_5\left|\mathrm{\Delta }\text{B}\right|\mathrm{+}{\text{w}}_6\left|\mathrm{\Delta }\text{CC}\right|\mathrm{+}{\text{w}}_7\left|\mathrm{\Delta }\text{WC}\right|\mathrm{+}{\text{w}}_8\left|\mathrm{\Delta }\text{AC}\right|\\ {\text{w}}_9\mathrm{\Delta }\left|\text{WR}\right|\mathrm{+}{\text{w}}_{10}\left|\mathrm{\Delta }\text{S}\right|{\text{ w}}_{11}\left|\mathrm{\Delta }\text{AL}\right|\mathrm{+}{\text{w}}_{12}\left|\mathrm{\Delta {\rm B}}\text{L}\right|\text{ und wahlweise }\mathrm{+}{\text{w}}_{13}\left|\mathrm{\Delta }\text{B}\right|.\end{array}$$

wobei w_n eine Gewichtung ist. Die Gewichtung kann höher sein, wenn der Ist-Wert einer der Differenzen negativ ist, da ein Kleidungsstück, das zu klein ist, problematischer ist als ein Kleidungsstück, das etwas weiter ist.The comparison may serve to generate an error or "mismatched" estimate that may be a function of the differences between the predicted values and the ready-to-wear garment sizes depending on whether the customer is male or female, ie $$\begin{array}{l}\text{e}=f(\mathrm{\Delta }\text{A}.\mathrm{\Delta }\text{W}.\mathrm{\Delta }\text{H}.\mathrm{\Delta }\text{C}.\mathrm{\Delta }\text{B}.\mathrm{\Delta }\text{CC}.\mathrm{\Delta }\text{WC}.\mathrm{\Delta }\text{AC}.\mathrm{\Delta }\text{WR}.\mathrm{\Delta }\text{SL}.\mathrm{\Delta }\text{AL}.\mathrm{\Delta }\text{BL un}\text{d optional}\\ \mathrm{\Delta }\text{BC}).\end{array}$$

where E is an error estimate and Δ refers to a difference between the predicted values and the biometric dimensions used for the sizes of ready-to-wear garments. An example would be a simple sum of the absolute values of the deviations for a male or female customer: $$\begin{array}{l}\text{e}={\text{w}}_1\left|\mathrm{\Delta }\text{A}\right|+{\text{w}}_2\left|\mathrm{\Delta }\text{W}\right|+{\text{w}}_3\left|\mathrm{\Delta }\text{H}\right|+{\text{w}}_4\left|\mathrm{\Delta }\text{C}\right|\mathrm{+}{\text{w}}_5\left|\mathrm{\Delta }\text{B}\right|\mathrm{+}{\text{w}}_6\left|\mathrm{\Delta }\text{CC}\right|\mathrm{+}{\text{w}}_7\left|\mathrm{\Delta }\text{WC}\right|\mathrm{+}{\text{w}}_{\mathrm{8th}}\left|\mathrm{\Delta }\text{AC}\right|\\ {\text{w}}_9\mathrm{\Delta }\left|\text{WR}\right|\mathrm{+}{\text{<figure-callout id="10" label="w" filenames="DE202018105003U1\_0015.png" state="{{state}}">w</figure-callout>}}_{10}\left|\mathrm{\Delta }\text{S}\right|{\text{<figure-callout id="11" label="w" filenames="DE202018105003U1\_0015.png" state="{{state}}">w</figure-callout>}}_{11}\left|\mathrm{\Delta }\text{AL}\right|\mathrm{+}{\text{<figure-callout id="12" label="w" filenames="DE202018105003U1\_0015.png" state="{{state}}">w</figure-callout>}}_{12}\left|\mathrm{\Delta {\rm B}}\text{L}\right|\text{and optionally}\mathrm{+}{\text{<figure-callout id="13" label="w" filenames="DE202018105003U1\_0015.png" state="{{state}}">w</figure-callout>}}_{13}\left|\mathrm{\Delta }\text{B}\right|,\end{array}$$

where w _{n is} a weight. The weighting may be higher if the actual value of one of the differences is negative because a garment that is too small is more problematic than a garment that is slightly wider.

Instead of getting the relevant sizes for ready-to-wear clothes from the sellers, the values A, W, H, C, B, CC, WC, AC, WR, SL, AL and BL, and optionally BC, may be alternative for a customer from finished article manufacturers available on e-commerce portal / e-commerce website or platform 32-35. If the design of ready-made products also comes from the forecasting service provider and / or these products have been manufactured by third parties according to these designs, then the details are in control 14 to disposal.

Instead of E or a function of E, the inverse of E ( 1 / E ) can be used as a measure of how good the fit is. Regardless of whether E or an inverse of E is used, the result is a fit quality value. The present invention has a function that provides a fit quality value such as E, 1 / E, E ² , 1 / E ² .

If a finished item can not be recommended because the fit quality value, e.g. B. E, is above a threshold, then checks the controller 14 under the control of the processor 19 the tailor-made product, with existing samples from a manufacturer 16 can be produced. If there are suitable existing patterns, the controller transforms 14 the complete set of body measurements and the known pattern data under the control of the processor 19 into a set of clothing pattern data 25 , The familiar patterns can be through API 28 to be obtained. Under the control of the processor 19 the customer can choose a second presentation 20 one under the control of the processor 11 displayed virtual garment prototype according to the customer-selected model and manufactured according to standard patterns. As before, the properties of the representation 20 Preferably, the virtual clothing prototype is interactively updated to simultaneously reflect the changes in the game Structure choice and the options of the customer. Under the control of the processor 11 For example, the prototype is preferably displayed three-dimensionally and movably so that it can be viewed in different directions.

