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Energies
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Energy Challenges and Smart Applications in Production Systems
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Energy Challenges and Smart Applications in Production Systems

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F5: Artificial Intelligence and Smart Energy".

Deadline for manuscript submissions: closed (10 August 2023) | Viewed by 13052

Special Issue Editors

Dr. Krzysztof Ejsmont

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Guest Editor
Faculty of Mechanical and Industrial Engineering, Warsaw University of Technology, 02-524 Warsaw, Poland
Interests: Industry 4.0; sustainability; operations management; artificial neural networks; power system
Special Issues, Collections and Topics in MDPI journals
Dr. Bartłomiej Gładysz

E-Mail Website
Guest Editor
Faculty of Production Engineering, Warsaw University of Technology, 02-524 Warsaw, Poland
Interests: energy sustainability; smart manufacturing; technology management
Special Issues, Collections and Topics in MDPI journals
Dr. Rodolfo Haber

E-Mail Website
Guest Editor
Center for Automation and Robotics, Politechnic University of Madrid (UPM) and Spanish Council for Scientific Research (CSIC), Ctra. Campo Real km 0,200 La Poveda, 28500 Madrid, Spain
Interests: cyber physical systems; internet of things; intelligent sensing and control; modeling supervision; intelligent systems; complex processes; Industry 4.0; Industry 5.0; power converter
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We live in times of extremely rapid technological progress, as evidenced by, among others, the emergence of the fourth industrial revolution (Industry 4.0). Energy consumption and deliveries are currently some of the greatest challenges of civilization. Society is becoming more and more aware of the scarcity of natural resources, the impact of climate change, and the importance of smart solutions that allow for rational use of energy. To this end, it is crucial to pay attention to the production processes that are gigantic energy consumers. Energy efficiency in production is a great challenge that cannot be successfully achieved without ground-breaking changes in production paradigms and underlying technologies and applications. The role of smart solutions in this area is going to be huge.

Despite significant technological advances in energy efficiency in many industrial sectors, there is still a need for new, smart solutions. They can be used in power supply and energy conversion systems, control of energy consumption in production plants, or more energy-efficient and environment-friendly production technologies. The development of Industry 4.0 and artificial intelligence (AI) provides many promising technologies, systems, and applications in the field of energy saving. Intelligent solutions can offer manufacturing companies many attractive benefits, such as reducing emissions, saving costs by reducing energy consumption, offering better customer service, and responding to market demand. The multidisciplinary nature of the problem motivates the need for innovative and robust solutions from various fields of knowledge. Industry 4.0 and AI play a key role in the success of smart applications in the area of energy efficiency.

The purpose of this Special Issue is to promote and disseminate new trends and the latest advancements in Industry 4.0 and AI supporting energy efficiency in production and manufacturing systems, and sustainable energy. We invite all interested parties to publish the results of their research. Theoretical approaches, frameworks, simulations, technological applications, as well as pilot and case studies are welcome.

Dr. Krzysztof Ejsmont
Dr. Bartłomiej Gładysz
Dr. Rodolfo Haber
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 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. 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 2600 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

  • industry 4.0
  • smart manufacturing/production
  • artificial intelligence
  • production processes
  • energy efficiency
  • energy savings
  • smart energy applications
  • smart energy monitoring
  • smart energy measuring
  • smart energy management
  • sustainability

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Related Special Issue

Published Papers (6 papers)

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Editorial

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6 pages, 186 KiB  
Editorial
Energy Challenges and Smart Applications in Production Systems
by Krzysztof Ejsmont, Bartlomiej Gladysz and Rodolfo Haber
Energies 2024, 17(22), 5624; https://doi.org/10.3390/en17225624 - 10 Nov 2024
Viewed by 610
Abstract
A key challenge of the modern world is addressing energy issues, especially in the context of growing public awareness of limited resources and the catastrophic effects of climate change, which are mainly caused by human activity and cumbersome industry [...] Full article
(This article belongs to the Special Issue Energy Challenges and Smart Applications in Production Systems)

