Sustainability

Editorial

5 pages, 217 KiB

Open AccessEditorial

Manufacturing and Management Paradigms, Methods and Tools for Sustainable Industry 4.0-Oriented Manufacturing Systems

by Leonilde Varela, Paulo Ávila, Hélio Castro, Goran D. Putnik, Luís Miguel Ciravegna Fonseca and Luís Ferreira

Sustainability 2022, 14(3), 1574; https://doi.org/10.3390/su14031574 - 29 Jan 2022

Cited by 11 | Viewed by 2216

Abstract

In the current Industry 4 [...] Full article

(This article belongs to the Special Issue Manufacturing and Management Paradigms, Methods and Tools for Sustainable Industry 4.0 oriented Manufacturing Systems)

Research

Jump to: Editorial, Review

27 pages, 1997 KiB

Open AccessArticle

Paradigms, Methods, and Tools for Multicriteria Decision Models in Sustainable Industry 4.0 Oriented Manufacturing Systems

by Lucas Borges Leal Da Silva, Evanielle Barbosa Ferreira, Rodrigo José Pires Ferreira, Eduarda Asfora Frej, Lucia Reis Peixoto Roselli and Adiel Teixeira De Almeida

Sustainability 2023, 15(11), 8869; https://doi.org/10.3390/su15118869 - 31 May 2023

Cited by 6 | Viewed by 1916

Abstract

The rise of Industry 4.0 tools transforms the way production plants are planned, controlled, and monitored, allowing organizations to achieve greater flexibility, efficiency, and cost reduction. This way, the use of emerging technologies provides a new look at the industrial sector, particularly concerning [...] Read more.

The rise of Industry 4.0 tools transforms the way production plants are planned, controlled, and monitored, allowing organizations to achieve greater flexibility, efficiency, and cost reduction. This way, the use of emerging technologies provides a new look at the industrial sector, particularly concerning sustainability issues in a society that suffers worsening effects from climate change. On the other hand, the degree of success when implementing Industry 4.0 practices in sustainable-oriented manufacturing systems is closely related to hard decision-making, which involves, in practice, multiple and even conflicting criteria to model multidimensional problems. For that reason, it is worth recognizing the importance of the multi-criteria decision-making/aid (MCDM/A) approach to support decision modeling and application so that this research field can be better explored to enhance Industry 4.0 implementation and innovative advances in operations management. Given this backdrop, this paper undertakes a systematic literature review (SLR) of 118 papers, thereby combining a set of predefined keywords with several exclusion criteria to detect the literature that is related to sustainable decisions in manufacturing systems that introduced Industry 4.0 practices in the Web of Science (Clarivate Analytics) database. Cross-matching important research metrics from these papers encourages this work to provide readers with two axes of discussion with the aid of five research questions: a bibliometric analysis and a content analysis. Among many findings, some guidelines for decision-making are put forward to share insights and provide decision-makers, scholars, experts, stakeholders, and other professionals with an overall managerial background when applying sustainable-oriented multicriteria models in manufacturing systems. Full article

(This article belongs to the Special Issue Manufacturing and Management Paradigms, Methods and Tools for Sustainable Industry 4.0 oriented Manufacturing Systems)

► Show Figures

Figure 1

23 pages, 8253 KiB

Open AccessArticle

Leveraging Blockchain to Support Collaborative Distributed Manufacturing Scheduling

by Veera Babu Ramakurthi, Vijaya Kumar Manupati, Leonilde Varela and Goran Putnik

Sustainability 2023, 15(4), 3283; https://doi.org/10.3390/su15043283 - 10 Feb 2023

Cited by 1 | Viewed by 2154

Abstract

The recent trend in collaborative distributed manufacturing scheduling (CDMS) has gained significant importance in extended, networked, and virtual manufacturing environments due to its adaptability and integration potential. In a distributed manufacturing environment, CDMS can occur within a single factory or across multiple companies [...] Read more.

The recent trend in collaborative distributed manufacturing scheduling (CDMS) has gained significant importance in extended, networked, and virtual manufacturing environments due to its adaptability and integration potential. In a distributed manufacturing environment, CDMS can occur within a single factory or across multiple companies in a dynamic and variable extended or virtual organization. For effective collaboration, the CDMS system must be secure, transparent, and trustworthy. This paper proposes a blockchain-based model for CDMS and discusses its implementation in the processing of manufacturing functions, specifically joint process planning and scheduling. An illustrative example is used to demonstrate the application of the proposed approach and its potential to enhance the management processes of CDMS enterprises. The results of the analysis indicate that the proposed blockchain approach can effectively facilitate communication and integration among CDMS enterprises. Additionally, the approach can be expanded to more complex manufacturing environments under different conditions. Full article

