作者
Virginia Fani, Sara Antomarioni, Romeo Bandinelli, Filippo Emanuele Ciarapica
发表日期
2023/2/10
期刊
Applied Sciences
卷号
13
期号
4
页码范围
2317
出版商
MDPI
简介
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The current paper proposes an approach to improve data analysis and visualization through Association Rule Mining and Augmented Reality. The applicability of the approach has been verified through a case study, providing Augmented Reality devices to expert and non-expert (or trainees) operators and letting them experience the adoption of the proposed technology in their daily quality management activities.
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 …
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V Fani, S Antomarioni, R Bandinelli, FE Ciarapica - Applied Sciences, 2023