Research

Jump to: Editorial

27 pages, 3270 KiB  
Article
Multi-Method Simulation and Multi-Objective Optimization for Energy-Flexibility-Potential Assessment of Food-Production Process Cooling
by Daniel Anthony Howard, Bo Nørregaard Jørgensen and Zheng Ma
Energies 2023, 16(3), 1514; https://doi.org/10.3390/en16031514 - 3 Feb 2023
Cited by 4 | Viewed by 2175
Abstract
Process cooling for food production is an energy-intensive industry with complex interactions and restrictions that complicate the ability to utilize energy-flexibility due to unforeseen consequences in production. Therefore, methods for assessing the potential flexibility in individual facilities to enable the active participation of [...] Read more.
Process cooling for food production is an energy-intensive industry with complex interactions and restrictions that complicate the ability to utilize energy-flexibility due to unforeseen consequences in production. Therefore, methods for assessing the potential flexibility in individual facilities to enable the active participation of process-cooling facilities in the electricity system are essential, but not yet well discussed in the literature. Therefore, this paper introduces an assessment method based on multi-method simulation and multi-objective optimization for investigating energy flexibility in process cooling, with a case study of a Danish process-cooling facility for canned-meat food production. Multi-method simulation is used in this paper: multi-agent-based simulation to investigate individual entities within the process-cooling system and the system’s behavior; discrete-event simulation to explore the entire process-cooling flow; and system dynamics to capture the thermophysical properties of the refrigeration unit and states of the refrigerated environment. A simulation library is developed, and is able to represent a generic production-flow of the canned-food process cooling. A data-driven symbolic-regression approach determines the complex logic of individual agents. Using a binary tuple-matrix for refrigeration-schedule optimization, the refrigeration-cycle operation is determined, based on weather forecasts, electricity price, and electricity CO2 emissions without violating individual room-temperature limits. The simulation results of one-week’s production in October 2020 show that 32% of energy costs can be saved and 822 kg of CO2 emissions can be reduced. The results thereby show the energy-flexibility potential in the process-cooling facilities, with the benefit of overall production cost and CO2 emissions reduction; at the same time, the production quality and throughput are not influenced. Full article
(This article belongs to the Special Issue Energy Challenges and Smart Applications in Production Systems)
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19 pages, 8627 KiB  
Article
Analysis and Evaluation of the Possibility of Electricity Production from Small Photovoltaic Installations in Poland
by Waldemar Izdebski and Katarzyna Kosiorek
Energies 2023, 16(2), 944; https://doi.org/10.3390/en16020944 - 14 Jan 2023
Cited by 5 | Viewed by 1707
Abstract
The production of electricity from photovoltaic (PV) systems is one of the significant opportunities for novel renewable energy sources. The PV systems can provide energy with minimum environmental harm; however, the usage of this energy source becomes strongly dependent on a wide range [...] Read more.
The production of electricity from photovoltaic (PV) systems is one of the significant opportunities for novel renewable energy sources. The PV systems can provide energy with minimum environmental harm; however, the usage of this energy source becomes strongly dependent on a wide range of social, economic, and technical factors. Based on the growing demand for renewable energy sources, the aim of the work focuses on the socio-economic analysis of possibilities of producing electricity from photovoltaic installations up to 10 kW in Poland. Based on expert research, the factors influencing energy production from PV systems were assessed based on factor three analysis (level II with 5 factors, level III with 15 factors). Using the expert-mathematical method, a hierarchy of economic, technical, and social factors of PV-based energy production was evaluated. The analysis of socio-economic factors indicated that the greatest impact on the PV systems development in Poland depends on energy purchasing costs and EU law regulations on renewable energy sources (RESs). The most influential factors were then used to forecast the possible cost-effectiveness of renewable energy production of home energy production. The study demonstrates the importance of renewable energy sources utilization and the cost-effectiveness of solar energy production in small PV systems in Poland. Full article
(This article belongs to the Special Issue Energy Challenges and Smart Applications in Production Systems)
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21 pages, 2333 KiB  
Article
Evaluation of Economic Possibilities of Production of Second-Generation Spirit Fuels for Internal Combustion Engines in Poland
by Waldemar Izdebski, Michał Izdebski and Katarzyna Kosiorek
Energies 2023, 16(2), 892; https://doi.org/10.3390/en16020892 - 12 Jan 2023
Viewed by 1555
Abstract
With the rapid growth in industrial development, there is a particular need for new environmentally balanced energy source utilization. Ethanol produced from biomass, especially lignocellulosic waste products, represents an attractive, sustainable energy source for fuel production. Until now, in Poland, bioethanol has been [...] Read more.