(This article belongs to the Special Issue Manufacturing and Management Paradigms, Methods and Tools for Sustainable Industry 4.0 oriented Manufacturing Systems)

► Show Figures

Figure 1

20 pages, 2696 KiB

Open AccessArticle

Job Adjustment Strategy for Predictive Maintenance in Semi-Fully Flexible Systems Based on Machine Health Status

by Thirupathi Samala, Vijaya Kumar Manupati, Bethalam Brahma Sai Nikhilesh, Maria Leonilde Rocha Varela and Goran Putnik

Sustainability 2021, 13(9), 5295; https://doi.org/10.3390/su13095295 - 10 May 2021

Cited by 2 | Viewed by 2134

Abstract

Complex systems consist of multiple machines that are designed with a certain extent of redundancy to control any unanticipated events. The productivity of complex systems is highly affected by unexpected simultaneous machine failures due to overrunning of machines, improper maintenance, and natural characteristics. [...] Read more.

Complex systems consist of multiple machines that are designed with a certain extent of redundancy to control any unanticipated events. The productivity of complex systems is highly affected by unexpected simultaneous machine failures due to overrunning of machines, improper maintenance, and natural characteristics. We proposed realistic configurations with multiple machines having several flexibilities to handle the above issues. The objectives of the proposed model are to reduce simultaneous machine failures by slowing down the pace of degradation of machines, to improve the average occurrence of the first failure time of machines, and to decrease the loss of production. An approach has been developed using each machine’s degradation information to predict the machine’s residual life based on which the job adjustment strategy where machines with a lower health status will be given a high number of jobs to perform is proposed. This approach is validated by applying it in a fabric weaving industry as a real-world case study under different scenarios and the performance is compared with two other key benchmark strategies. Full article

(This article belongs to the Special Issue Manufacturing and Management Paradigms, Methods and Tools for Sustainable Industry 4.0 oriented Manufacturing Systems)

► Show Figures

Figure 1

11 pages, 1891 KiB

Open AccessArticle

Simulation-Based Decision Support System to Improve Material Flow of a Textile Company

by Vítor Silva, Luís Pinto Ferreira, Francisco J. G. Silva, Benny Tjahjono and Paulo Ávila

Sustainability 2021, 13(5), 2947; https://doi.org/10.3390/su13052947 - 9 Mar 2021

Cited by 12 | Viewed by 4498

Abstract

To remain competitive, companies must continuously improve the processes at hand, be they administrative, production, or logistics. The objective of the study described in this paper was to develop a decision-making tool based on a simulation model to support the production of knits [...] Read more.

To remain competitive, companies must continuously improve the processes at hand, be they administrative, production, or logistics. The objective of the study described in this paper was to develop a decision-making tool based on a simulation model to support the production of knits and damask fabrics. The tool was used to test different control strategies for material flow, from the raw material warehouse to the finished product warehouse, and thus can also be used to evaluate the impacts of these strategies on the productivity. The data upon which the decision support tool was built were collected from five sectors of the plant: the raw material warehouse, knit production, damask production, finishing work, and the finished product warehouse. The decision support tool met the objectives of the project, with all five strategies developed showing positive results. Knit and damask production rates increased by up to 8% and 44%, respectively, and a reduction of 75% was observed in the waiting time on the point of entry to the finishing work area, compared to the company’s existing system. Full article

(This article belongs to the Special Issue Manufacturing and Management Paradigms, Methods and Tools for Sustainable Industry 4.0 oriented Manufacturing Systems)

► Show Figures

Figure 1

16 pages, 405 KiB

Open AccessArticle

Optimal MTS and MTO Hybrid Production System for a Single Product Under the Cap-And-Trade Environment

by Shouyao Xiong, Yuanyuan Feng and Kai Huang

Sustainability 2020, 12(6), 2426; https://doi.org/10.3390/su12062426 - 20 Mar 2020

Cited by 9 | Viewed by 4540

Abstract

This paper studies the optimal production planning in a hybrid Make-To-Stock (MTS) and Make-To-Order (MTO) production system for a single product under the cap-and-trade environment. The manufacturer aims to minimize the total cost in production, inventory and emissions allowances trading. The decisions include [...] Read more.

