The impacts of digital technologies on coping with the COVID-19 pandemic in the manufacturing industry: a systematic literature review

Abstract

The COVID-19 pandemic’s impacts have been devastating for the global economy, and particularly for manufacturing companies. Many firms were unprepared for a crisis of this magnitude and adapted their operations in an ad-hoc manner. Some of these adaptations were facilitated by digital technologies (DTs). This article examines extant literature using a systematic review methodology in order to extend our understanding of what DTs have been used in manufacturing companies during the pandemic, how DTs have helped manufacturing companies cope with the pandemic, and how these innovations can be used in the post-pandemic world. The major outcome of our study is a novel classification of DT applications in the pandemic setting in the manufacturing industry. In addition, we propose an agenda for future research.

KEYWORDS:

• COVID-19
• Digital technologies
• SCOR
• systematic literature review
• manufacturing

Acknowledgement

The authors sincerely thank anonymous reviewers whose comments greatly contributed to the development of this paper.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

Data related with this paper is available with the corresponding author and will be available upon reasonable request.

Additional information

Notes on contributors

Marco Ardolino

Marco Ardolino is Research Fellow at Università degli Studi di Brescia (Italy). Since 2013 he has carried out research and teaching activities at the Department of Mechanical and Industrial Engineering of the Università degli Studi di Brescia (Italy), and he is a member of the Research Laboratory RISE (Research & Innovation for Smart Enterprises). Within RISE Laboratory he carries out his research on the adoption of digital technologies to support manufacturing companies, in particular for logistics processes and supply chain management. He is author of more than 30 scientific publications on international conferences and journals.

Andrea Bacchetti

Andrea Bacchetti is researcher at the University of Brescia (Italy); in 2011 he holds a doctoral degree in Design and Management of Production and Logistic Systems at the same university. His research involves supply chain management, demand forecasting, inventory management and, recently, digital manufacturing. He is senior member of the RISE (Research and Innovation for Smart Enterprises) Laboratory (www.rise.it) and he is senior partner at IQ Consulting (www.iqconsulting.it), a spin-off of University of Brescia. He is also director of Smart AgriFood Observatory (https://www.osservatori.net/it/ricerche/osservatori-attivi/smart-agrifood). He is author of more than 50 scientific publications on international conferences and journals.

Alexandre Dolgui

Alexandre Dolgui is an IISE Fellow, Distinguished Professor, and the Head of Automation, Production and Computer Sciences Department at the IMT Atlantique, France. His research focuses on manufacturing line design, production planning and supply chain optimization with stochastic modelling and combinatorial optimisation approaches. His main results are based on the exact mathematical programming methods and their intelligent coupling with heuristics and metaheuristics algorithms. He published 5 books, comprising Supply Chain Engineering: Useful Methods and Techniques (Springer), and more than 285 refereed journal papers. He is the Editor-in-Chief of the International Journal of Production Research and member of Editorial Board of 25 other journals, including International Journal of Production Economics and Computers & Industrial Engineering.

Guglielmo Franchini

Guglielmo Franchini received his bachelor degree in management engineering in 2021 at the Università degli Studi di Brescia. He has been working in the field of industrial manufacturing since 2010 and has developed a wide practical knowledge regarding production processes of metal components and factory digitization. Started his career as a CNC machine operator and programmer, is currently production process engineer and cycle optimisation specialist for an automotive components manufacturing company.

Dmitry Ivanov

Dmitry Ivanov is a professor of supply chain and operations management at Berlin School of Economics and Law (HWR Berlin). His publication list includes around 380 publications, including over 120 papers in international academic journals and leading textbooks Global Supply Chain and Operations Management and Introduction to Supply Chain Resilience. His main research interests and results span the resilience and ripple effect in supply chains, risk analytics, and digital twins. He co-edits International Journal of Integrated Supply Management (IJISM) and is an associate editor of the International Journal of Production Research (IJPR) and OMEGA. He is Chairman of IFAC TC 5.2 “Manufacturing Modelling for Management and Control”.

Anand Nair

Anand Nair is the Eli Broad Endowed Professor at Michigan State University. He has worked with organizations on issues such as inventory management, forecasting, pricing, capacity planning, lean systems, manufacturing planning and control, quality management, contracting, product development, process improvement and technology implementation. His research examines how firms, teams, and individuals learn, adapt, and organize to manage processes, supplies, technology, and innovation, and the associated performance implications. He has published articles in leading journals and is currently serving as a Department Editor for the Journal of Operations Management and an Associate Editor for Decision Sciences. He holds the Certified Fellow in Production and Inventory Management (CFPIM) designation from The Association of Supply Chain Management (ASCM) and has completed the deep learning specialization from Deeplearning. AI and Data Science Methodology certification from IBM.