Online Quality Monitoring of
Nonwoven Fabrics Using
Digital Image Processing
Technique
PRESENTED BY
HARSHAL PATIL
FINAL YEAR TEXTILE TECHNOLOGY
CENTER FOR TEXTILE FUNCTIONS
MPSTME, NMIMS, DEEMED TO BE UNIVERSITY SHIRPUR CAMPUS
INTRODUCTION
• Manufacturers recover only 45-65 % of their profits
from seconds or off quality goods.
• Online monitoring system is an important system
installed on almost all modern nonwoven
manufacturing machines.
• It not only provides the details of fabrics but also
analyze the data of faults like repetition of faults,
frequency of occurring faults on screen, so it helps in
process control.
AUTOMATED INSPECTION SYSTEM
• Automated inspection system consists-
Fabric monitoring system which may be offline or online.
High resolution camera is used for monitoring
Image processing tools for enhancement of the images
captured
Defect analyzing and classifying software.
WHY ONLINE QUALITY MONITORING ?
• The defects at present are frequently examined by human
inspectors and they have some limitation-
human perception may vary from individual to individual
high labour cost .
More time.
Extra step
Less degree of accuracy.
IMPORTANCE IN NONWOVEN
• The nonwoven fabrics are structured fabrics designed by considering
performance properties required in its end use.
• Many time the application area are intricate required highly presided
quality fabric like filter fabric.
• Nonwoves with very small defects rejected by the customers, causes
huge loss to manufactures.
• In this situation nonwoven manufactures need a reliable and
sustainable solution like online quality monitoring.
• As Nonwovens are produced with high production rate on few
machines, thus it is cost effective to have online monitoring as
compared with woven fabrics.
ONLINE MONITORING SYSTEM
• There are two important steps-
Image acquisition
Monitoring and analysis
PROCESS OF ONLINE MONITORING
IMAGE ACQUISITION
• The image acquisition section comprises
source of image acquisition
It consist camera
CCD - charge coupled device
CMOS - (Complementary Metal-Oxide Semiconductor)
source of illumination
Choice of an illumination depends on the fabric density, defect types and
stage in which the inspection is carried out
Illumination effects the quality of the image captured
The front or top lighting is normally used for enhancing surface texture
while backlighting is normally used to enhance the structure of translucent
fabrics
Infra-red lighting , fluorescent lamp , halogen lamp are also used.
Selection of lamp to suit the cost economy would be desirable .
Fig: various illumination configurations
• Techniques involved in image acquisition
Line Scan
Monitoring and analysis
Area Scan
MONITORING AND ANALYSIS
• The Monitoring and analysis section comprises of a computer
platform with inspection software module.
• It is the main image processing and analysing unit and the main
functions of this section are defect detection and control of image
acquisition as well as the whole system.
• The algorithm used in the software module majorly contributes to the
effectiveness of the system
• Various algorithm are : Structural Approaches, Statistical
Approaches, Histogram based Approaches, Morphological operations
approach
FAULTS DETECTED BY OQM SYSTEM
AVAILABLE SUPPLIERS
• EVS:-Elbit Vision System’s I-TEX- Welspun Anjar
• Andritz Perfojet, France.- Ginni Filaments
• Mahlo America, Inc.
• Isra Visio
• Summit Engineering DC3000 Pinhole
Detection System n
ADVANTAGES
• Continuous Quality Monitoring
• Census/ Population Quality Checking
• Assurance about the Quality
• More accuracy
• Less time
• No Need of Separate Inspection
• Reduce labour cost
• Reduce rejection percentage
• Store data for reference
• Helps to Process Control and Improve Productivity
CHALLENGES AND DIFFICULTIES IN
THE IMPLEMENTATION
Variety of fabric faults obtained differing with respect to nature,
size, frequency and severity .
Characterization of defects in case of nonwovens because of
their homogeneous fibrous structure.
Online Image acquisition and analysis at higher Production rate
High Capital Investment.
Big Data Analysis is required to conclude.
Chances of failure in Image Acquisition
Use of different algorithms for different nature of defects.
CONCLUSION
• Nonwoven manufacturing is rapidly growing textile
manufacturing sector due to its technical and economical
advantages .
• The effective online monitoring will play a key role for in
quality nonwoven manufacturing.
• The results obtained from Online quality monitoring are not
only useful for quality monitoring but can also used for
automated process control with artificial intelligence.
• With all these advantages OQM will helps to enhance the
profit of by reduction in rejection percentage , improved
quality and low labor cost as well as time.
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