Sungmin Kim

SEOUL NATIONAL UNIVERSITY

Fashion Technology7. Manufacturing Technology

Printing Process

Conventional Silk-Screen Printing

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Printing Process

Conventional Rotary-Screen Printing

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Digital Textile Printing

Digital Textile Printing (DTP) Features

Unlimited range of expression

Small lot printing for sampling and production

Needs pre and post treatment

Slower than rotary-screen printing

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Digital Textile Printing

Digital Textile Printing Ten Reasons for using DTP

Short run printing advantage

– Run lengths as low as one yard of fabric without the need for screen changes

Lower water and power consumption

– Elimination of the substantial amount of water and electrical energy for rotary screen printing

Less chemical waste

– Results in significantly less ink usage and waste relative to rotary screen printing

Large repeat sizes

– Without the usual screen printing limitation in pattern repeat size

Reduced production space requirements

– The production footprint for digital printing is a fraction of the size of screen print facility

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Digital Textile Printing

Digital Textile Printing Ten Reasons for using DTP

Less printed inventory needed

– Reduction of the need for pre-printed inventory of fabric that may or may not be used

Sampling and production done on same printer

– Samples of designs will exactly match the final printed material

Print flexibility

– Small quantity printing for market test before high volume rotary screen printing

Variety of creative design choices for printing

– Capable of photographic/continuous tone images

Low capital investment

– Lower capital investment compared to rotary printing production

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Digital Textile Printing

Digital Textile Printing Application Fields

Apparel

Upholstery

Transportation

Footwear

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Digital Textile Printing

Digital Textile Printing Application Fields

Rapid Prototyping

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3D Printing

3D Printing Technology Stereolighography (SLA)

Patented by Charles Hull, co-founder of 3D Systems, Inc in 1986.

3D model is converted into an STL file (up to ten layers per each millimeter)

SLA machine exposes the liquid plastic and laser starts to form each layer of the item

After plastic hardens the platform drops down in the tank a fraction of a millimeter

Printed object is rinsed and placed in an ultraviolet oven for finish processing

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3D Printing

3D Printing Technology Digital Light Processing (DLP)

Created in 1987 by Larry Hornbeck of Texas Instruments

Uses digital micro mirrors laid out on a semiconductor chip

– The same technology applied for movie projectors

One section of object is built simultaneously

– The printing speed is pretty impressive

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Other method DLP method

3D Printing

3D Printing Technology Selective Laser Sintering (SLS)

Developed by Carl Deckard and Joe Beaman (Texas University) in 1980s

Doesn’t need any support structure

More spread among manufactures rather than 3D amateurs at home

– Use of high-powered lasers, which makes the printer to be very expensive

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3D Printing

3D Printing Technology Selective Laser Melting (SLM)

Developed in Fraunhofer Institute ILT in 1995

The fine metal powder is intensively fused by applying high laser energy

– Metal powder melts fully and forms a solid object (stainless steel, titanium, chrome, aluminum)

Applied to parts with complex geometries and structures

– Thin walls, hidden voids or channels

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3D Printing

3D Printing Technology Fused Deposition Modeling (FDM)

Developed by Scott Crump, Stratasys Ltd. founder, in 1980s

Slower than SLA or DLP

Simple-to-use and environment-friendly

Different kind of thermoplastic can be used to print parts

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3D Printing

3D Printed Garment Advanced 3D Printing (4D Printing)

Life-size Garment

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3D Printing

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3D Printing

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3D Printing

3D Printed Garment

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3D Printing

3D Printed Garment by FDM

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Sewing Robot

Sewbo Prototype Sewing Robot (Jonathan Zornow, 2016)

Using water soluble thermoplastic to stiffen fabric to be as sturdy as cardboard

Fabric manipulation using universal robot

Sewn garment is put into hot water for the plastic to melt off

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Objective Evaluation

Application Fields Quality Evaluation

Visual appearance

– Seam pucker, wrinkle, smoothness appearance, pilling, color fastness, etc.

Physical property

– Drape coefficient, etc.

Structure Analysis

Extraction of fabric design parameters

Technology Non-contact 3D Measurement

Image Analysis

Numerical Analysis

Artificial Intelligence

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Objective Evaluation

Fabric Surface Quality Evaluation Conventional Method

Comparison of specimen with standard replica by human experts

Newly Developed Method

Objective evaluation of specimen with 2D/3D measurement

Wrinkle Replicas Smoothness Replicas Seam Smoothness Replicas

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Objective Evaluation

Fabric Surface Quality Evaluation Non-Contact 3D Measurement

Laser Scanning

Stereovision

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Object

Shift

Objective Evaluation

Fabric Surface Quality Evaluation Fractal Dimension

Index of Shape Complexity

: 2.5

N( ) : 21

: 5

N( ) : 14

: 10

N( ) : 7

CD

LDDNL

N D

ln

lnlnln

)(

y = -2.012x + 11.379

R2 = 0.999

0

2

4

6

8

10

12

0 1 2 3

ln

ln N

()