The virtual representation 20 may be extended to the rendering of a virtual person, which preferably represents the predicted body shape of the customer according to the estimated body measurements and that according to the control provided by the controller 14 generated pattern data carries selected clothes made according to special instructions. Under the control of the processor 11 the virtual person is preferably three-dimensional ( 3D ) and is preferably movable to demonstrate how the clothing may look in use. Such virtual representations are known in the art, and a suitable example of this technology is taken from the EP0933728 out.

The virtual representation 20 can be for the customer under the control of the processor 11 be available in a variety of different postures and backgrounds, such as static or mobile simulations in urban or rural environments, preferably with the possible presence of additional virtual figures. Under the control of the processor 11 It may also be possible for the customer to use the shirt made according to special instructions 18 in addition to wearing additional clothing, such as different pants. In this way, the customer can judge the shirt in various environments, combinations and styles as an overall picture. At this stage, the customer may change their choice in style or even in terms of fit by, for example, requesting another fit. After considering the selection made and the changes in the simulation, the customer is asked to confirm that the new prototype is preferred or rejected.

wobei E eine Fehlerschätzung ist und Δ sich auf eine Differenz zwischen den vorausgesagten Werten und den für die Größen von fertig lieferbarer Kleidung verwendeten biometrischen Abmessungen bezieht. Ein Beispiel wäre eine einfache Summe der Absolutwerte der Abweichungen für einen männlichen oder weiblichen Kunden: $$\begin{array}{l}\text{E}={\text{w}}_1\left|\mathrm{\Delta }\text{A}\right|+{\text{w}}_2\left|\mathrm{\Delta }\text{W}\right|+{\text{w}}_3\left|\mathrm{\Delta }\text{H}\right|+{\text{w}}_4\left|\mathrm{\Delta }\text{C}\right|\mathrm{+}{\text{w}}_5\left|\mathrm{\Delta }\text{B}\right|\mathrm{+}{\text{w}}_6\left|\mathrm{\Delta }\text{CC}\right|\mathrm{+}{\text{w}}_7\left|\mathrm{\Delta }\text{WC}\right|\mathrm{+}{\text{w}}_8\left|\mathrm{\Delta }\text{AC}\right|\\ {\text{w}}_9\mathrm{\Delta }\left|\text{WR}\right|\mathrm{+}{\text{w}}_{10}\left|\mathrm{\Delta }\text{S}\right|{\text{ w}}_{11}\left|\mathrm{\Delta }\text{AL}\right|\mathrm{+}{\text{w}}_{12}\left|\mathrm{\Delta {\rm B}}\text{L}\right|\text{ und wahlweise }\mathrm{+}{\text{w}}_{13}\left|\mathrm{\Delta }\text{B}\right|.\end{array}$$

wobei w_n eine Gewichtung ist. Die Gewichtung kann höher sein, wenn der Ist-Wert einer der Differenzen negativ ist, da ein Kleidungsstück, das zu klein ist, problematischer ist als ein Kleidungsstück, das etwas weiter ist.As described above, a fit quality value such as E, which is an error or a poor fit, may be calculated for the custom-made article by any of the methods set forth above. The error or "mismatched" estimate may be a function of the differences between the predicted values and the size values relevant to the custom-made garment, depending on whether the customer is male or female, ie $$\begin{array}{l}\text{e}=f(\mathrm{\Delta }\text{A}.\mathrm{\Delta }\text{W}.\mathrm{\Delta }\text{H}.\mathrm{\Delta }\text{C}.\mathrm{\Delta }\text{B}.\mathrm{\Delta }\text{CC}.\mathrm{\Delta }\text{WC}.\mathrm{\Delta }\text{AC}.\mathrm{\Delta }\text{WR}.\mathrm{\Delta }\text{SL}.\mathrm{\Delta }\text{AL}.\mathrm{\Delta }\text{BL un}\text{d optional}\\ \mathrm{\Delta }\text{BC}).\end{array}$$

where E is an error estimate and Δ refers to a difference between the predicted values and the biometric dimensions used for the sizes of ready-to-wear garments. An example would be a simple sum of the absolute values of the deviations for a male or female customer: $$\begin{array}{l}\text{e}={\text{w}}_1\left|\mathrm{\Delta }\text{A}\right|+{\text{w}}_2\left|\mathrm{\Delta }\text{W}\right|+{\text{w}}_3\left|\mathrm{\Delta }\text{H}\right|+{\text{w}}_4\left|\mathrm{\Delta }\text{C}\right|\mathrm{+}{\text{w}}_5\left|\mathrm{\Delta }\text{B}\right|\mathrm{+}{\text{w}}_6\left|\mathrm{\Delta }\text{CC}\right|\mathrm{+}{\text{w}}_7\left|\mathrm{\Delta }\text{WC}\right|\mathrm{+}{\text{w}}_{\mathrm{8th}}\left|\mathrm{\Delta }\text{AC}\right|\\ {\text{w}}_9\mathrm{\Delta }\left|\text{WR}\right|\mathrm{+}{\text{<figure-callout id="10" label="w" filenames="DE202018105003U1\_0015.png" state="{{state}}">w</figure-callout>}}_{10}\left|\mathrm{\Delta }\text{S}\right|{\text{<figure-callout id="11" label="w" filenames="DE202018105003U1\_0015.png" state="{{state}}">w</figure-callout>}}_{11}\left|\mathrm{\Delta }\text{AL}\right|\mathrm{+}{\text{<figure-callout id="12" label="w" filenames="DE202018105003U1\_0015.png" state="{{state}}">w</figure-callout>}}_{12}\left|\mathrm{\Delta {\rm B}}\text{L}\right|\text{and optionally}\mathrm{+}{\text{<figure-callout id="13" label="w" filenames="DE202018105003U1\_0015.png" state="{{state}}">w</figure-callout>}}_{13}\left|\mathrm{\Delta }\text{B}\right|,\end{array}$$

