Special Issue "Industry 4.0 and Sustainable Supply Chain Management"

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Sustainable Processes".

Deadline for manuscript submissions: closed (31 December 2019) | Viewed by 9769

Special Issue Editors

Prof. Dr. Eleonora Bottani
E-Mail Website
Guest Editor
Prof. Dr. Barbara Bigliardi
E-Mail Website
Guest Editor
Department of Engineering and Architecture, University of Parma, 43124 Parma, Italy
Interests: innovation; open innovation; business model innovation; sustainability; circular economy
Special Issues, Collections and Topics in MDPI journals
Dr. Giorgia Casella
E-Mail Website
Guest Editor
Department of Engineering and Architecture, University of Parma, Parco Area delle Scienze 181/A, 43124 Parma, Italy
Interests: logistic and supply chain management; sustainable innovations for supply chain; sustainable supply chain; analysis and optimization of supply chains; supply chain performances
Dr. Letizia Tebaldi
E-Mail Website
Guest Editor
Department of Engineering and Architecture, University of Parma, Parco Area delle Scienze 181/A, 43124 Parma, Italy
Interests: Industry 4.0 for worker safety; security of industrial plants; augmented reality solutions for safety; supply chain management; sustainable supply chain; sustainable innovations for supply chain; supply chain performances; analysis and optimization of supply chains.

Special Issue Information

Dear Colleagues,

The introduction of Industry 4.0 has proven to be successful in providing various business benefits, including operational optimization and value chain optimization. The term Industry 4.0 was coined to mark the fourth industrial revolution, a new paradigm enabled by the introduction of the Internet of things (IoT). Industry 4.0’s vision consists in networks of machines collaborating in a smart factory setting, able of autonomously exchanging information while controlling each other (Tjahjono et al., 2017).

The link between the concepts of Industry 4.0 and sustainable supply chain management is the focus of this Special Issue. Total system integration and automation are key developments in Industry 4.0 (Kagermann, 2015; Zhou et al., 2015). Sustainability, on the other hand, is grounded on the well-known triple bottom line approach, which aims at enhancing the economic, environmental, and social performance of a supply chain, and is increasingly gaining importance among companies. At the same time, however, digitalization of business is no more a choice in today’s dynamic business environment. From these considerations, some questions arise and need to be answered. What is the relationship between Industry 4.0 solutions and supply chain sustainability? Can Industry 4.0 technologies impact on the sustainability of a supply chain? Can Industry 4.0 technologies be leveraged to enhance the sustainability of a supply chain? What is the (positive or negative) impact of implementing Industry 4.0 technologies on the economic, environmental, and social performance of a supply chain? Which technologies can have a (positive or negative) impact on the sustainability of a supply chain?

Our aim with this Special Issue is to encourage research that helps answer some of these questions by means of review studies or research papers providing evidence of the relationship between Industry 4.0 technologies and supply chain sustainability.

Prof. Dr. Eleonora Bottani
Prof. Dr. Barbara Bigliardi
Dr. Giorgia Casella
Dr. Letizia Tebaldi
Guest Editors

References:

Tjahjono, B., Esplugues, C., Enrique, A., Peláez, G.C. (2017). What does Industry 4.0 mean to Supply Chain? Procedia Manufacturing, 13, 1175-1182

Kagermann, H. (2015). Change through digitization: value creation in the age of Industry 4.0. In: Albach, H., Meffert, H., Pinkwart, A. and Reichwald, R. (Eds), Management of Permanent Change, Springer Gabler, Wiesbaden, pp. 23-45, doi: 10.1007/978-3-658-05014-6_2.

Zhou, K., Liu, T., Zhou, L. (2015). Industry 4.0: towards future industrial opportunities and challenges. Proceedings of the 12th International Conference on Fuzzy Systems and Knowledge Discovery, IEEE, Zhangjiajie, pp. 2147-2152, doi: 10.1109/FSKD.2015.7382284

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • sustainable supply chain
  • Industry 4.0
  • internet of things
  • big data
  • simulation
  • cyber-physical systems
  • additive manufacturing
  • augmented reality

Published Papers (6 papers)

