Using Machine Learning for Data Quality Assessment for the Textile and Clothing Digital Product Passport
Year: 2025
Type: article
Abstract: The implementation of the digital product passport in the Textile & Clothing (T&C) industrial sector can help in the transition to the circular economy and can bring many benefits both socially and environmentally, but its implementation brings many challenges. One of the challenges is the integration of data from all types of industry involved in the value chain, from raw material creation, transportation, transformation, etc. This integration must be inclusive in all aspects. Therefore, small and medium-sized industries cannot be excluded, nor can companies at the lowest level of technological evolution. With such a huge diversity of companies and such disparate levels of digitization, from the manual production of traditional lace and embroidery without any automation to large manufacturing companies where everything is guided automatically and data is collected by Internet Of Things (IoT) devices, it is necessary to create an uniform and homogeneous data validation. In this article we propose the creation of an Application Programming Interface (API) that provides a set of validation services based on Machine Learning (ML) algorithms thus being prepared to integrate new types of products and new productive activities in a constantly changing sector.
Source: IFAC-PapersOnLine
Authors: Estrela F. Cruz, Rodrigo Rodrigues, Sérgio Serra, Pedro Silva, A.M. Rosado da Cruz
Institution: Universidade Politécnica de Viana do Castelo
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4414568184