where w _{n is} a weight. The weighting may be higher if the actual value of one of the differences is negative because a garment that is too small is more problematic than a garment that is slightly wider.

If a custom-made item can not be recommended because the fit quality value, such as E, is above a threshold, then the controller checks 14 under the control of the processor 19 the e-tailor-made products that come with new patterns or a combination of new and existing patterns from a manufacturer 16 can be produced. About API 28 All the rules or size data related to how new patterns can be created by the manufacturer 16 to be obtained. The control 14 transforms the complete set of body measurements under the control of the processor 19 then into a set of new clothing pattern data 25 or a combination of new and existing clothing pattern data 25 , Under the control of the processor 19 can give the customer a third presentation 20 one under the control of the processor 11 displayed virtual garment prototype according to the customer-selected model and produced according to new patterns. As before, the properties of the representation 20 of the virtual apparel prototype are preferably interactively updated to simultaneously reflect the changes in the structural choice and options of the customer. Under the control of the processor 11 For example, the prototype is preferably displayed three-dimensionally and movably so that it can be viewed in different directions.

The virtual representation 20 may be extended to the rendering of a virtual person, which preferably represents the predicted body shape of the customer according to the estimated body measurements and that according to the control provided by the controller 14 generated pattern data carries selected clothes made according to special instructions. Under the control of the processor 11 the virtual person is preferably three-dimensional ( 3D ) and is preferably movable to demonstrate how the clothing may look in use. Such virtual representations are known in the art, and a suitable example of this technology is taken from the EP0933728 out.

The virtual representation 20 can be for the customer under the control of the processor 11 be available in a variety of different postures and backgrounds, such as static or mobile simulations in urban or rural environments, preferably with the possible presence of additional virtual figures. Under the control of the processor 11 It may also be possible for the customer to use the shirt made according to special instructions 18 in addition to wearing additional clothing, such as different pants. In this way, the customer can judge the shirt in various environments, combinations and styles as an overall picture. At this stage, the customer may change their choice in style or even in terms of fit by, for example, requesting another fit. After considering the selection made and the changes in the simulation, the customer is asked to confirm that the new prototype is preferred or rejected.

If an order is confirmed, and preferably satisfies the fit quality value, such as the error condition E is below the threshold, then the customer will be taken to online billing for the order to be executed. It is understood, of course, that customer accounts, credit cards and other similar means may be used for billing and that these may be provided to the ecommerce portal / ecommerce web site or platform via back office APIs 29 for Enterprise Resource Planning (ERP) and Customer Relationship Management (CRM). ERP is the integrated management of core business processes, often in real time, and mediated through software and technology. These business activities may include product planning, purchase production planning, manufacturing or service delivery, marketing and sales, materials management, inventory management, shipping, and payment and finance.

CRM brings together data from a variety of communication channels, including corporate websites, telephones, e-mail, live chat, marketing materials, and social media. The CRM approach and the systems that make it possible enable companies to learn more about their customers and partners, and how to best meet their needs.

If a ready-to-deliver article is to be provided then the e-commerce portal / e-commerce website or platform will be charged with the delivery.

When a custom-made or e-tailor-made item is selected, the garment pattern data becomes 25 after processing the billing, for example via API 28 to a clothing manufacturing plant 16 passed. This can be a computer-aided manufacturing facility 16 belong under the control of a processor 27 the material (eg via API 28 ) from the options available from the non-volatile memory 17 the controller 14 which the customer's entries / changes have been saved. The computer-aided manufacturing plant 16 cuts under the control of the processor 27 the material or materials according to the sample data 25 for the ordering customer too. The cut material is then assembled and finished. The output of the plant 16 is a shirt made for the specific customer according to specific instructions 18 which is then forwarded to a distribution center (not shown separately) and then delivered to the customer.

Now, let's take a closer look at the development and application of the predictor rules and the meaning of the special requested input variables, as in WO0235952 which is hereby incorporated in its entirety.

The basic consideration on which the calculation of the rules is based is that there is some correlation between certain body measures in a given population. For example, there is a proven correlation between size and arm length. Another basic consideration is that there is a certain correlation between age and specific body measurements such as height or waist size exist. The identification of a correlation between known variables, e.g. For example, the input variables A, W, H, C for a man or a woman, and the unknown body measures B, CC, WC, AC, WR, SL, AL and BL to be predicted, and optionally also BC for a man or a woman, allow the Construction of a forecasting model and its use for its estimation.

