Textile Mending Machine: Data Recording System

Abstract

The textile industry relies heavily on precision in data logging to ensure that operations such as fabric mending are performed efficiently. Traditional methods involve manual data entry, which is prone to human error and is inefficient, particularly when data is needed for quick decision-making. This project seeks to address these challenges by implementing an automated textile data logging system, which utilizes an Arduino-based system integrated with a rotary encoder, LCD, and thermal printer for real-time data capturing. The system will log data on fabric length and quality, interfacing with an ESP8266 for web-based reporting and data access. Through this system, loom operators will be able to input loom numbers and fabric quality, and the system will automatically track fabric length using encoder-based measurement. This data will be printed on a thermal printer and uploaded to a central database through the ESP8266 for remote access and analysis. This solution aims to eliminate manual errors, reduce reporting delays, and create a seamless fabric mending process, ultimately enhancing efficiency and data accuracy in the textile industry.

Introduction

I. INTRODUCTION AND BACKGROUND OF THE INDUSTRY PROBLEM

A. Overview of the Textile Industry

The textile industry is a global powerhouse, providing raw materials and finished products to multiple sectors. This industry, however, faces numerous challenges, including the need for real-time data accuracy, quality control, and efficient reporting. The complex nature of textile manufacturing, with the involvement of multiple stages— spinning, weaving, dyeing, and finishing—demands precise data logging at each step to ensure that the final product meets the quality standards expected by customers and regulatory bodies. Globally, the textile industry contributes over USD 920 billion annually, with key players in China, India, and Europe. According to the International Textile Manufacturers Federation (ITMF), there has been a growing emphasis on digitizing textile manufacturing, with IoT-based solutions predicted to reach USD 2.5 billion in market value by 2025. One of the critical challenges remains in accurately measuring fabric production, mending data, and quality consistency, leading to inefficiencies across production lines.

B. Industry Challenges in Data Logging and Fabric Measurement

A specific challenge in textile production is the reliance on manual data logging for quality checks and fabric length measurement during the mending process. Operators often use manual counters or estimate fabric length visually, leading to inconsistencies in fabric quality reports. Furthermore, data on the quality of fabric mended by a loom is often not centralized, making it difficult for management to review the performance of individual looms and quality over time. The lack of automated logging in these areas introduces several risks:

1. Human Error: Manual entry results in data inaccuracies, with studies showing error rates as high as 5% in industries dependent on manual data logging.
2. Time-Consuming Processes: The time taken to log and process data manually can cause production delays, especially when large volumes of fabric are being produced and mended.
3. Lack of Real-Time Insights: Traditional methods make it difficult to generate real-time reports that could otherwise be used for predictive maintenance and inventory management.
4. Paper-Based Reporting: Current systems rely heavily on paper-based reports, making it hard to track long-term performance and review historical data.

C. Significance of Automation in Textile Data Logging

The incorporation of automation into textile manufacturing has shown to improve both efficiency and accuracy. Industry reports have demonstrated that IoT-enabled systems can improve data accuracy by up to 99%, reduce reporting time by 70%, and decrease overall operational costs by up to 20%. Specifically, automated data logging systems that measure fabric length and mending quality using sensors and microcontrollers provide real-time, accurate insights that are crucial for quality control and operational efficiency.

In this project, we address the textile industry’s need for an automated, integrated solution for textile mending data logging using an Arduino-based system, a thermal printer for on-site report generation, and an ESP8266 microcontroller for web-based data access.

II. LITERATURE SURVEY

A. Review of Existing Solutions

Several automated solutions have been proposed and implemented in the textile industry for fabric length measurement and data logging, focusing on real-time data capture and improving operational efficiency.

1) IoT-Based Fabric Measurement Systems

Research conducted by Zhang et al. (2019) demonstrated the use of IoT sensors for textile manufacturing, specifically for tracking fabric length and automating data entry. The use of sensors for fabric measurement, coupled with cloud integration for data sharing, resulted in an 85% reduction in manual logging time and a significant increase in data accuracy. However, their system faced limitations due to connectivity issues and cost overheads associated with cloud infrastructure.

2) Automation in Quality Control Systems

In another study, Kumar et al. (2020) explored the implementation of an Arduino-based fabric inspection system that used machine learning algorithms for identifying fabric defects. Their system showed that automated quality control could replace up to 80% of manual quality checks. Despite its success in defect detection, the system required extensive data processing power and incurred high costs, making it inaccessible for small-scale textile manufacturers.

3) Cloud-Based Data Logging Systems

Smith and Ali (2021) proposed a cloud-based data logging system integrated with RFID tags for textile inventory management. Their approach aimed to improve the traceability of fabric rolls within the production line. While successful, the focus of their solution was more on inventory management rather than real-time data collection during the production process, highlighting a gap in the real-time logging of fabric length and quality in mending processes.

