Special Issue "Manufacturing Energy Efficiency and Industry 4.0"

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "Sustainable Energy".

Deadline for manuscript submissions: 31 October 2021.

Special Issue Editors

Prof. Dr. Konstantinos Salonitis
E-Mail Website
Guest Editor
Sustainable Manufacturing Systems Centre, Manufacturing Department, School Of Aerospace, Transport and Manufacturing Building 50, Cranfield University, Cranfield, Bedfordshire MK43 0AL, UK
Interests: sustainable manufacturing systems; green manufacturing; environmental impact assessment; simulation; modelling
Special Issues and Collections in MDPI journals
Dr. Christos Emmanouilidis
E-Mail Website
Guest Editor
Through-life Engineering Services Institute, Manufacturing Department, School Of Aerospace, Transport and Manufacturing Building 50, Cranfield University, Cranfield, Bedfordshire MK43 0AL, UK
Interests: industrial sustainability; simulation and modeling; sensor technologies; systems engineering, throughlife engineering services; instrumentation and sensors; Industry 4.0
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Energy efficiency in manufacturing systems and processes will carry on being a key research topic. Research in the energy efficiency of manufacturing in the last decade has resulted in very promising improvements. While design-time energy efficiency considerations have received considerable attention, operating time efficiency is now increasingly benefitting from the adoption and implementation of Industry-4.0-enabling technologies. The Industrial Internet of Things (IIoT), the upgrade of manufacturing facilities into industrial cyber physical systems (ICPS), and the efficient exploitation of manufacturing and process monitoring data through advanced Machine Learning present concrete opportunities towards more responsive, smarter, and more energy-efficient manufacturing.

This Special Issue considers the energy efficiency of both manufacturing processes and systems and how these can be improved by the use of Industry-4.0-enabling technologies. Papers are particularly invited in the following areas:

  • Industry-4.0-enabled methods for the real time measurement of energy efficiency;
  • Machine learning from production line monitoring data for energy efficiency;
  • Tools and techniques in the context of Industry 4.0 for the analysis and development of improvements with regards to energy consumption;
  • Tools and techniques for the modeling and simulation of energy efficiency;
  • Case studies on the management of Industry 4.0 systems for energy efficiency;
  • Industry 4.0 and decarbonization of manufacturing;
  • Enabling technologies for green, lean, and smart manufacturing;
  • Joint asset and production management aided by Industry 4.0 technologies.

Prof. Dr. Konstantinos Salonitis
Dr. Christos Emmanouilidis
Guest Editors

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 papers will be 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. Energies is an international peer-reviewed open access semimonthly 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

  • Green manufacturing
  • Industrial Internet of Things (IIoT)
  • Industry 4.0
  • Industrial cyberphysical systems (ICPS)
  • Big data management in manufacturing
  • Industrial sustainability
  • Artificial Intelligence and machine learning for energy-efficient manufacturing

Published Papers (4 papers)