It may be that an estimate of the chest circumference, which uses only a specific input variable, is rather inaccurate (see especially 2 ). In this case, collar C is the input variable, and body measurements represent a pattern of potential customers. Chest coverage is plotted across the collar C / neckline, and a "proper fit zone" is developed around a line with the best fit by the population. The diagram represents the principle of a simple sizing system of the clothing industry. This system assumes that the chest circumference is proportional to the neck circumference, which, while true to some extent, results in many potential customers having fit issues; For custom-made clothing, this system is not accurate enough.

3 Figure 12 shows an estimate of the chest circumference, where the measurements of two persons are known and weight and size are plotted on the x-axis in the square root of (weight / size). This chart introduces two body measurements to estimate the chest circumference instead of one. It can be seen that the correlation between available data and the estimate is clearer. Fewer potential customers have problems with the fit.

Out 2 and 3 It can be seen that increasing the number of input variables increases the accuracy of estimated body measurements, and it is believed that the ones chosen in the present invention provide a good trade-off between accuracy and ease-of-use for customers. The customer often knows the requested input variables by heart or can easily determine them at least without expert help. Out 4 shows that the inclusion of age A in a predictor rule the results of the prognosis of 3 improved.

After selecting the input variables A, W, H, C, the next step in the development of the present invention is the construction of the prediction model and its associated rules and values of B, CC, WC, AC, WR, SL, AL and BL and optionally also BC, depending on whether it is a customer or a customer.

The forecasting model is based on regression techniques. Such regression techniques aim to produce mathematical relationships between variables for prognosis purposes, thereby obtaining a significant sample of cases. Relationships are formalized as functions that describe how a dependent variable responds when an independent variable is changed. The functions selected are those that best describe the relationship between variables on average.

The functions are, of course, only approximate to the average behavior of the population, and although the prognosis is satisfactory in most cases, an error can often be noticed when the prognosis is compared to the actual value. The functions that minimize the absolute error between sample actual values and values calculated using the regression function are chosen. It has to be "multiple regression" techniques, because several variables, eg. For example, four independent variables (age A, weight W, height H, and collar C) and several variables that depend on them, d. H. the predicted body measurements chest circumference, waist circumference, arm circumference, wrist circumference, shoulder length, arm length, back length plus optional abdominal width (eg B, CC, WC, AC, WR, SL, AL and BL and also optional BC for a client) must be processed.

Many multiple regression techniques would yield well-fitting results in the present application. However, a linear multiple regression technique generally yields robust models and should preferably be chosen when the relationships between variables are more or less linear. To determine if the relationship is linear or not, it is convenient to use standard, commercially available statistical software packages such as SAS, SPSS, STATISTICA, or others that provide interactive graphical exploration of data facilities. In the case of the present invention, the WINIDAMS software was used. Using this software, isolating the relationships between pairs of variables gives graphs similar to those found in 5 to be shown.

In these diagrams the dependent variables are plotted over the independent variables. As can be seen, although these diagrams are very useful, they represent only a subset of the behavior of the Population because they are only two-dimensional. However, we are interested in the multidimensional relationships between independent and dependent variables. Out 5 It can be seen that in some cases there are linear relationships (arm circumference to weight), non-linear relationships (arm circumference to age, banana-shaped) and some undefined relationships (wrist circumference to size with no or very loose correlation).

To convert non-linear relationships to linear, some variable changes must be introduced. It can be seen that all relationships seem to be either linear or undefined, except when age A played a role. This is perfectly logical, as some body measurements may increase with age until a certain age is reached, after which they decrease with advancing age. For example, this category often includes height and related body measures such as leg length. For example, when dealing with a curved relationship, such as between arm circumference and age, the predictor rules introduce the square of age as a dependent variable. This allows the curve to approximate through a second degree polynomial curve.

$$\begin{array}{lllll}\text{c}=2\mathrm{\Pi }\text{r}\hfill & =>\hfill & c=2{\mathrm{\Pi }}^{1/2}{\left(\text{v/h}\right)}^{1/2}\hfill & =>\hfill & \text{c proportional zu }{\left(\text{v/h}\right)}^{1/2}\hfill \end{array}$$

und wenn angenommen wird, dass Gewicht w proportional zu v ist, dann ergibt sich:

• c proportional zu (w/h)^1/2.

It may also turn out that some other relationships are not linear. Assuming that there is an analogy between body parts such as the chest or arm and a cylinder, the relationship between circumference measurements and the indicated weight and size information can be identified. $$\begin{array}{ccc}\text{v}=\mathrm{\Pi }{\text{r}}^2\text{H}& =>& \text{r}{\mathrm{\Pi }}^{1/2}\end{array}={\left(\text{v / h}\right)}^{1/2}$$

$$\begin{array}{lllll}\text{c}=2\mathrm{\Pi }\text{r}\hfill & =>\hfill & c=2{\mathrm{\Pi }}^{1/2}{\left(\text{v / h}\right)}^{1/2}\hfill & =>\hfill & \text{c proportional to}{\left(\text{v / h}\right)}^{1/2}\hfill \end{array}$$

and if it is assumed that weight w is proportional to v, then:

• c proportional to (w / h) ^1/2 .

That is, (w / h) ^1/2 is introduced into the model as an additional independent variable.

At the end of this step, we have a gender-dependent set of independent variables: age, weight, height, collar size / neck circumference, age square, square root of the weight divided by the square root of the size. It is likely that these variables all fit in favor of the multiple linear regression model.

