Advanced Systems Engineering: Theory and Applications, 2nd Volume

Topic Information

Dear Colleagues,

This topic is focused in the most recent developments in Advanced Systems Engineering, and the development of related subsystems and components.

Advanced Systems Engineering consists of solutions (and respective development) that increasingly rely on intelligent components and subsystems to deliver an improved performance for different and complex applications of engineering systems. In this context, the correct understanding of the interaction and connection between subsystems is crucial for making products that are more efficient and reliable and, most of all, successfully designed for specific successful engineering applications. More than ever, these systems belong to a new generation of more integrated and complex products with more dedicated and sophisticated applications in several domains, bringing together critical knowledge about design, materials, energy, sustainability and reliability.

The topics to be considered in this context include, but are not limited to, the following:

• Aerospace Technology and Astronautics
• Agricultural Processes
• Applied Mechanics
• Automotive Engineering
• Biotechnological and Environmental Systems
• Biotechnology
• Biomechanics
• Cyber–Physical Systems
• Control Theory and Architectures
• Control Technology
• Decision Theory and Algorithms
• Dynamical Systems
• Discrete-Event Systems
• Distributed and Networked Control
• Economic Models
• Engine Technology
• Engineering Design
• Engineering Thermodynamics, Heat and Mass Transfer
• Fault-Tolerant Control
• Fluid Mechanics
• Fuzzy and Neuro-Fuzzy Systems
• Genetic Algorithms and Nonlinear Control
• Hardware for Control Systems
• Image Processing and Computer Vision
• Industrial Automation
• Industrial Networking
• Instrumentation, Sensors and Actuators
• Machinery and Machine Elements
• Manufacturing Engineering
• Manufacturing Systems and Scheduling
• Marketing and Entrepreneurship
• Marine Control
• Materials Engineering
• Mechanical Systems Design
• Mechanical Structures and Stress Analysis
• Mechanical Vibrations
• Mechatronics Design
• Mechatronics Modelling, Simulation and Identification
• Medical Devices
• MEMS
• Model-Based Design and Development
• Modeling and Identification
• Nanotechnology and Microengineering
• Neural Networks
• Open Innovation
• Power Systems
• Precision Engineering, Instrumentation, Measurement
• Process Control
• Real-Time Systems Architectures
• Rehabilitation Devices
• Reliable Systems
• Remote and Virtual Laboratories
• Renewable Energy Systems
• Requirements Analysis
• Robust Control
• Robotics
• Synergy between EU research, innovation and development funds
• Social and Industrial entrepreneurship
• Sustainability Successful Practices
• Theoretical and Applied Mechanics
• Transportation Systems
• Tribology and Surface Technology
• Web Remote Control
• Wellbeing
• Wireless Applications and Systems

Dr. Katarzyna Antosz
Dr. Jose Machado
Dr. Erika Ottaviano
Dr. Pierluigi Rea
Dr. Camelia Claudia Avram
Dr. Vijaya Kumar Manupati
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Applied Sciences applsci	2.5	5.3	2011	17.8 Days	CHF 2400	Submit
Electronics electronics	2.6	5.3	2012	16.8 Days	CHF 2400	Submit
Energies energies	3.0	6.2	2008	17.5 Days	CHF 2600	Submit
Metals metals	2.6	4.9	2011	16.5 Days	CHF 2600	Submit
Sensors sensors	3.4	7.3	2001	16.8 Days	CHF 2600	Submit
Systems systems	2.3	2.8	2013	17.3 Days	CHF 2400	Submit
Inventions inventions	2.1	4.8	2016	21.2 Days	CHF 1800	Submit

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Published Papers (17 papers)

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16 pages, 5643 KiB  

Open AccessArticle

Revolutionizing Palm Dates Harvesting with Multirotor Flying Vehicles

by Hanafy M. Omar and Saad M. S. Mukras

Appl. Sci. 2024, 14(22), 10529; https://doi.org/10.3390/app142210529 - 15 Nov 2024

Viewed by 301

Abstract

This study addresses the challenges of traditional date palm harvesting, which is often labor-intensive and hazardous, by introducing an innovative solution utilizing multirotor flying vehicles (MRFVs). Unlike conventional methods such as hydraulic lifts and ground-based robotic manipulators, the proposed system integrates a quadrotor [...] Read more.