III. PROBLEM STATEMENT AND SPECIFICATION

A. Problem Statement

The lack of an automated fabric mending data logging system in textile manufacturing results in operational inefficiencies, data inaccuracies, and limited access to real-time performance metrics. The primary challenge is to automate the process of fabric length measurement during mending, generate on-site reports, and provide centralized access to this data via a web interface.

B. Project Specifications

The system will include:

1. Arduino Board: Serves as the core controller for capturing encoder data and interacting with the user via an LCD and keypad.
2. Rotary Encoder: Tracks the fabric movement to provide real-time data on fabric length.
3. Adafruit Thermal Printer: Prints out the fabric length, loom number, and fabric quality on-site.
4. ESP8266 Module: Provides Wi-Fi connectivity to upload data to a centralized database accessible via a website.
5. Keypad and LCD: Allow the operator to input the loom number and fabric quality before mending starts.
6. Web Interface: The collected data will be viewable and downloadable through a website that interacts with the ESP8266 for real-time data updates.

IV. PROPOSED METHODOLOGY

A. System Design and implementation

This project proposes a system that integrates hardware components such as rotary encoders, Arduino, LCD, and thermal printer with the ESP8266 for web-based data access. The flow of the system is as follows:

1. User Input: The loom operator inputs the loom number and fabric quality using the keypad and LCD interface.
2. Fabric Measurement: The rotary encoder continuously measures the fabric length as it is being mended.
3. Real-Time Display: The fabric length is displayed on the LCD screen in real-time.
4. Report Generation: At the end of the mending process, the operator presses a button to print the report using the thermal printer.
5. Data Upload: The ESP8266 uploads the data to a central server, where it can be accessed via a web interface.
6. Web Access: Operators and management can access reports remotely,download the data, and track performance metrics across multiple looms.

B. Hardware Design

1. Arduino Controller: The Arduino controller will serve as the main processing unit. It will receive data from the rotary encoder, calculate fabric length, display this data on the LCD, and print the report through the thermal printer.
2. Rotary Encoder: The encoder will be mounted to the fabric roller to track the movement of the fabric. Based on the pulses generated by the encoder, the Arduino will calculate the length of fabric being processed.
3. ESP8266: The ESP8266 will manage the data transfer from the Arduino to the web server. It will use Wi-Fi connectivity to send the data in real-time, ensuring that remote users can access it as soon as the mending process is complete.

C. Software and Technologies used

1. Arduino IDE: Microcontroller Programming.
2. ThingSpeak: Cloud database for data storage and retrieval.
3. HTML, CSS, JavaScript: Web interface for real-time data visualization.
4. Excel Integration: Exports inspection reports for further analysis.

D. Working principle

1. The rotary encoder measures fabric length as it passes through the mending machine.
2. The operator enters the loom number and fabric quality via the keypad.
3. The Arduino processes the data and transmits it to the ESP32/ESP8266.
4. The ESP32 uploads the data to the cloud, storing it securely.
5. The thermal printer prints an inspection report for record-keeping.
6. The data is accessible through a web dashboard for remote monitoring.

E. Data Flow Diagram

V. RESULTS AND DISCUSSION

A. System Testing and Accuracy

The system was tested on different types of fabrics to measure length accuracy.

The rotary encoder provided 98% measurement accuracy, reducing manual errors.

Data logging efficiency improved compared to manual logging.

B. Performance Analysis

VI. OUTPUTS

A. Printer Module

B. Website

C. Report Format

D. Final Model

E. Results

Conclusion

The \"Textile Mending Data Logging System\" successfully automates the manual fabric inspection process by integrating a rotary encoder, Arduino, ESP, and a thermal printer into a single, cohesive system. This project significantly reduces the risk of human error in data logging and provides a streamlined solution for tracking and managing fabric inspections. The ability to store data in the cloud and access it via a web interface adds significant value to the system, enabling real-time data access and reporting. While the current system is effective for small-scale operations, future improvements could focus on enhancing scalability, optimizing real-time data synchronization, and expanding the system to include other aspects of textile production. Further exploration of more advanced cloud platforms or integration with enterprise systems could also be valuable for large-scale industrial applications.

References

[1] Zhang, H., et al. (2019). IoT in Textile Manufacturing: Enhancing Fabric Measurement and Data Logging. Journal of Textile Science, 15(3), 123-137. [2] Kumar, P., et al. (2020). Automated Defect Detection in Fabric Using Machine Learning Algorithms. International Journal of Industrial Automation, 34(5), 213- 229. [3] Smith, J., C Ali, R. (2021). Cloud-Based Textile Inventory Systems Using RFID and IoT. Proceedings of the International Conference on Automation and Robotics, 45(1), 78-84.

Copyright

Copyright © 2025 Shreya Sachin Bhokare, Riya Mahavir Murchite, Prachi Pravinkumar Karade, Pradnya Prakash Patil, Ashwini Devmore. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.