After that, the next step is the formalization of relationships between variables through a set of equations. This step is the actual "modeling" step, where all parameters of the regression are set and the predictor rules are completed. Again, a specific statistics package such as WINIDAMS is useful in which a stepwise regression application is preferably used.

The stepwise creation of a regression allows the simultaneous identification of the relationships between variables (i.e., obtaining a set of equations / predictor rules) and checking the significance of the enhancement added to the model of each independent variable. In other words, if the standard error of the forecast does not decrease significantly by using a particular independent variable, that variable can be ignored.

• Unter der Annahme, dass: a=Alter (Jahre), w=Gewicht (kg), h=Größe (cm) und c=Kragenweite/Halsumfang (cm).

At the end of the step-type regression method, an exemplary model can generally be obtained in accordance with the following:

• Assuming that: a = age (years), w = weight (kg), h = size (cm) and c = collar width / neck circumference (cm).

$$\begin{array}{cc}\text{Bauchumfang}& =-\mathrm{70,7}+\mathrm{0,232}\text{a}+\mathrm{0,802}\text{c}+185{\left(\text{w/h}\right)}^{1/2}\end{array}$$

$$\begin{array}{cc}\text{Taillenumfang}& =\mathrm{86,2}+\mathrm{0,21}\text{a}-\mathrm{0,423}\text{h}+\mathrm{0,246}\text{c}+\mathrm{0,742}\text{w}\end{array}$$

$$\begin{array}{cc}\text{Armumfang}& =-\mathrm{1,5}-\mathrm{0,00034}{\text{a}}^2-\mathrm{0,043}\text{h}+\mathrm{0,089}\text{c}+\mathrm{57,6}{\left(\text{w/h}\right)}^{1/2}\end{array}$$

$$\begin{array}{cc}\text{Handgelenkumfang}& =\mathrm{4,2}+\mathrm{0,00019}{\text{a}}^2+\mathrm{0,02}\text{h}+\mathrm{15,3}{\left(\text{w/h}\right)}^{1/2}\end{array}$$

$$\begin{array}{cc}\text{Schulterlänge}& =\mathrm{12,4}-\mathrm{0,00012}{\text{a}}^2+\mathrm{0,013}\text{h}-\mathrm{0,065}\text{c}+\mathrm{0,045}\text{w}\end{array}$$

$$\begin{array}{cc}\text{Armlänge}& =\mathrm{6,1}+\mathrm{0,047}\text{a}+\mathrm{0,326}\text{h}-\mathrm{0,165}\text{c}+\mathrm{0,058}\text{w}\end{array}$$

$$\begin{array}{cc}\text{Rückenlänge}& =\mathrm{7,9}+\mathrm{0,02}\text{a}+\mathrm{0,3}\text{h+}\mathrm{0,149}\text{c}+\mathrm{0,072}\text{w}\end{array}$$

In this case, the predictor rules were obtained from a representative sample of approximately 1400 Belgian men over 18 using the IS08559 definitions for body measurements and read as follows (all results in centimeters) $$\begin{array}{cc}\text{chest}& =-4.87+0.229\text{a}-0.0019{\text{a}}^2+0361\text{c}+130.4{\left(\text{w / h}\right)}^{1/2}\end{array}$$

$$\begin{array}{cc}\text{waist circumference}& =-70.7+0.232\text{a}+0.802\text{c}+185{\left(\text{w / h}\right)}^{1/2}\end{array}$$

$$\begin{array}{cc}\text{waist size}& =86.2+0.21\text{a}-0.423\text{H}+0.246\text{c}+0.742\text{w}\end{array}$$

$$\begin{array}{cc}\text{arm circumference}& =-1.5-0.00034{\text{a}}^2-0.043\text{H}+\mathrm{0,089}\text{c}+57.6{\left(\text{w / h}\right)}^{1/2}\end{array}$$

$$\begin{array}{cc}\text{wrist}& =4.2+0.00019{\text{a}}^2+0.02\text{H}+15.3{\left(\text{w / h}\right)}^{1/2}\end{array}$$

$$\begin{array}{cc}\text{shoulder length}& =12.4-0.00012{\text{a}}^2+\mathrm{0,013}\text{H}-\mathrm{0,065}\text{c}+\mathrm{0,045}\text{w}\end{array}$$

$$\begin{array}{cc}\text{arm's length}& =6.1+0.047\text{a}+0.326\text{H}-\mathrm{0,165}\text{c}+0.058\text{w}\end{array}$$

$$\begin{array}{cc}\text{back length}& =7.9+0.02\text{a}+0.3\text{h +}\mathrm{0,149}\text{c}+0.072\text{w}\end{array}$$

It should be noted that this model is derived from a specific sample of a particular population. If a different sample is used, or if only the significance threshold level in the stepwise regression is changed, or if only strictly linear relationships are maintained, or even if the linear fit method is changed, this can cause the equations to look quite different. But the predicted values of the dependent variables remain tight. After establishing the predictor rules, they are preferably checked on a different sample of the population to calculate the standard deviation of the resulting estimates from the actual body sizes. It should turn out that this standard deviation is close to the standard deviation of the regression model. Upon completion of the entire process, a robust predictive model of body dimensions is obtained, which is used in the design of patterns for custom-designed, custom-made shirts 18 or other clothing can be used.

Statistically, the uncertainty of the conformity of the pattern with the body shape has been reduced compared to the clothing industry.