This study addresses the challenges of traditional date palm harvesting, which is often labor-intensive and hazardous, by introducing an innovative solution utilizing multirotor flying vehicles (MRFVs). Unlike conventional methods such as hydraulic lifts and ground-based robotic manipulators, the proposed system integrates a quadrotor equipped with a winch and a suspended robotic arm with a precision saw. Controlled remotely via a mobile application, the quadrotor navigates to targeted branches on the date palm tree, where the robotic arm, guided by live video feedback from integrated cameras, accurately severs the branches. Extensive testing in a controlled environment demonstrates the system’s potential to significantly improve harvesting efficiency, safety, and cost-effectiveness. This approach offers a promising alternative to traditional harvesting methods, providing a scalable solution for date palm cultivation, particularly in regions with large-scale plantations. This work marks a significant advancement in the field of agricultural automation, offering a safer, more efficient method for harvesting date palms and contributing to the growing body of knowledge in automated farming technologies. Full article

(This article belongs to the Topic Advanced Systems Engineering: Theory and Applications, 2nd Volume)

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20 pages, 3051 KiB  

Open AccessArticle

Integrating Process Re-Engineering Models in Cement Production to Improve Energy Efficiency

by Moses Charles Siame, Tawanda Zvarivadza, Wiyao Edjeou, Isaac N. Simate and Edward Lusambo

Appl. Sci. 2024, 14(19), 8850; https://doi.org/10.3390/app14198850 - 1 Oct 2024

Viewed by 1148

Abstract

The demand for cement has significantly increased, growing by 8% in the year 2022 and by a further 12% in 2023. It is highly anticipated that this trend will continue, and it will result in significant growth by 2030. However, cement production is [...] Read more.

The demand for cement has significantly increased, growing by 8% in the year 2022 and by a further 12% in 2023. It is highly anticipated that this trend will continue, and it will result in significant growth by 2030. However, cement production is highly energy-intensive, with 70 to 80% of the total energy consumed during the clinker formation, which is the main cement production process. Minimising energy losses requires a radical approach that includes optimising the performance of the kilns and significantly improving their energy efficiency. One of the most efficient approaches to optimise the performance of the kilns and reduce energy losses is by integrating process re-engineering models, which leverage process data analytics, machine learning, and computational methods. This study employed a model-based integration approach to improve energy efficiency during clinker formation. Energy consumption data were collected from two semi-automated cement production plants. The data were analysed using a regression model in Minitab (Minitab 21.1.0) statistical software. The analysis resulted in a linear energy consumption equation that links energy consumption to both production and energy loss. Dynamic simulations and modelling using Simulink in MATLAB were performed based on a proportional–integral–derivative (PID)-controlled system. The dynamic behaviour of the model was evaluated using data from Plant A and validated with data from Plant B. The energy efficiency equation was established as a mathematical model that explains energy improvements based on incorporating parameters for the cement kiln system and disturbances from the environment. Full article

(This article belongs to the Topic Advanced Systems Engineering: Theory and Applications, 2nd Volume)

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33 pages, 5556 KiB  

Open AccessArticle

Multi-Layer Objective Model and Progressive Optimization Mechanism for Multi-Satellite Imaging Mission Planning in Large-Scale Target Scenarios

by Xueying Yang, Min Hu, Gang Huang and Feiyao Huang

Appl. Sci. 2024, 14(19), 8597; https://doi.org/10.3390/app14198597 - 24 Sep 2024

Viewed by 575

Abstract

With the continuous increase in the number of in-orbit satellites and the explosive growth in the demand for observation targets, satellite resource allocation and mission scheduling are faced with the problems of declining benefits and stagnant algorithm performance. This work proposes a progressive [...] Read more.