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Research

Article
The Profile of the Foreign Investor in the Romanian Chemical Industry
Processes 2020, 8(3), 348; https://doi.org/10.3390/pr8030348 - 18 Mar 2020
Cited by 2 | Viewed by 1008
Abstract
The main aim of this study is to build the investor’s profile in the Romanian chemical industry and to highlight the factors that influenced the decision of investing in Romania rather than other Central Eastern European countries. The data collection was performed in [...] Read more.
The main aim of this study is to build the investor’s profile in the Romanian chemical industry and to highlight the factors that influenced the decision of investing in Romania rather than other Central Eastern European countries. The data collection was performed in June 2019 and the list of the 150 foreign companies from the chemical industry was obtained from The National Trade Register Office. Data used in this research were collected using a questionnaire. Dependent variable represents the probability of investing in Romania, with the option of the other Central and Eastern European countries as reference group. The main part of our analysis focus on this question: “Which were the reasons that made you decide invest in Romania?” For analysis, a number of six main classes are used: Infrastructure, labor force, Agglomeration factors, Knowledge, Market Size and Cost factors (as independent variables). Main results consist in the presence of three factors with a positive impact. The paper also highlights that the main advantage considered by a foreign investor in Romania is represented by the cheap labor force. As a secondary conclusion, companies are also interested in other factors that are mentioned in the paper. Full article
(This article belongs to the Special Issue Industry 4.0 and Sustainable Supply Chain Management)
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Article
A Numerical Study on the Effects of Trust in Supplier Development
Processes 2020, 8(3), 300; https://doi.org/10.3390/pr8030300 - 05 Mar 2020
Cited by 1 | Viewed by 1396
Abstract
Supplier development constitutes one of the current tools to enhance supply chain performance. While most literature in this context focuses on the relationship between manufacturers and suppliers, supplier development also provides an opportunity for distinct manufacturers to collaborate in enhancing a joint supplier. [...] Read more.
Supplier development constitutes one of the current tools to enhance supply chain performance. While most literature in this context focuses on the relationship between manufacturers and suppliers, supplier development also provides an opportunity for distinct manufacturers to collaborate in enhancing a joint supplier. This article proposes a model for the optimization of such joint supplier development programs, which incorporates the effects of trust in the manufacturer-to-manufacturer relationship. This article uses a model-predictive formulation to obtain optimal supplier development investment decisions to consider the strong dynamics of the markets. Thereby, the model is designed to be highly customizable to the needs and requirements of different companies. We analyzed the price development related to Mercedes’ A-Class cars and the cost development in the automotive sector over the last ten years in Germany. According to the obtained result, the proposed model shows a sensible behavior in including trust and its effects in supplier development, even when just applying a set of generalized rules. Moreover, the numeric experiments showed that aiming for a balanced mix of optimizing revenue and trust results in the highest revenue obtained by each partner. Full article
(This article belongs to the Special Issue Industry 4.0 and Sustainable Supply Chain Management)
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Article
A Hybrid Data-Based and Model-Based Approach to Process Monitoring and Control in Sheet Metal Forming
Processes 2020, 8(1), 89; https://doi.org/10.3390/pr8010089 - 09 Jan 2020
Cited by 6 | Viewed by 2234
Abstract
The ability to predict and control the outcome of the sheet metal forming process demands holistic knowledge of the product/process parameter influences and their contribution in shaping the output product quality. Recent improvements in the ability to harvest in-line production data and the [...] Read more.
The ability to predict and control the outcome of the sheet metal forming process demands holistic knowledge of the product/process parameter influences and their contribution in shaping the output product quality. Recent improvements in the ability to harvest in-line production data and the increased capability to understand complex process behaviour through computer simulations open up the possibility for new approaches to monitor and control production process performance and output product quality. This research presents an overview of the common process monitoring and control approaches while highlighting their limitations in handling the dynamics of the sheet metal forming process. The current paper envisions the need for a collaborative monitoring and control system for enhancing production process performance. Such a system must incorporate comprehensive knowledge regarding process behaviour and parameter influences in addition to the current-system-state derived using in-line production data to function effectively. Accordingly, a framework for monitoring and control within automotive sheet metal forming is proposed. The framework addresses the current limitations through the use of real-time production data and reduced process models. Lastly, the significance of the presented framework in transitioning to the digital manufacturing paradigm is reflected upon. Full article
(This article belongs to the Special Issue Industry 4.0 and Sustainable Supply Chain Management)
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Article
Dynamic Semi-Quantitative Risk Research in Chemical Plants
Processes 2019, 7(11), 849; https://doi.org/10.3390/pr7110849 - 12 Nov 2019
Cited by 2 | Viewed by 1085
Abstract