If morphological changes were to occur in the population over time, For example, if you made it bigger or heavier, the forecasting model would be less accurate. However, it is possible to change the model to reflect the evolution of the population. The regression simply has to be done in exactly the same way, but using a new updated pattern of individual variables. If an updated sample is continuously available, the rules may evolve continuously. Each time you place an order or change your sample, you may regress to generate new rules.

More generally, if the invention is to be applied to a population that has significant morphological changes compared to the original sample, the model can be recalculated based on a new sample from the other population concerned. Such morphological changes may, for example, reflect specific characteristics in the geographic or ethnic origin of the new target population. Another step in the same direction would be to add new personal variables to the model that represent the geographic or ethnic origin of the customer. The introduction of the new variable into the regression would lead to a single model that would be applicable to different morphological types.

The use of age A as an independent input variable and within the predictor rules is particularly noteworthy. Experiments have shown that their use in some cases leads to the following error reduction in the estimates. The numbers may be construed as the improvement in forecast accuracy resulting from the use of the A age variable.

While the present invention has been particularly shown and described with reference to a preferred embodiment, it will be understood by those skilled in the art that changes in form and Detail can be made without departing from the scope of the invention and the spirit of the invention.

For example, it would be preferable to also obtain an input variable indicating arm or sleeve length, as well as an input variable for the waist, as these would further increase accuracy. If the embodiment described above were changed to provide a blouse, it would be useful to obtain other input variables that are specific to the female body and generally known to the customer, such as bust size.

The invention may also be varied to make other custom-made garments, such as pants; There, too, the use of age is useful to predict temporal changes such as thigh circumference. Namely, since the size is already 'known' to the model, it can generally already take into account the effect of body length and its age-related shrinkage. The projection of the dorsal length remains generally unaffected by the introduction of age into the model, although the back length, in absolute terms, may well be greatly affected by age as the distance between the vertebrae decreases. Under these conditions, it would also be preferable to request input variables indicating foot and leg length, e.g. B. shoe size and stride length. Using the invention for the production of a jacket and a pair of trousers, complete suits may be designed with an appropriate vest, if necessary.

To facilitate implementation of the invention, an information carrier such as a CD-ROM could be provided, which is presented for example as a giveaway or sold and charged with subsequent purchases. It would encode at least one program for implementing the invention, including, for example, a website interface and / or a database of clothing options or dimension information and / or a web browser and / or an order / billing system and / or a mapping program to enable Displaying an image as discussed above.

It should be understood that the results of the samples taken in the construction of the database may be used to further develop the invention so that limits may be determined as to whether or not a particular customer may be served using the automatic method of estimating body measurements. In the graphic in 4 For example, a border line is drawn around the range of results with the highest data density, and this borderline may include, for example, an ellipse or oval that extends beyond the boundaries of the zone of proper fit. If a potential customer is out of bounds because of the input variables that they specify, they are defined as hard to deliver. This may be because the customer has entered exceptional or very inaccurate input variables, which could lead him to interactively receive a message asking him to check his input variables or possibly even get himself trained by professionals.

It could also be a database with data on exceptional customers and with records of any orders that are returned or reported as bad sitting, z. Returns under warranty, dimensions used. Advantageously, this database could also keep more records of orders that were complaint free. The data collected in this manner is then used to update the population sample records and / or predictor rules to provide protection against inaccuracies trends due to negative or out of tolerance inputs, or to increase confidence in the robustness of the method from positive results. The database may be integrated with the records of the original / updated sample, or stored separately from them, as may prove necessary if a database has been acquired from third parties. The information thus collected could also serve to protect customers who are difficult to satisfy, for example by recording customers who often return goods for whatever reason.

For example, a customer answers 4 simple questions, and software components translate that data into a complete biometric profile of the customer's body. After saving all these sizes, an endpoint can use one of the backbone implementation functions to tune these biometric values to the selected product and return the best fit standard size. The algorithm then provides a percentage of the standard size fit level. An acceptable percentage may be set as a design threshold before recommending another garment to the customer or the platform's fully customized approach.

In 1 to 7 Embodiments of the present invention utilize the APIs 22 . 24 . 26 for specially designed and custom-made software 3D Configuration embedded in the multichannel platform. Upon receipt of input variables such as A, W, H, C, a predictor service may be provided 40 use a forecasting model and its associated rules to predict the values of B, CC, WC, AC, WR, SL, AL and BL, and optionally BC, depending on whether it is a client. Configuration sizing is provided using size tables 38 as a service to provide finished, custom-made or e-tailor-made products. The API 24 provides benefits for 3D configurators 37 for delivery through the use of plug-ins 36 (eg, based on the platform's web capabilities) as a way to start the process quickly and cheaply. This can be platforms 32 be opened for fully customized biometric fitting clothing.

Embodiments of the present invention may be an API 28 use, for. B. as a web service for CAD / CAM interfaces 39 : Tissue cutting files for connection to manufacturing systems 16 who tailor, manufacture and deliver fashion products.

Embodiments of the present invention may be an API-driven platform 30 that will allow all sellers and consumers to benefit from technically advanced sizing and custom-made solutions that are currently unavailable. This platform can be local, central or distributed. Consumers can benefit from a fit that is as correct as it is standardized, as well as accurate stock availability information.

