Factories of the Future in Digitization of Industrial Urban Areas

Author:

Bolshakov Nikolai1,Celani Alberto2ORCID,Badenko Vladimir1ORCID,Benedicto Rafael Magdalena3ORCID

Affiliation:

1. Civil Engineering Institute, Peter the Great St. Petersburg Polytechnic University, 195251 St. Petersburg, Russia

2. ABC Department, Politecnico di Milano, 20133 Milano, Italy

3. Escola Tècnica Superior d’Enginyeria ETSE-UV, University of Valencia, 46010 Valencia, Spain

Abstract

This paper delves into the integration of Factories of the Future (FoF) and digital twin technologies within urban contexts, marking a significant leap in Smart Cities development. We present a thorough exploration of the principles and a scientifically grounded framework designed for seamlessly blending advanced manufacturing systems with the urban environment’s digital and physical aspects. Our detailed analysis has identified core principles crucial for this integration, focusing on interoperability, sustainability, adaptability, stakeholder collaboration, and strong data governance. We propose a structured framework that puts these principles into action, outlining strategic routes for incorporating digital twin and Building Information Modeling (BIM) technologies into FoF, establishing public-private partnerships, enhancing education and workforce development, and setting up mechanisms for ongoing evaluation and enhancement. The potential of this integration to transform urban development is vast, providing a model for boosting operational efficiency, driving economic growth, and enhancing urban livability. Although challenges exist in realizing this vision, our research offers practical insights and strategies for cities and industries to effectively navigate the complexities of the digital era. This contribution enriches the growing field of urban science, advocating for a harmonious integration of industrial production with urban development in the Smart Cities framework.

Funder

Ministry of Science and Higher Education of the Russian Federation

Publisher

MDPI AG

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3