With the continuous increase in the number of in-orbit satellites and the explosive growth in the demand for observation targets, satellite resource allocation and mission scheduling are faced with the problems of declining benefits and stagnant algorithm performance. This work proposes a progressive optimization mechanism and population size adaptive strategy for an improved differential evolution algorithm (POM-PSASIDEA) in large-scale multi-satellite imaging mission planning to address the above challenges. (1) MSIMPLTS based on Multi-layer Objective Optimization is constructed, and the MSIMPLTS is processed hierarchically by setting up three sub-models (superstructure, mesostructure, and understructure) to achieve a diversity of resource selection and step-by-step refinement of optimization objectives to improve the task benefits. (2) Construct the progressive optimization mechanism, which contains the allocation optimization, time window optimization, and global optimization phases, to reduce task conflicts through the progressive decision-making of the task planning scheme in stages. (3) A population size adaptive strategy for an improved differential evolution algorithm is proposed to dynamically adjust the population size according to the evolution of the population to avoid the algorithm falling into the local optimum. The experimental results show that POM-PSASIDEA has outstanding advantages over other algorithms, such as high task benefits and a high task allocation rate when solved in a shorter time. Full article

(This article belongs to the Topic Advanced Systems Engineering: Theory and Applications, 2nd Volume)

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24 pages, 4033 KiB  

Open AccessArticle

A New Stochastic Petri Net Modeling Approach for the Evolution of Online Public Opinion on Emergencies: Based on Four Real-Life Cases

by Chen Guo and Yinghua Song

Systems 2024, 12(9), 333; https://doi.org/10.3390/systems12090333 - 29 Aug 2024

Viewed by 672

Abstract

In this study, we analyzed the evolution of online public opinion on emergencies using a new Stochastic Petri Net modeling approach. First, an intuitive description of the emergency online public opinion development process was conceptualized from the life cycle evolution law perspective. Then, [...] Read more.

In this study, we analyzed the evolution of online public opinion on emergencies using a new Stochastic Petri Net modeling approach. First, an intuitive description of the emergency online public opinion development process was conceptualized from the life cycle evolution law perspective. Then, based on Petri net theory, a Stochastic Petri Net isomorphic Markov chain model was constructed to simulate the evolution of online public opinion on emergencies. Finally, four real-life cases were selected to validate and analyze the model, demonstrating that the evolutionary leaps, complexity, critical nodes, evolutionary rate, and execution time differ across different online public opinions on emergencies. The study results indicate that this modeling approach has certain advantages in examining the evolution based on multi-factor coupling and quantifying the evolution law in online public opinion on emergencies. Full article

(This article belongs to the Topic Advanced Systems Engineering: Theory and Applications, 2nd Volume)

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19 pages, 3294 KiB  

Open AccessArticle

Air Traffic Controller Workload Detection Based on EEG Signals

by Quan Shao, Hui Li and Zhe Sun

Sensors 2024, 24(16), 5301; https://doi.org/10.3390/s24165301 - 15 Aug 2024

Viewed by 740

Abstract

The assessment of the cognitive workload experienced by air traffic controllers is a complex and prominent issue in the research community. This study introduces new indicators related to gamma waves to detect controllers’ workload and develops experimental protocols to capture their EEG data [...] Read more.

The assessment of the cognitive workload experienced by air traffic controllers is a complex and prominent issue in the research community. This study introduces new indicators related to gamma waves to detect controllers’ workload and develops experimental protocols to capture their EEG data and NASA-TXL data. Then, statistical tests, including the Shapiro–Wilk test and ANOVA, were used to verify whether there was a significant difference between the workload data of the controllers in different scenarios. Furthermore, the Support Vector Machine (SVM) classifier was employed to assess the detection accuracy of these indicators across four categorizations. According to the outcomes, hypotheses suggesting a strong correlation between gamma waves and an air traffic controller’s workload were put forward and subsequently verified; meanwhile, compared with traditional indicators, the indicators associated with gamma waves proposed in this paper have higher accuracy. In addition, to explore the applicability of the indicator, sensitive channels were selected based on the mRMR algorithm for the indicator with the highest accuracy, β + θ + α + γ, showcasing a recognition rate of a single channel exceeding 95% of the full channel, which meets the requirements of convenience and accuracy in practical applications. In conclusion, this study demonstrates that utilizing EEG gamma wave-associated indicators can offer valuable insights into analyzing workload levels among air traffic controllers. Full article

