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DATA-DRIVEN SMART MANUFACTURING: CASE STUDY OF WORKFORCE MANAGEMENT PROCESS IN AN ITALIAN LEATHER GOODS COMPANY

Published online by Cambridge University Press:  19 June 2023

Giorgia Pietroni  and
Marco Marconi
Giorgia Pietroni*
Affiliation:
Università degli Studi della Tuscia
Marco Marconi
Affiliation:
Università degli Studi della Tuscia
*
Pietroni, Giorgia, Università degli Studi della Tuscia, Italy, [email protected]

Abstract

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Digitalization is one of the fundamental pillars of Industry 4.0. Within smart factories, Big Data Analytics systems play a key role in supporting the decision-making process of various stages of business processes. In this context, this research aims to identify solutions able to process large volumes of data from digital business processes with the final goal of adding value to the organisation. More specifically, the research deals with the implementation of a digital manufacturing tool able to digitize the workforce management process. The research has been applied in the case study of an Italian manufacturing company operating in the leather goods sector through the digitalization of the workforce management by a cloud-based platform. The implementation of the tool increases the efficiency of the production process, provides efficient management and integrates workforce data into one system. The implemented tool generates a large volume of data, the final goal is to make data user-friendly to support business decisions. Digitisation provides an exchange of information to support managers to make confident decisions.

Keywords

Industry 4.0Big dataDigital / Digitised engineering value chainsWorkforce Management
Type
Article
Information
Proceedings of the Design Society , Volume 3: ICED23 , July 2023 , pp. 1127 - 1136
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2023. Published by Cambridge University Press

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