Implementing industry 4.0 for flexibility, quality, and productivity improvement: technology arrangements for different purposes

ABSTRACT

Productivity, quality, and flexibility are key production targets pursued by companies that adopt Industry 4.0. However, it is unclear how Industry 4.0 technologies can help achieve these different and sometimes competing targets. This study investigates this relationship through a survey of 92 manufacturers. The study employs Exploratory Factor Analysis to define four main technology arrangements based on 18 Industry 4.0 technologies: Vertical Integration, Virtual Manufacturing, Advanced Manufacturing Processing Technologies, and Online Traceability. Then, independent samples tests were conducted to compare the implementation status of these arrangements when manufacturing flexibility, process quality, and productivity are (or are not) pursued as the main production targets. The results show that Vertical Integration is a general-purpose technology arrangement because it supports all targets. On the other hand, Virtual Manufacturing and Online Traceability are specific-purpose arrangements, adopted especially for flexibility and productivity targets, respectively. Advanced Manufacturing Processing Technologies, in turn, is an integrative-purpose technology arrangement since it is adopted when two competing targets are pursued: productivity and manufacturing flexibility. The study ends with a decision model to implement Industry 4.0 based on the production targets a company may pursue. It shows the interconnection and trade-offs between these production targets and the Industry 4.0 technologies adopted.

KEYWORDS:

• Industry 4.0
• production targets
• smart manufacturing
• technology adoption
• digital transformation

Acknowledgments

This project received research funds from the Brazilian National Council for Scientific and Technological Development (CNPq – Conselho Nacional de Desenvolvimento Científico e Tecnológico) (Process n. 443680/2018-3 and 306034/2018-2), the Research Council of the State of Rio Grande do Sul (FAPERGS, Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul) (Process n. 17/2551-0001) and the Research Coordination of the Brazilian Ministry of Education (CAPES) (PhD scholarship). One of the authors of this project was also financially supported by C-MAST/ Centre for Mechanical and Aerospace Science and Technologies of the University of Beira Interior, and by the project INDTECH 4.0, co-financed by the PT2020 and COMPETE2020 programs, and the European Union through the European Regional Development Fund (ERDF) and UID/EMS/00151/2019.

Disclosure statement

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

Data availability statement

Data available on request due to privacy restrictions

Notes

1 Other variables from this survey were used in Frank, Dalenogare, and Ayala (2019). This other study focused on investigating the implementation patterns of Industry 4.0 technologies through cluster analysis. Frank, Dalenogare, and Ayala (2019) did not consider production target variables. They focused on other ‘smart dimensions’ like smart products, smart working, and smart supply chain complementary to smart manufacturing. In this sense, while this present study deepens the manufacturing technology variables and connects them with production targets (motivations), the one from Frank, Dalenogare, and Ayala (2019) has a broader scope and focuses on the breath of Industry 4.0 technologies complementary to the manufacturing technology variables. Therefore, both studies are complementary in their research focus.

Additional information

Funding

This work was supported by CAPES: [Grant Number PhD Scholarship (CAPES-PROEX)]; CNPQ: [Grant Number 306034/2018-2,443680/2018-3]; European Commission:[Grant Number INDTECH 4.0]; Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul: [Grant Number 17/2551-0001].

Notes on contributors

Daisy Valle Enrique

Daisy Valle Enrique, B.S. in Industrial Engineering from the Instituto Politécnico José A. Echeverría (Cuba) and M.S in Industrial Engineering from the Federal University of Rio Grande do Sul, Brazil. She is PhD candidate at the Department of Industrial Engineering of the Federal University of Rio Grande do Sul and at the Centre for Mechanical and Aerospace Science and Technologies of University of Beira Interior, Portugal. Her main research interests include strategic and organisational management, digital transformation and operation management.

Giuliano Almeida Marodin

Giuliano Almeida Marodin is a Clinical Associate Professor at the Moore School of Business at the University of South Carolina. He received his PhD, his Master’s degree in industrial engineering and a BBA degree from the Federal University of Rio Grande do Sul in Brazil, where he also worked as an adjunct professor for the Department of Industrial Engineering (2013 and 2014) and the Business School (2007 and 2008). He was a Visiting Professor at the Department of Management Sciences, The Ohio State University for the academic year of 2014/2015. Since 2002, he has worked as a consultant implementing lean production systems in firms from several sectors, also as a partner of Lean Enterprise Institute in Brazil.

Fernando Bigares Charrua Santos

Fernando Charrua-Santos, Ph.D., is an Assistant Professor in the Department of Electromechanical Engineering of the University of Beira Interior and a member of the Center for Mechanical and Aerospace Science and Technologies Research Group. He graduated in Industrial Production and Management Engineering (1995) at Beira Interior University (Portugal). He received an MSc in Mechanical Engineering at Beira Interior University in 2001 and his Ph.D. in Production Engineering (2009). During this period, he was the coordinator of more than a dozen of applied research projects in process optimisation and operations scheduling, always in the industrial environment. He has been involved in several research projects. Doctor (Ph.D.) Santos, also, is author or co-author of chapters and congresses proceedings.

Alejandro G. Frank

Alejandro G. Frank, Ph.D. is an Associate Professor at the Department of Industrial Engineering of the Federal University of Rio Grande do Sul (UFRGS). He is also the Chair of Graduate Studies — UFRGS Industrial Engineering Program, the Director of the UFRGS Organizational Engineering Group, and an Associate Editor at Journal of Knowledge Management (Emerald). He received Ph.D. and M.Eng. degrees in Industrial Engineering from UFRGS, Brazil, and a B.Eng. degree in Industrial Engineering from the National University of Misiones (UNaM), Argentina. He has been a visiting scholar and research affiliate at the Massachusetts Institute of Technology (USA), and a visiting researcher at Politecnico di Milano (Italy). His research is devoted to the interface between operations and technology management, with emphasis on digital transformation, Industry 4.0, and servitized business models in manufacturing firms.