(This article belongs to the Topic Advanced Systems Engineering: Theory and Applications, 2nd Volume)

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17 pages, 48356 KiB  

Open AccessArticle

EfficiencyX: Study of Energy Efficiency between Two Robotic Arms

by Eduardo José-Trujillo, Edgar Adrián Franco-Urquiza, Dario Bringas-Posadas and Antonio Trejo-Morales

Appl. Sci. 2024, 14(15), 6491; https://doi.org/10.3390/app14156491 - 25 Jul 2024

Viewed by 767

Abstract

Optimization of the energy consumption of a Dorna 1 commercial robot was carried out by replacing the original materials of the links (aluminum) with a lighter and more resistant material (carbon fiber) with the aim of lowering the operating costs of the robot. [...] Read more.

Optimization of the energy consumption of a Dorna 1 commercial robot was carried out by replacing the original materials of the links (aluminum) with a lighter and more resistant material (carbon fiber) with the aim of lowering the operating costs of the robot. For this reason, a reduction in the total mass of the robot of 11.08% was achieved by replacing the original materials. In addition, simulations were carried out using finite element analysis to verify that the mechanical resistance of the optimized parts was adequate according to the level of demand that occurs during the operation of the robot. Subsequently, a comparison of the energy consumption of the original robot and the robot with the optimized parts was carried out using the Internet-of-Things device. The tests were carried out at three different speeds—1000, 3000, and 9000 deg/min—for 15 min by executing a pre-established routine starting from home. The results showed that at all test speeds, there were energy savings, but the greatest energy savings occurred at the speed of 3000 degrees/min in the range of 3.66%. With this result, it has been shown that the integration of light materials in robots can achieve energy savings. Full article

(This article belongs to the Topic Advanced Systems Engineering: Theory and Applications, 2nd Volume)

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13 pages, 1283 KiB  

Open AccessArticle

Increasing the Reliability of Software Systems Using a Large-Language-Model-Based Solution for Onboarding

by Ioan Cristian Schuszter and Marius Cioca

Inventions 2024, 9(4), 79; https://doi.org/10.3390/inventions9040079 - 15 Jul 2024

Viewed by 1254

Abstract

Software systems are often maintained by a group of experienced software developers in order to ensure that faults that may bring the system down are less likely. Large turnover in organizations such as CERN makes it important to think of ways of onboarding [...] Read more.

Software systems are often maintained by a group of experienced software developers in order to ensure that faults that may bring the system down are less likely. Large turnover in organizations such as CERN makes it important to think of ways of onboarding newcomers on a technical project rapidly. This paper focuses on optimizing the way that people get up-to-speed on the business logic and technologies used on the project by using a knowledge-imbued large language model that is enhanced using domain-specific knowledge from the group or team’s internal documentation. The novelty of this approach is the gathering of all of these different open-source methods for developing a chatbot and using it in an industrial use-case. Full article

(This article belongs to the Topic Advanced Systems Engineering: Theory and Applications, 2nd Volume)

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28 pages, 4065 KiB  

Open AccessArticle

Modeling and Simulation of a 2SPU-RU Parallel Mechanism for a Prosthetic Ankle with Three Degrees of Freedom

by Victoria E. Abarca and Dante A. Elias

Inventions 2024, 9(4), 71; https://doi.org/10.3390/inventions9040071 - 9 Jul 2024

Viewed by 818

Abstract

To assist an individual with an amputation in regaining daily quality of life, a 2SPU-RU type parallel mechanism was developed based on ankle biomechanics. The inverse kinematic analysis of this mechanism was performed using the vector method. Subsequently, the Jacobian matrices were analyzed. [...] Read more.