When a major accident occurs in a chemical industry park, it directly affects the personal safety of operators and neighboring residents and causes major losses; therefore, we should take measures to strengthen the management of chemical industry parks. This article proposes and analyzes [...] Read more.
When a major accident occurs in a chemical industry park, it directly affects the personal safety of operators and neighboring residents and causes major losses; therefore, we should take measures to strengthen the management of chemical industry parks. This article proposes and analyzes a new dynamic semi-quantitative risk calculation model for chemical plants that can be applied digitally. This model provides a sustainable, standardized, and comprehensive management strategy for the safety management of chemical plants and chemical industry park managers. The model and its determined parameters were applied to the safety management of chemical companies within the chemical industry park of Quzhou, Zhejiang Province. From the point of view of the existing semi-quantitative model, the existing problems of the current model are analyzed, the current model is optimized, and a new dynamic semi-quantitative calculation model scheme is proposed. The new model uses an analytical hierarchy process targeting the factors affecting the risks in chemical plants, and chemical plant semi-quantitative dynamic calculation system consisting of the operator, process/equipment, risk, building environment, safety management, and domino effect, and the comprehensive risk of the chemical plant was calculated. The model is ultimately a real-time quantitative value, but its calculation process can compare and analyze the causes of high risk in a chemical plant as they relate to these six factors. Its implementation requires only software, which will greatly help chemical plant safety management. Full article
(This article belongs to the Special Issue Industry 4.0 and Sustainable Supply Chain Management)
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Article
Analysis of the Risk Impact of Implementing Digital Innovations for Logistics Management
Processes 2019, 7(11), 815; https://doi.org/10.3390/pr7110815 - 05 Nov 2019
Cited by 10 | Viewed by 2218
Abstract
The emergence of digital technology is a paradigmatic historical change. As a process of transforming social engineering structures, digitization has had a ubiquitous impact on the organization of structures and business logic, as well as on economic principles and rules. The fertile ground [...] Read more.
The emergence of digital technology is a paradigmatic historical change. As a process of transforming social engineering structures, digitization has had a ubiquitous impact on the organization of structures and business logic, as well as on economic principles and rules. The fertile ground for digital technology applications is logistics management, which manifests itself in the dynamic development of logistics 4.0. Increasingly, it is pointed out that digital technology has some distinct features that have fundamental implications for innovation. The aim of the present study is to determine the impact of the risk of implementing digital technologies for logistics management. The study was conducted using the standardized questionnaire interview method with representatives of the management of enterprises. The attempt was random. The sampling was made up of micro, small, medium, and large enterprises from the production and services sectors, having a logistics unit or a logistics division, located in the “Bisnode Poland” database. In total, 360 full interviews were carried out. For the study, we defined macro-environment, operational, functional, and microenvironment risks. The basic conclusion is that between each type of risk and the type of digital technologies used in the studied entities and their partners in the supply chain, there is a high and very high dependence in the case of three-dimensional printing (3D printing), artificial intelligence, blockchain, drones, augmented reality, and self-propelled vehicles. Full article
(This article belongs to the Special Issue Industry 4.0 and Sustainable Supply Chain Management)
Article
Optimal Design of Bioenergy Supply Chains Considering Social Benefits: A Case Study in Northeast China
Processes 2019, 7(7), 437; https://doi.org/10.3390/pr7070437 - 10 Jul 2019
Cited by 3 | Viewed by 1131
Abstract
Bioenergy supply chains can offer social benefits. In most related research, the total number of created jobs is used as the indicator of social benefits. Only a few of them quantify social benefits considering the different impact of economic activities in different locations. [...] Read more.
Bioenergy supply chains can offer social benefits. In most related research, the total number of created jobs is used as the indicator of social benefits. Only a few of them quantify social benefits considering the different impact of economic activities in different locations. In this paper, a new method of measuring the social benefits of bioethanol supply chains is proposed that considers job creation, biomass purchase, and the different impacts of economic activities in different locations. A multi-objective mixed integer linear programming (MILP) model is developed to address the optimal design of a bioethanol supply chain that maximizes both economic and social benefits. The ε-constraint method is employed to solve the model and a set of Pareto-optimal solutions is obtained that shows the relationship between the two objectives. The developed model is applied to case studies in Liaoning Province in Northeast China. Actual data are collected as practical as possible for the feasibility and effectiveness of the results. The results show that the bioethanol supply chain can bring about both economic and social benefits in the given area and offers governments a better and more efficient way to create social benefits. The effect of the government subsidy on enterprises’ decisions about economic and social benefits is discussed. Full article
(This article belongs to the Special Issue Industry 4.0 and Sustainable Supply Chain Management)
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