This paper studies the optimal production planning in a hybrid Make-To-Stock (MTS) and Make-To-Order (MTO) production system for a single product under the cap-and-trade environment. The manufacturer aims to minimize the total cost in production, inventory and emissions allowances trading. The decisions include the selection of production mode (pure MTS, pure MTO or hybrid MTS/MTO), the inventory and emissions trading quantity. We derive the optimal solution analytically. We show that the cost of optimal MTO/MTS hybrid production strategy is remarkably less than that of either pure MTO or pure MTS production strategy alone. Compared with the no initial carbon quota and trading environment, there are significant differences in the optimal production decisions under trading environment. When the emissions cost is a source of costs, the manufacturer has to face more costs pressure even if there is no emissions allowance trading. In particular, the results show that the initial emissions allowance determines the optimal production decision and emissions allowance trading decision in cases where the difference between the inventory cost for per unit product and the delayed delivery cost for per unit order is between the minimum and the maximum emissions cost and has no effect on production mode and emissions allowances trading decision in other cases. These conclusions will provide optimal production decision and carbon trading decision for the manufacture under a cap-and-trade environment. Full article

(This article belongs to the Special Issue Manufacturing and Management Paradigms, Methods and Tools for Sustainable Industry 4.0 oriented Manufacturing Systems)

► Show Figures

Graphical abstract

20 pages, 1282 KiB

Open AccessArticle

Malmquist Indexes of Productivity Change in Tunisian Manufacturing Industries

by Houyem Zrelli, Abdullah H. Alsharif and Iskander Tlili

Sustainability 2020, 12(4), 1367; https://doi.org/10.3390/su12041367 - 13 Feb 2020

Cited by 8 | Viewed by 4189

Abstract

This research aims to investigate the extent and nature of productivity growth in manufacturing industries using nonparametric frontier techniques. In order to decompose the total factor productivity (TFP) into technical efficiency change and technological change we use the output-oriented Malmquist productivity index method [...] Read more.

This research aims to investigate the extent and nature of productivity growth in manufacturing industries using nonparametric frontier techniques. In order to decompose the total factor productivity (TFP) into technical efficiency change and technological change we use the output-oriented Malmquist productivity index method for 34 Tunisian manufacturing industries over the period 2002–2016. The results indicated that TFP has witnessed an average growth of two percent over the period 2002–2016. The productivity growth identified was attributed to the improvements in the technology (or frontier-shift) rather than improvements or changes in the efficiency. Full article

(This article belongs to the Special Issue Manufacturing and Management Paradigms, Methods and Tools for Sustainable Industry 4.0 oriented Manufacturing Systems)

► Show Figures

Figure 1

Review

Jump to: Editorial, Research

21 pages, 1341 KiB

Open AccessReview

Impact of Industry 4.0 on Environmental Sustainability

by Judit Oláh, Nemer Aburumman, József Popp, Muhammad Asif Khan, Hossam Haddad and Nicodemus Kitukutha

Sustainability 2020, 12(11), 4674; https://doi.org/10.3390/su12114674 - 8 Jun 2020

Cited by 332 | Viewed by 40597

Abstract

Industry 4.0 is a concept that originated from the German industry, and whose essence is the use of technology for efficient production. In business today, the emergence of Industry 4.0 for production, and its related technologies, such as the Internet of Things (IoT) [...] Read more.

Industry 4.0 is a concept that originated from the German industry, and whose essence is the use of technology for efficient production. In business today, the emergence of Industry 4.0 for production, and its related technologies, such as the Internet of Things (IoT) and cyber-physical systems, amongst others, have, however, a negative impact on environmental sustainability as a result of air pollution, the poor discharge of waste, and the intensive use of raw materials, information, and energy. The method used in this study is an analysis of a literature review of manuscripts discussing topics related to Industry 4.0 and environmental sustainability published between 2000 and 2020. There is currently a gap existing between the actual and the desired situation, in that production occurs in a weak sustainability model, and, therefore, this research debates the effects on environmental sustainability and the challenges facing Industry 4.0. Four scenarios are discussed: a deployment scenario, an operation scenario, integration and compliance with sustainable development goals, and a long-run scenario. The results indicate that there is a negative relationship related to the flow of the production process from the inputs to the final product, including raw materials, energy requirements, information, and waste disposal, and their impacts on the environment. However, the integration of Industry 4.0 and the sustainable development goals enhance environmental sustainability to create ecological support that guarantees high environmental performance with a more positive impact than before. This paper will help stakeholders and companies to provide solutions to the existing environmental challenges that can be mediated through adopting new technologies. The novelty of this study is its depiction of Industry 4.0 and its technologies integrated with sustainable development goals to create a sustainable Industry 4.0 combining environmental protection and sustainability. Full article

(This article belongs to the Special Issue Manufacturing and Management Paradigms, Methods and Tools for Sustainable Industry 4.0 oriented Manufacturing Systems)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Manufacturing and Management Paradigms, Methods and Tools for Sustainable Industry 4.0 oriented Manufacturing Systems

Share This Special Issue

Special Issue Editors

Special Issue Information

Keywords

Benefits of Publishing in a Special Issue

Published Papers (8 papers)

Editorial

Research

Review

Further Information

Guidelines

MDPI Initiatives

Follow MDPI