To assist an individual with an amputation in regaining daily quality of life, a 2SPU-RU type parallel mechanism was developed based on ankle biomechanics. The inverse kinematic analysis of this mechanism was performed using the vector method. Subsequently, the Jacobian matrices were analyzed. The dynamic model of the mechanism was then created based on the principle of virtual work, and its theoretical solution was compared with numerical results obtained in a simulation environment. Additionally, the validity of the dynamic model and the inverse kinematics was verified by comparing theoretical and simulation results for the movements of plantarflexion–dorsiflexion, eversion–inversion, and abduction–adduction during the gait cycle. Full article

(This article belongs to the Topic Advanced Systems Engineering: Theory and Applications, 2nd Volume)

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13 pages, 13325 KiB  

Open AccessArticle

Converter Capacitor Temperature Estimation Based on Continued Training LSTM under Variable Load Conditions

by Xiaoteng Dai, Yiqiang Chen, Jie Chen and Ruichang Qiu

Sensors 2024, 24(13), 4304; https://doi.org/10.3390/s24134304 - 2 Jul 2024

Viewed by 818

Abstract

Capacitors are crucial components in power electronic converters, responsible for harmonic elimination, energy buffering, and voltage stabilization. However, they are also the most susceptible to damage due to their operational environment. Accurate temperature estimation of capacitors is essential for monitoring their condition and [...] Read more.

Capacitors are crucial components in power electronic converters, responsible for harmonic elimination, energy buffering, and voltage stabilization. However, they are also the most susceptible to damage due to their operational environment. Accurate temperature estimation of capacitors is essential for monitoring their condition and ensuring the reliability of the converter system. This paper presents a novel method for estimating the core temperature of capacitors using a long short-term memory (LSTM) algorithm. The approach incorporates a continued training mechanism to adapt to variable load conditions in converters. Experimental results demonstrate the proposed method’s high accuracy and robustness, making it suitable for real-time capacitor temperature monitoring in practical applications. Full article

(This article belongs to the Topic Advanced Systems Engineering: Theory and Applications, 2nd Volume)

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24 pages, 6340 KiB  

Open AccessArticle

Towards Assessing the Economic Sustainability of Reconfigurable Modularization in Semi-Automatic Assembly Systems: A System Dynamics Perspective

by Gary Linnéusson and Simon Boldt

Systems 2024, 12(6), 218; https://doi.org/10.3390/systems12060218 - 19 Jun 2024

Viewed by 1028

Abstract

The purpose of this paper is to investigate the economic sustainability implications of reconfigurable modularization and changeability in semi-automatic assembly systems using a system dynamics perspective. Through our applied research, using a multiple case study approach, we assess the potential and drawbacks of [...] Read more.

The purpose of this paper is to investigate the economic sustainability implications of reconfigurable modularization and changeability in semi-automatic assembly systems using a system dynamics perspective. Through our applied research, using a multiple case study approach, we assess the potential and drawbacks of reconfigurable modularization to advance sustainable practices in the manufacturing industry with the purpose of improving overall long-term resource allocation in product realization processes. The traditional approach of developing and industrializing one product at a time is becoming obsolete due to factors such as more frequent product introductions, technological innovations, and sustainability requirements. This is due to the increasing trends of product variety and customization, which often necessitate costly modifications to production systems throughout their life cycles. To address these challenges, scholars advocate for the adoption of reconfigurable modular architectures in product and production system designs, facilitated through product platforming. However, when it comes to studies of the long-term economic impacts from the effects in operations, meaning the economic sustainability implications for the production system throughout its life cycle, there is limited research examining the economic rationale for this approach. Therefore, this paper proposes a systematic examination of the economic sustainability implications of reconfigurable modularization in semi-automatic assembly systems using a system dynamics perspective. By leveraging a system dynamics simulation, we structure and investigate the potential economic short- and long-term tradeoffs between the benefits and drawbacks of reconfigurable modularization derived from empirical findings across four case studies. The novelty of this study highlights not only the investment costs and related engineering implications and their costs but also the estimated operation costs encompassing multiple product introductions expected during the life cycle of a production system. We believe that such an approach offers valuable insights into how reconfigurable modularization can be useful from an economic sustainability viewpoint within semi-automatic assembly systems, thereby contributing to the ongoing industrial transformation towards sustainability. Full article

