PreprintArticleVersion 1Preserved in Portico This version is not peer-reviewed
Designing Digital Twin with IoT and AI in Warehouse to Support Optimization and Safety in Engineer-to-Order Manufacturing Process for Prefabricated Building Products
Version 1
: Received: 17 June 2024 / Approved: 17 June 2024 / Online: 18 June 2024 (08:29:00 CEST)
How to cite:
Pracucci, A. Designing Digital Twin with IoT and AI in Warehouse to Support Optimization and Safety in Engineer-to-Order Manufacturing Process for Prefabricated Building Products. Preprints2024, 2024061176. https://doi.org/10.20944/preprints202406.1176.v1
Pracucci, A. Designing Digital Twin with IoT and AI in Warehouse to Support Optimization and Safety in Engineer-to-Order Manufacturing Process for Prefabricated Building Products. Preprints 2024, 2024061176. https://doi.org/10.20944/preprints202406.1176.v1
Pracucci, A. Designing Digital Twin with IoT and AI in Warehouse to Support Optimization and Safety in Engineer-to-Order Manufacturing Process for Prefabricated Building Products. Preprints2024, 2024061176. https://doi.org/10.20944/preprints202406.1176.v1
APA Style
Pracucci, A. (2024). Designing Digital Twin with IoT and AI in Warehouse to Support Optimization and Safety in Engineer-to-Order Manufacturing Process for Prefabricated Building Products. Preprints. https://doi.org/10.20944/preprints202406.1176.v1
Chicago/Turabian Style
Pracucci, A. 2024 "Designing Digital Twin with IoT and AI in Warehouse to Support Optimization and Safety in Engineer-to-Order Manufacturing Process for Prefabricated Building Products" Preprints. https://doi.org/10.20944/preprints202406.1176.v1
Abstract
Engineer-to-order manufacturing, characterized by highly customized products and complex workflows, presents unique challenges for warehouse management and operational efficiency. This paper explores the potential of a digital twin as a transformative solution for engineer-to-order environments in manufacturing companies realizing prefabricated building components. The paper outlines a methodology encompassing users’ requirement and the design to support development of a digital twin that integrates Internet of Things devices, Building Information Modeling, and Artificial Intelligence capabilities. It delves into the specific challenges of outdoor warehouse optimization and worker safety within the context of engineer-to-order manufacturing, and how the digital twin aims to address these issues through data collection, analysis, and visualization. The research is conducted through an in-depth analysis of the warehouse of Focchi S.p.A., a leading manufacturer of high-tech prefabricated building envelopes. Focchi's production processes and stakeholder interactions are investigated, and the paper identifies key user groups and their multiple requirements for the warehouse improvement. It also examines the potential of the digital twin to streamline communication, improve decision-making, and enhance safety protocols. While preliminary testing results are not yet available, the paper concludes by underlining the significant opportunities offered by a BIM, IoT, and AI-powered Digital Twin for engineer-to-order manufacturers. The research, developed within the IRIS project serves as a promising model for integrating digital technologies into complex warehouse environments, paving the way for increased efficiency, safety, and ultimately, a competitive edge in the market of manufacturing companies working in construction industry.
Keywords
digital twin; engineer-to-order manufacturing; warehouse management; internet of things; building information modeling; artificial intelligence; safety; optimization; customization manufacturing; built environment
Subject
Engineering, Architecture, Building and Construction
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