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Article
Event-Driven Interoperable Manufacturing Ecosystem for Energy Consumption Monitoring
Energies 2021, 14(12), 3620; https://doi.org/10.3390/en14123620 - 17 Jun 2021
Viewed by 415
Abstract
Industrial environments are heterogeneous systems that create challenges of interoperability limiting the development of systems capable of working collaboratively from the point of view of machines and software. Additionally, environmental issues related to manufacturing systems have emerged during the last decades, related to [...] Read more.
Industrial environments are heterogeneous systems that create challenges of interoperability limiting the development of systems capable of working collaboratively from the point of view of machines and software. Additionally, environmental issues related to manufacturing systems have emerged during the last decades, related to sustainability problems faced in the world. Thus, the proposed work aims to present an interoperable solution based on events to reduce the complexity of integration, while creating energetic profiles for the machines to allow the optimization of their energy consumption. A publish/subscribe-based architecture is proposed, where the instantiation is based on Apache Kafka. The proposed solution was implemented in two robotic cells in the automotive industry, constituted by different hardware, which allowed testing the integration of different components. The energy consumption data was then sent to a Postgres database where a graphical interface allowed the operator to monitor the performance of each cell regarding energy consumption. The results are promising due to the system’s ability to integrate tools from different vendors and different technologies. Furthermore, it allows the possibility to use these developments to deliver more sustainable systems using more advanced solutions, such as production scheduling, to reduce energy consumption. Full article
(This article belongs to the Special Issue Manufacturing Energy Efficiency and Industry 4.0)
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Article
Business and Energy Efficiency in the Age of Industry 4.0: The Hulten, Broweus and Van Dijk Sensory Marketing Model Applied to Spanish Textile Stores during the COVID-19 Crisis
Energies 2021, 14(7), 1966; https://doi.org/10.3390/en14071966 - 02 Apr 2021
Viewed by 545
Abstract
Strategic and tactical factors come into play in shop competitiveness where, in addition to the products sold, other marketing mix variables must also be considered. There are also subjective factors, such as perceptions through the senses. This became even more important when, as [...] Read more.
Strategic and tactical factors come into play in shop competitiveness where, in addition to the products sold, other marketing mix variables must also be considered. There are also subjective factors, such as perceptions through the senses. This became even more important when, as a result of the COVID-19 crisis and the forced closure of certain establishments with physical sales, it was necessary to increase profitability and efficiency. The aim of this study was to determine the exact role of sensory marketing in shop efficiency and profitability, based on the guiding principles of technology, innovation, and respect for the environment. We conducted an exploratory and experimental study consisting of the creation of a sensory strategy through the adaptation of the Hulten, Broweus and Van Dijk model on a specific establishment in the current era of Industry 4.0. The results indicate an increase in sales as well as customer satisfaction and happiness after implementing the relevant strategies. The conclusions show that this model is valid and reliable for physical retail establishments, and that these business strategies can significantly contribute to the optimisation of energy resources. Full article
(This article belongs to the Special Issue Manufacturing Energy Efficiency and Industry 4.0)
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Article
Exploring the Determinants of Industry 4.0 Development Using an Extended SWOT Analysis: A Regional Study
Energies 2020, 13(22), 5972; https://doi.org/10.3390/en13225972 - 16 Nov 2020
Cited by 3 | Viewed by 798
Abstract
Researchers and practitioners argue that in the global context of the Fourth Industrial Revolution, also labelled Industry 4.0, the regional dimension of industrial development remains equally essential. A region that effectively implements the concept of Industry 4.0 can accelerate by enhancing the manufacturing [...] Read more.
Researchers and practitioners argue that in the global context of the Fourth Industrial Revolution, also labelled Industry 4.0, the regional dimension of industrial development remains equally essential. A region that effectively implements the concept of Industry 4.0 can accelerate by enhancing the manufacturing energy efficiency, thus contributing to the goals of the “Green Deal” policy. Therefore, to support the policy-making process, it is necessary to develop analytical tools exploring the determinants of the Industry 4.0 development. This paper presents a methodology of strategic analysis of a region in terms of the Industry 4.0 development potential. The core of the methodology is an extended Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis. The study identifies regional strengths and weaknesses, external incentives and disincentives, internal opportunities and threats, and external opportunities and threats with regard to the development of Industry 4.0, related technologies and the potential of increasing manufacturing energy efficiency. The research procedure is exemplified by the case of Podlaskie Voivodeship in Poland. The results of this study demonstrate the robustness of the proposed approach. The elaborated methodology can be used by decision-makers in designing strategies for the development of fourth-generation industry at a regional level. Full article
(This article belongs to the Special Issue Manufacturing Energy Efficiency and Industry 4.0)
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Systematic Review
Towards the Development of Digital Manufacturing Ecosystems for Sustainable Performance: Learning from the Past Two Decades of Research
Energies 2021, 14(10), 2945; https://doi.org/10.3390/en14102945 - 19 May 2021
Viewed by 638
Abstract
Although the Internet of Things (IoT), advanced manufacturing technologies, and cloud manufacturing contribute to developing a digital manufacturing ecosystem that enhances energy efficiency and resource utilization, manufacturing processes are vulnerable to timely production and delivery. The digital manufacturing systems in Industrial Revolution 4.0 [...] Read more.
Although the Internet of Things (IoT), advanced manufacturing technologies, and cloud manufacturing contribute to developing a digital manufacturing ecosystem that enhances energy efficiency and resource utilization, manufacturing processes are vulnerable to timely production and delivery. The digital manufacturing systems in Industrial Revolution 4.0 (IR 4.0) minimized the human-technology interactions to foster productivity and material flow. However, there is scarce research to gauge the efficiency of these digital technologies in the entire manufacturing process; also, little is known about the collaborative efforts among countries to achieve sustainable manufacturing performance through the digitalization of the production process. Thus, this systematic review aimed to highlight the effectiveness of the digital manufacturing systems for sustainable product development and the collaborative research on the subject. We selected 52 research articles for this review by following the 2015 Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA) statement. The literature classifications were developed using text frequency algorithms in VOSviewer (Centre for Science and Technology Studies, Leiden University, The Netherlands) Results exposed literature from 2005 to 2020 can be categorized into four major research streams: digital transformation, digital manufacturing ecosystem, performance management, and sustainability. The study’s findings revealed that the manufacturing processes are moving towards the IoT, digital devices, and smart factories that are entirely dependent on digital technologies. The digital manufacturing ecosystem is dependent on the availability of digital technologies to all stakeholders. The study concluded that digital technologies are improving manufacturing efficiency and process effectiveness. However, this requires infrastructure that primarily available in developed countries; thus, the digital transformation in underdeveloped regions is deliberate and requires more collaborative research. Full article
(This article belongs to the Special Issue Manufacturing Energy Efficiency and Industry 4.0)
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: A Process Planning Framework for Sustainablemanufacturing
Authors: Colin Reiff; Matthias Buser; Thomas Betten
Affiliation: 1 Institute for Control Engineering of Machine Tools and Manufacturing Units (ISW), University of Stuttgart, Stuttgart, Baden-Württemberg, Germany 2 Institut für Strahlwerkzeuge (IFSW), University of Stuttgart, Stuttgart, Baden-Württemberg, Germany 3 Institute of Acoustics and Building Physics (IABP), University of Stuttgart, Stuttgart, Baden-Württemberg, Germany
Abstract: The increasing importance of environmental protection affects not only our daily lives, but also the manufacturing industry in particular. Resource-saving production is of enormous importance in order to remain competitive, and also to comply with the increasingly stringent legislation, and customer demands. At present, environmental factors play a subordinate role for the choice of manufacturing processes during process planning for highly-customized products. As a consequence, opportunities are not taken into account to reduce environmental impacts, which could also save costs and thus improve the economic efficiency of the production processes. In order to support manufacturing experts during process planning, this paper presents an approach of a highly-automated selection process of manufacturing resources with regard to environmental aspects for individual parts. This is achieved by abstracting and generalizing manufacturing resources and part descriptions to dynamically calculate the resulting price, required time, and environmental impacts for the manufacturing of a specific part. The approach is implemented using a web framework. The main advantage is the possibility to model and compare different manufacturing processes within a single framework, which is demonstrated by exemplary use cases.

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