(This article belongs to the Topic Advanced Systems Engineering: Theory and Applications, 2nd Volume)

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18 pages, 3686 KiB  

Open AccessArticle

Solving a Multi-Objective Optimization Problem of a Two-Stage Helical Gearbox with Second-Stage Double Gear Sets Using the MAIRCA Method

by Duc-Binh Vu, Huu-Danh Tran, Van-Thanh Dinh, Duong Vu, Ngoc-Pi Vu and Van-Trang Nguyen

Appl. Sci. 2024, 14(12), 5274; https://doi.org/10.3390/app14125274 - 18 Jun 2024

Viewed by 965

Abstract

This paper provides a novel application of the multi-criteria decision-making (MCDM) method to the multi-objective optimization problem (MOOP) of creating a two-stage helical gearbox (TSHG) with second-stage double gear sets (SDGSs). The aim of the study is to determine the optimum major design [...] Read more.

This paper provides a novel application of the multi-criteria decision-making (MCDM) method to the multi-objective optimization problem (MOOP) of creating a two-stage helical gearbox (TSHG) with second-stage double gear sets (SDGSs). The aim of the study is to determine the optimum major design components for enhancing the gearbox efficiency while reducing the gearbox volume. In this work, three primary design parameters are chosen to accomplish this: the gear ratio of the first stage and the coefficients of the wheel face width (CWFW) of the first and second stages. Additionally, the study is conducted with two distinct objectives in mind: the lowest gearbox volume and the maximum gearbox efficiency. Moreover, phase 1 and phase 2, respectively, are the two stages of the MOOP. Phase 2 handles the MOOP to identify the ideal primary design factors as well as the single-objective optimization problem to minimize the difference between the variable levels. Additionally, the Multi-Attributive Ideal–Real Comparative Analysis (MAIRCA) approach is selected to deal with the MOOP. The results of the study are utilized to determine the ideal values for three crucial design parameters in order to create a TSHG with SDGSs. Full article

(This article belongs to the Topic Advanced Systems Engineering: Theory and Applications, 2nd Volume)

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17 pages, 3835 KiB  

Open AccessArticle

Microcontroller Based Evaluation of Voltage Regulators Efficiency and Their Noise Performance Estimation by Fast Allan Variance Method

by Miroslav Matejček and Mikuláš Šostronek

Electronics 2024, 13(11), 2144; https://doi.org/10.3390/electronics13112144 - 30 May 2024

Viewed by 792

Abstract

This article deals with power supply linear and switching regulators commonly used in various applications for stabilizing an output voltage and ensuring a necessary power input to the load. It describes their basic parameters, performances, advantages, and disadvantages according to their topologies. We [...] Read more.

This article deals with power supply linear and switching regulators commonly used in various applications for stabilizing an output voltage and ensuring a necessary power input to the load. It describes their basic parameters, performances, advantages, and disadvantages according to their topologies. We design a measurement chain for efficiency evaluation based on power monitors INA219 connected to an embedded system, Arduino UNO. Measurements were focused on evaluation linear regulators MA7805, LM317, switching regulators SZBK07, LM2575, SCW05B-05, and XH-M401. The resulting efficiency of linear and switching regulators was analyzed and errors in the measurement chain were evaluated. The second contribution is an innovative way of carrying out regulator noise estimation using a fast Allan variance method, focused on white noise and flicker noise (bias instability). The main contribution is employing a fast Allan variance method algorithm that dramatically decreases computation time by up to 11 s for 72 million measured (or generated) samples. It enables the analysis of large data sets of various physical quantities (for example, regulator output voltages). Full article