1. (i) einfache Größenprognoseimplementierung → Zeitaufwand zur Implementierung dieser Leistung um 50 % reduziert;
2. (ii) Abstimmen des Produkts auf die Kundengröße → Retouren um 50 % reduziert;
3. (iii) Streubreite des Maßschneiderungsparadigmas → 40 % mehr nach Maß gefertigte Produkte;
4. (iv) Integration von Produktkonfiguration und Herstellung → Lieferzeit von nach Maß gefertigten Produkten um 30 % reduziert.
5. (v) eine indirekte Auswirkung auf die Umwelt, weil die Menge an falschen Online-Verkäufen drastisch reduziert wird, dank der Verwendung von Größenprognosen oder dem Wählen von maßgeschneiderten Produkten. Abfall wird reduziert, indem die Gesamtzahl an Online-Retouren gesenkt wird, indem Größen von Kunden und Modeprodukten mit einem Größenprädiktor mit anderen Funktionalitäten wie dem Einschluss von nach Maß gefertigten Kleidungsstücken verbunden werden,
6. (vi) auf den Kunden zugeschnittene und konfigurierbare nach Maß gefertigte (MtM) und e-maßgeschneiderte Lösung auf der Grundlage von offenen Normen,
7. (vii) weniger Produktzurückweisungen und Retouren hauptsächlich von e-Commerce in Verbindung mit unbequemer und schlecht sitzender Kleidung.
8. (viii) Möglichkeit der Bereitstellung von offenen und vollständig kompatiblen Plattformen, die von beliebigen Betrieben in der Modebranche zur Bereitstellung ihrer Produkte, Verfahren und Dienstleistungen genutzt werden können.

Advantages of the present invention include:

1. (i) simple size prediction implementation → time required to implement this performance reduced by 50%;
2. (ii) matching product to customer size → returns reduced by 50%;
3. (iii) Range of customization paradigm → 40% more tailor-made products;
4. (iv) Integration of product configuration and manufacturing → Delivery time of custom made products reduced by 30%.
5. (v) an indirect environmental impact, because the amount of incorrect online sales is drastically reduced thanks to the use of size forecasts or the selection of tailor-made products. Waste is reduced by reducing the total number of online returns by combining sizes of customers and fashion products with a size predictor with other functionalities such as the inclusion of custom-made garments,
6. (vi) custom tailored and configurable custom made (MtM) and e-tailor-made solution based on open standards;
7. (vii) fewer product rejections and returns, mainly from e-commerce coupled with uncomfortable and ill-fitting clothing.
8. (viii) the ability to provide open and fully compatible platforms that can be used by any fashion industry company to provide its products, processes and services.

Processors described with respect to embodiments of the present invention, e.g. B. can be used together with non-volatile memories can be operated by an independent digital processing device or embedded in another device. The processor preferably has processing capability as may be provided by one or more microprocessors, FPGAs or a Central Processing Unit (CPU) and / or Graphics Processing Unit (GPU), and is configured to perform the respective functions by: he is programmed with software, d. H. one or more computer programs. Software can include any type of program in any language that can be processed directly or indirectly by a processor, either through a compiled language or an interpretive language such as Java. The implementation of any of the methods of the present invention may be performed or supported by logic circuits, electronic hardware, processors, or circuits including any type of arbitrary integrated logic or analog circuit, rather than general purpose processors, digital signal processors, ASICs, FPGAs, discrete ones Components, Transistor Logic Gate u. Ä. Are limited.

Such devices may include memory (such as nonvolatile memory, non-transitory computer readable medium, RAM and / or ROM), an operating system, optionally a display such as a fixed format display, ports for data input devices such as a keyboard, a pointing device such as a mouse , serial or parallel ports for communicating with other devices, network cards and ports for connection to any of the networks.

The software may be embodied in a computer program product adapted to perform the functions below when the software is loaded into the controller and executed in one or more processing modules such as microprocessors, ASICs, FPGAs, and so forth. Devices for use with any of the embodiments of the present invention may include a computer system that may run one or more computer applications in the form of computer software.

The methods of embodiments of the present invention may be performed by one or more computer application programs running on the computer system by loading them into memory and operating on or in connection with an operating system such as Windows ™ from Microsoft Corp., USA, Linux, Android o run. The computer system may include main memory, preferably random access memory (RAM), and may also include a non-volatile hard disk drive and / or a removable nonvolatile memory and / or a non-volatile semiconductor memory. The non-volatile removable memory may be an optical disk (CD-ROM or DVD-ROM) or a magnetic tape that is read by and written to by a suitable reader. The removable nonvolatile memory may be a computer readable medium storing computer software and / or data. The non-volatile memory may be used to store persistent information that must not be lost when the computer system is turned off. The application programs can use and store information in non-volatile memory.

The software executed in the computer program is designed to perform the following functions of any of the method steps of the embodiments of the present invention when the software is loaded into the respective device or devices and processed in one or more processing modules such as microprocessors, ASICs, FPGAs, and so on.

Any of the above software may be implemented as a computer program product that has been compiled for a processing module in any of the servers or nodes of the network, or written in an interpretive language such as Java running on a virtual machine such as the Java Virtual Machine , The computer program product may be stored in a nonvolatile signal storage medium such as an optical disk (CD-ROM or DVD-ROM), a digital magnetic tape, a magnetic disk, a USB flash memory, a ROM, etc.

QUOTES INCLUDE IN THE DESCRIPTION

This list of the documents listed by the applicant has been generated automatically and is included solely for the better information of the reader. The list is not part of the German patent or utility model application. The DPMA assumes no liability for any errors or omissions.