With the rapid growth in industrial development, there is a particular need for new environmentally balanced energy source utilization. Ethanol produced from biomass, especially lignocellulosic waste products, represents an attractive, sustainable energy source for fuel production. Until now, in Poland, bioethanol has been produced from edible plants containing sugars susceptible to fermentation. Due to the growing technical and economical needs for alternative biomass source utilization, in the present work, an attempt has been made to identify the most cost-effective strategy to analyze ethyl alcohol production from different lignocellulose sources. The concept of an installation for the first and second stages of bioethanol production was proposed. All of the most relevant elements of the bioethanol production cost analysis were identified and characterized. Cost analyses of all important production process elements showed their relative effects on the production cost and potential for the competitive advantage of applied raw material. The study demonstrates the importance of renewable energy source utilization and the cost-effectiveness of bioethanol production. Furthermore, the proposed less energy- and labor-demanding process, primarily achieved via the implementation of technological medium recovery and recirculation, reduces the production cost and results in higher production efficiency, and therefore has a significant effect on the overall process economy. Full article
(This article belongs to the Special Issue Energy Challenges and Smart Applications in Production Systems)
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18 pages, 4288 KiB  
Article
Energy-Based Prognostics for Gradual Loss of Conveyor Belt Tension in Discrete Manufacturing Systems
by Mahboob Elahi, Samuel Olaiya Afolaranmi, Wael M. Mohammed and Jose Luis Martinez Lastra
Energies 2022, 15(13), 4705; https://doi.org/10.3390/en15134705 - 27 Jun 2022
Cited by 8 | Viewed by 1716
Abstract
This paper presents a data-driven approach for the prognosis of the gradual behavioural deterioration of conveyor belts used for the transportation of pallets between processing workstations of discrete manufacturing systems. The approach relies on the knowledge of the power consumption of a conveyor [...] Read more.
This paper presents a data-driven approach for the prognosis of the gradual behavioural deterioration of conveyor belts used for the transportation of pallets between processing workstations of discrete manufacturing systems. The approach relies on the knowledge of the power consumption of a conveyor belt motor driver. Data are collected for two separate cases: the static case and dynamic case. In the static case, power consumption data are collected under different loads and belt tension. These data are used by a prognostic model (artificial neural network (ANN)) to learn the conveyor belt motor driver’s power consumption pattern under different belt tensions and load conditions. The data collected during the dynamic case are used to investigate how the belt tension affects the movement of pallets between conveyor zones. During the run time, the trained prognostic model takes real-time power consumption measurements and load information from a testbench (a discrete multirobot mobile assembling line) and predicts a belt tension class. A consecutive mismatch between the predicted belt tension class and optimal belt tension class is an indication of failure, i.e., a gradual loss of belt tension. Hence, maintenance steps must be taken to avoid further catastrophic situations such as belt slippages on head pulleys, material slippages and belt wear and tear. Full article
(This article belongs to the Special Issue Energy Challenges and Smart Applications in Production Systems)
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18 pages, 2574 KiB  
Article
Pre-Cooling Concrete System in Massive Concrete Production: Energy Analysis and Refrigerant Replacement
by Malik I. Alamayreh, Ali Alahmer, Mai Bani Younes and Subhi M. Bazlamit
Energies 2022, 15(3), 1129; https://doi.org/10.3390/en15031129 - 3 Feb 2022
Cited by 13 | Viewed by 3687
Abstract
Several techniques for cooling mass concrete structures were developed in order to increase structural integrity and reduce the influence of cement hydration, which sometimes causes cracking in concrete structures, negatively affecting their durability. This research focuses on cooling system design, initial investment, and [...] Read more.
Several techniques for cooling mass concrete structures were developed in order to increase structural integrity and reduce the influence of cement hydration, which sometimes causes cracking in concrete structures, negatively affecting their durability. This research focuses on cooling system design, initial investment, and the influence of different refrigerants on cooling system performance aims in producing higher quality massive concrete. Cooling aggregates in massive concrete structures such as desert dams can be performed by employing cooled air from an air conditioning duct system or chilled water. The experimental study illustrates the relationship between the coefficient of performance COP, the evaporator temperature, cooling capacity, and refrigerant mass flow rate as a function of the evaporator temperature, cooling capacity, and refrigerant mass flow rate. The findings of the experiments were utilized to verify a numerical model developed utilizing engineering equation solver (EES) software. The performance of the vapor compression of the cooling systems was compared using alternative refrigerants, including R22, R32, and R410a at different operating conditions. This study revealed that R22 refrigerant has a higher coefficient of performance than R32 and R410A, while R32 has the highest cooling capacity among other refrigerants. Full article
(This article belongs to the Special Issue Energy Challenges and Smart Applications in Production Systems)
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