Call for Papers

2022-08-19

When titans meet – Industry 4.0, Lean and Circular Economy opportunities towards operational excellence and sustainability

 

Guest editor(s): Daniel Nascimento¹, Guilherme Tortorella², Rodrigo Goyannes Gusmão Caiado³. Juan Manuel Maqueira¹

¹ University of Jaén, Spain

² The University of Melbourne, Australia

³ Pontifical Catholic University of Rio de Janeiro, Brazil

The effects of climate change are perceived by society as increasingly severe and intense, causing frequent catastrophes and expectations of a threatening future. According to the United State Environmental Protection Agency report, the industry comprises 22.9% of the total emissions, with iron and steel and metallurgical coke production the main factor with 41.3% of the total emissions in the industry in 2019. In fact, the main opportunities for reducing emissions in the industry are Energy Efficiency, Fuel Switching, Recycling, Training, and Awareness. One of these opportunities is recycling iron and steel to manufacture new raw materials from scrap, generating new products, and reducing waste, CO2 emissions, and mineral exploration.

Agenda 2030 is a blueprint for ending poverty, protecting the planet, and improving the prospects of people around the world by transforming society toward sustainable development. Considering these facts, the integrated practices of Circular Economy (CE) and Industry 4.0 (I4.0) technologies are critical success factors to increase the capacity and efficiency of this transformation toward sustainability. Although several studies related to I4.0 and CE or numerous articles focused on Lean Management (LM) and I4.0 exist, no work has been identified in the literature to date that considers the integration of I4.0, LM, and CE to achieve sustainable development. LM is a management system oriented toward efficiency that could complement the interrelation between I4.0 and CE. In this context, integrating LM, I4.0, and CE practices is a crucial success requirement for circular production systems to contribute to the continuous and incremental improvement of Sustainable Supply Chains.

To solve real-world operations and supply chain problems in sustainable, circular, and digitalization contexts surrounded by complex, social, environmental, technical, political, and economic interactions with natural systems, the need for practical, robust, and intelligent models is still urgent.

In recent decades, several multi-criteria decision-making (MCDM) methods, and multivariate and machine learning models have been proposed to solve operational excellence and sustainability problems, attracting much attention from academics and practitioners. In this context, there is a need to explore I4.0, Lean and Circular opportunities, and capabilities, considering sustainable development dimensions jointly and individually, with the help of multi-methods and interdisciplinary approaches (such as statistics, mathematics, decision sciences, and social sciences).

 

Topics of interest in this Special Issue:

  • Business Models that use LM and I4.0 to Improve CE practices;
  • Systematic Literature Review (SLR) or Scoping Reviews that integrate LM, I4.0, and CE;
  • Case Studies applying LM, I4.0, and CE in Real World Industry;
  • Theoretical Frameworks that use Lean 4.0 to Improve CE practices;
  • Empirical Studies using statistical techniques, such as Structural Equation Modelling (SEM) to Analyse the Casual Relationship between LM, I4.0, and CE;
  • Data mining or Machine learning techniques for discovering hidden patterns and relationships in operations and supply chain management (OSCM);
  • MCDM methods and hybrid decision-making models in sustainable-OSCM or OSCM4.0 problems;
  • Data-driven MCDM models for evaluating circular, lean and digital OSCM.

 

 

Important dates

 

Manuscript Submission Deadline: February 2023

Notification of First Decision: April 2023

Revised Version Submission: May 2023

Final Decision: July 2023

 

Note: The actor must describe in the body article that it belongs to the special issue.