Cited patent literature

• EP 0933728 [0084, 0091, 0095]
• WO 0235952 [0101]

Claims (15)

System based on a computer system for supplying ready-made or custom made or e-tailor made textile products made from synthetic or natural fibers, comprising: Means for receiving a first set of a plurality of body measurement input variables, which are biometric metrics of a customer to be equipped with at least a first textile product, Means for processing the first set of the plurality of body measure input variables in a predictive model to predict a second set of at least 2, 4, 6, or 8 estimated body measures, each of the estimated body measures being derived from two or more of the input variables; Means for deriving a fit quality value for the first textile product which may be a ready-made or made-to-measure and e-tailor made textile product as a function of the first set of the plurality of body size input variables and the second set of at least two , 4, 6 or 8 estimated body measurements, Means of rejecting all ready-made or made-to-measure textile products that do not conform to the fit quality standard, and, when a ready-made or made-to-measure textile product conforms to the fit quality value, means for sending this finished or custom made textile product to the customer are provided while the customer is otherwise sent the e-tailor-made product. System after Claim 1 wherein the first set of a plurality of body measurement input variables is provided by first software of a first seller, the system further comprising: means for mapping that first set to a third set of values of a second software of the forecast model, wherein the mapping is performed by the transferring the plurality of body size input variables is performed by a first API, means for deriving the fit quality value for any ready-made or made-to-measure and e-tailor made textile product from a size prediction based on a size map, and means for allowing the customer to specify whether a finished product or a custom-made product or an e-tailor-made product is acceptable. System after Claim 1 or 2 wherein: a second API is provided for 3D configuration for the finished, custom-made or custom-made product. System after Claim 1 or 2 or 3 , further comprising: means for generating both CAD and CAM data to enable production via a third API for manufacturing integration of the custom or e-tailed product with a manufacturing method of a manufacturer. System after Claim 4 and further comprising: - the manufacturer being able to obtain a digital design specification of a textile product from a design unit over a wide area network, - means for processing the obtained design specification to obtain a virtual prototype of the textile product, - means for converting the virtual prototype to a format, compatible with an additive and subtractive processing system, means for obtaining a material from which the textile product is to be made, and means for obtaining the textile product by molding using the additive and subtractive processing system. System after Claim 5 wherein the means for obtaining the textile product by molding using the additive and subtractive processing system depending on the material selected comprises one of the following: cutting means, stepping means, crimping means, crimping means, sewing means, gluing means , Means for welding. System according to one of Claims 1 to 6 , wherein the plurality of body size input variables are selected from weight, height, girth and additional input variables age and gender. System according to one of Claims 1 to 7 The second set of at least 2, 4, 6, or 8 estimated body measurements are selected from KMI, chest circumference, waist circumference, arm circumference, wrist circumference, shoulder length, arm length, back length, and waist or waist circumference. System according to one of Claims 5 to 8th , further comprising means for providing the customer with a representation of the three-dimensional displayed virtual prototype. Computer-based system for supplying ready-made or custom-made or custom-made textile products made from synthetic or natural fibers, comprising: Means for receiving product design data comprising parameter values about at least a first textile product and / or biometric measurement data of a customer to wear the at least one first textile product, the product design data being provided by first software of a first seller, Means for mapping said product design data to values of a second software of a predictive system of textile products, said mapping means including a first API for biometrics and size prediction based on a sizing chart, Means for determining the extent to which the textile product size matches the biometric measurement data, and means for allowing a customer to indicate whether to buy a ready-made or custom-made product or a custom-made product. System after Claim 10 further comprising means for providing a 3D configuration for the finished, custom-made or e-tailor-made product. System after Claim 10 or 11 and further comprising means for generating both CAD and CAM data to enable production via a third API for manufacturing integration of the custom-made or custom-made product with a manufacturing method of a manufacturer. System after Claim 12 and further comprising - the manufacturer having means for obtaining a custom or custom made digital design specification from a design unit over a wide area data network, - means for processing the obtained design specification to obtain a custom made or custom tailored virtual prototype Product, means for converting the virtual prototype to a format compatible with an additive and subtractive processing system, means for obtaining a material from which the textile product is to be made, and means for obtaining the textile product by molding using the additive and subtractive editing system. System after Claim 13 in which the customer is provided with means for displaying a virtual representation of the three-dimensionally displayed virtual prototype. A non-volatile signal storage device having at least one program for executing a method as it is executed on a processor, the method comprising the steps of: receiving, by the computer system, a first set of a plurality of body size input variables that are biometric measurement data of a customer to be equipped with at least a first textile product, processing the first set of the plurality of body measurement input variables by the computer system in a prognosis model for predicting a second set of at least 2, 4, 6, or 8 estimated body measurements, each of deriving an estimated body dimension from two or more of the input variables, deriving a fit quality value for the first textile product by the computer system that is a ready-made or made-to-measure and e-tailor made textile product, or any of them s can act as a function of the first set of the plurality of body measurement input variables and the second set of at least 2, 4, 6, or 8 estimated body measurements, rejecting by the computer system all ready-made or custom-made textile products that do not conform to the fit quality value; and, when a finished or made-to-measure textile product conforms to the fit quality value, the customer obtains that finished or made-to-measure textile product under the control of the computer system while the customer otherwise receives the e-tailor-made product.

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