EAI Endorsed Transactions on Sustainable Manufacturing and Renewable Energy

Design and Implementation of a Line-Tracking Robot for Autonomous Navigation

2025-08-08T13:31:34+00:00

This study presents the design and implementation of a line-following Automated Guided Vehicle (AGV) for stock distribution using color detection. The AGV incorporates mechanical, electrical, and control engineering principles to improve warehouse automation. The primary goal is to develop an AGV that autonomously follows a designated path and sorts stocks by color. This project enhances students’ understanding of mechatronics system design by integrating fabrication, sensor integration, embedded programming, and control system optimization. The methodology includes system modeling, hardware selection, circuit design, algorithm implementation, and experimental validation. The AGV’s performance was assessed under different conditions to evaluate accuracy, stability, and adaptability. The AGV successfully follows predefined paths and accurately classifies stocks by color, optimizing logistics and automation processes. Experimental and simulation data confirm the system’s effectiveness. This project establishes a fundamental framework for AGV-based logistics and contributes to the advancement of autonomous warehouse solutions.

Research into the Influence of the Ease Coefficient on the Fit of Torso Dresses

2025-08-25T12:55:38+00:00

This approach offers an alternative method for size selection, one that accounts for the inherent variability in body measurements, thus providing a more tailored and accurate fit for consumers. This study aims to establish a dataset of ease coefficients for torso pattern design across various fabric types and body shapes to ensure proper garment fit. Data were collected from 120 women aged 18–30 in Ho Chi Minh City. Using principal component analysis, K-means clustering, discriminant analysis, and ANOVA via SPSS, participants were classified into four distinct body shape groups. A basic dress pattern was developed based on the average measurements of each group and simulated on different woven fabrics to assess fit and make necessary adjustments. The correlation between body-specific and average-group patterns was analyzed, resulting in a table of ease coefficients for multiple fabric types. Fit evaluations were conducted through 3D simulation and wearer feedback. The study provides ease coefficient data for the bust, waist, and hip areas of Vietnamese women aged 18–30, offering a foundation for the design of dresses and blouses in the fashion industry.

Optimizing the Needle - Thread - Fabric Interaction for Enhanced Seam Performance in Clothing Manufacturing

2025-09-16T09:40:08+00:00

In apparel industry, product quality is always the key factor determining the success of a business. Not only does this create customer satisfaction, but product quality also directly affects the business's reputation, competitiveness, and market expansion opportunities. In this, seam appearance is one of the most important quality requirements, directly determining customer satisfaction. This paper examines the relationship and impact of three most important specifications, including needle-thread compatibility, fabric weight on the quality of seam performance. Through the experiment according to the full factorial design, this paper has determined the influence of each factor, in which the fabric weight is the factor with the most significant impact on the variation of the seam length, followed by the needle size and thread size. Determining the relationship between material parameters (fabric, thread) and equipment parameters (needle) not only helps to minimize errors but also creates the premise for building standardization processes for technical parameters according to each specific product group. These results will support the operator to adjust the machine faster, more accurately and less dependent on manual experience, thereby improving productivity and efficiency of the whole system.