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Objective Evaluation

Fabric Surface Quality Evaluation Suggestion of New Evaluation Criteria

Linear relationship between grade and actual visual appearance

y = -0.0396x + 2.3112r2 = 0.7618

2.05

2.1

2.15

2.2

2.25

2.3

2.35

0 1 2 3 4 5

2.08

2.12

2.16

2.2

2.24

2.28

2.32

0 1 2 3 4 5

Fra

cta

l D

imensio

n

New linear evaluation criteria

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Objective Evaluation

Image Analysis Image acquisition

Digital camera

Image processing

Grayscale conversion

Binary conversion

Topology modification

– Opening, closing, thinning, skeletonization, etc.

Filtering

– Average, median, Gaussian, edge detection, etc.

Frequency domain analysis

– Fast Fourier transformation (FFT)

Quantitative analysis

– Counting, measurement

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Objective Evaluation

Image Analysis Fabric Pilling Evaluation

ASTM 3512 photographic pilling standards

Grade 1 Grade 2 Grade 3 Grade 4 Grade 5

FFT, Gray Scaling, Binarization, Counting

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Objective Evaluation

Image Analysis Fabric Structure Analysis

Extraction of Design Parameters

Warp/weft density Fabric cover factor Fabric thickness

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Objective Evaluation

Image Analysis Fabric Structure Analysis

Extraction of Design Parameters

Evaluation of crimp Orthogonality Defect detection

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Objective Evaluation

Image Analysis Yarn Crimp

Evaluation of yarn crimp under zero-tension condition

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Objective Evaluation

Image Analysis Fabric Drape Coefficient

Quantitative analysis of drape phenomenon

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Objective Evaluation

Physical Measurement Garment Fit

Strain/pressure simulation and measurement

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Objective Evaluation

Physical Measurement Evaluation of Human Factors

Interaction between…

– Human body and garment

– Garment and environment

Physiological analysis

– Garment function

– Garment comfort

– Safety factors

Elimination of questionnaire

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Artificial Intelligence

Negative View ? Evil Self-Conscious A. I. in Movies

HAL 9000 (2001 Space Odyssey, 1968)

Sky Net (Terminator, 1984)

Ava (Ex Machina, 2015)

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Artificial Intelligence

Current Status

Problems Easy for Computer

Hard for human

– Simple-repetitive-precise calculation

– Huge data analysis

Problems Hard for Computer

Easy for human

– Voice, image, text recognition

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Artificial Intelligence

Killer Robots ? DARPA Robotics Challenge

Most robots could not cross a few hurdles made of brick pieces

Just climbing a ladder or opening a door were difficult

The key to success is the seamless interaction with the real world

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Artificial Intelligence

Solution of NP-Hard Problems Nondeterministic Polynomial Time Problem

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3!=64!=24...35!=1040

Artificial Intelligence

Optimization

Definition

Determination of optimum set of independent variables

Examples

Determination of the area, height, and cost of building construction

Consideration of the price, function, and after-service of goods

Determination of the optimal route for overseas travel planning

Determination of an index from a number of variables without any visible relationship

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Artificial Intelligence

Traditional Solution Numerical Analysis

Simulated Annealing

Conjugated Gradient

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NFL (No free lunch) Theorem !

Artificial Intelligence

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A. I. Solution Artificial Neural Network

Imitation of neuron-synapse system

Error back propagation network

Artificial Intelligence

A. I. Solution Genetic Algorithm

Calculation based on Natural Evolution Process

– Simulated evolution

– Similar terms are used : Population, Generation, Fitness, Selection, Cross-Over, Mutation

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111010101100

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11101010110032%

24%

24%

20%

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InitialPopulation

FitnessEvaluation

Selection Cross-Over Mutation

Artificial Intelligence

A. I. Solution Fuzzy Inference

Logic for the Description of Vague Concepts

– Meaningless and ambiguous properties such as person’s appearance etc.

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Level of Middle Agedness

Age35 55

1

1

Application Fields

• Control

Subway

Robot arm

Furnace temperature

• Social Science

Fuzzy questionnaire

• Information Science

Fuzzy database

-15 -10 -5 0 5 10 15

-45 -30 -15 0 15 30 45

Artificial Intelligence

Applications in Fashion Technology Material Selection

Fusible Interlining– Input

» Physical properties of fabric and adhesive» Fusing condition (temperature, pressure)

– Output » Optimum interlining

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Neural Network

Artificial Intelligence

Applications in Fashion Technology Categorization

Multivariate nonlinear regression

– Body type

– Insole type

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Artificial Intelligence

Applications in Fashion Technology Pattern Nesting

Classic NP-Hard problem

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Artificial Intelligence

Research Topics Improvement of Unstructured Data Processing Method

Why do I think so ?

– Understanding the mechanism of human thinking

Image or text recognition is particularly important in fashion sectors

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