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Data Mining and Augmented Reality: An Application to the Fashion Industry

Authors :
Virginia Fani
Sara Antomarioni
Romeo Bandinelli
Filippo Emanuele Ciarapica
Source :
Applied Sciences, Vol 13, Iss 4, p 2317 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

The wider implementation of Industry 4.0 technologies in several sectors is increasing the amount of data regularly collected by companies. Those unstructured data need to be quickly elaborated to make on-time decisions, and the information extracted needs to be clearly visualized to speed up operations. This is strongly perceived in the quality field, where effective management of the trade-off between increasing quality controls to intercept product defects and decreasing them to reduce the delivery time represents a competitive challenge. A framework to improve data analysis and visualization in quality management is proposed, and its applicability is demonstrated with a case study in the fashion industry. A questionnaire assesses its on-field usability. The main findings refer to overcoming the lack in the literature of a decision support framework based on the joint application of association rules mining and augmented reality. The successful implementation in a real scenario has a twofold aim: on the one hand, sample sizes are strategically revised according to the supplier performance per product category and material; on the other hand, the daily quality controls are speeded up through accurate suggestions about the most occurrent defect and location per product characteristics, integrated with extra tips only for trainees.

Details

Language :
English
ISSN :
20763417
Volume :
13
Issue :
4
Database :
Directory of Open Access Journals
Journal :
Applied Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.000a435a7a74cbca8076839f37b6ce8
Document Type :
article
Full Text :
https://doi.org/10.3390/app13042317