Data-driven smart manufacturing: case study of workforce management process in an Italian leather goods company

DS 122: Proceedings of the Design Society: 24th International Conference on Engineering Design (ICED23)

Year: 2023
Editor: Kevin Otto, Boris Eisenbart, Claudia Eckert, Benoit Eynard, Dieter Krause, Josef Oehmen, Nadège Troussier
Author: Pietroni, Giorgia; Marconi, Marco
Series: ICED
Institution: Università degli Studi della Tuscia
Section: Design Methods
Page(s): 1127-1136
DOI number: https://doi.org/10.1017/pds.2023.113
ISBN: -
ISSN: -

Abstract

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 4.0, Big data, Digital / Digitised engineering value chains, Workforce Management