(This article belongs to the Topic Advanced Systems Engineering: Theory and Applications, 2nd Volume)

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15 pages, 11074 KiB  

Open AccessArticle

Enhancing Structural Capacity Assessment with a Novel Failure Decision Function for Rectangular Reinforced Concrete Columns

by Petros Christou, Marios Charalambides, Demetris Nicolaides and Georgios Xekalakis

Inventions 2024, 9(3), 63; https://doi.org/10.3390/inventions9030063 - 29 May 2024

Viewed by 916

Abstract

This study introduces the Failure Decision Function, a novel approach for evaluating the structural capacity of rectangular reinforced concrete columns under axial forces and moments, both uniaxial and biaxial. The method simplifies existing practices, enhancing accuracy and integration into design software. The methodology [...] Read more.

This study introduces the Failure Decision Function, a novel approach for evaluating the structural capacity of rectangular reinforced concrete columns under axial forces and moments, both uniaxial and biaxial. The method simplifies existing practices, enhancing accuracy and integration into design software. The methodology hinges on deriving exact biaxial bending failure surfaces, utilizing integral expressions based on material properties and cross-sectional geometry. This direct integration process uncovers failure surface characteristics previously undocumented. Results confirm the utility of the Failure Decision Function through comparative analysis with established literature, showcasing its potential for simplifying and improving structural capacity assessments. The analytic procedure developed enables efficient computation of failure surfaces, streamlining the inclusion of these functions in structural engineering software in two key ways: (1) compiling a library of pre-calculated functions for quick capacity checks and (2) creating a dynamic application that generates these functions based on specific design parameters, allowing users to explore various load and moment scenarios. In conclusion, the Failure Decision Function represents a significant advancement in structural engineering design, offering an accurate and user-friendly method for assessing column performance under critical loading conditions. Full article

(This article belongs to the Topic Advanced Systems Engineering: Theory and Applications, 2nd Volume)

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19 pages, 8948 KiB  

Open AccessArticle

Offline Identification of a Laboratory Incubator

by Süleyman Mantar and Ersen Yılmaz

Appl. Sci. 2024, 14(8), 3466; https://doi.org/10.3390/app14083466 - 19 Apr 2024

Viewed by 1301

Abstract

Laboratory incubators are used to maintain and cultivate microbial and cell cultures. In order to ensure suitable growing conditions and to avoid cell injuries and fast rise and settling times, minimum overshoot and undershoot performance indexes should be considered in the controller design [...] Read more.

Laboratory incubators are used to maintain and cultivate microbial and cell cultures. In order to ensure suitable growing conditions and to avoid cell injuries and fast rise and settling times, minimum overshoot and undershoot performance indexes should be considered in the controller design for incubators. Therefore, it is important to build proper models to evaluate the performance of the controllers before implementation. In this study, we propose an approach to build a model for a laboratory incubator. In this approach, the incubator is considered a linear time-invariant single-input, single-output system. Four different model structures, namely auto-regressive exogenous, auto-regressive moving average exogenous, output error and Box–Jenkins, are applied for modeling the system. The parameters of the model structures are estimated by using prediction error methods. The performances of the model structures are evaluated in terms of mean squared error, mean absolute error and goodness of fit. Additionally, residue analysis including auto-correlation and cross-correlation plots is provided. Experiments are carried out in two scenarios. In the first scenario, the identification dataset is collected from the unit-step response, while in the second scenario, it is collected from the pseudorandom binary sequence response. The experimental study shows that the Box–Jenkins model achieves an over 90% fit percentage for the first scenario and an over 95% fit percentage for the second scenario. Based on the experimental results, it is concluded that the Box–Jenkins model can be used as a successful model for laboratory incubators. Full article

(This article belongs to the Topic Advanced Systems Engineering: Theory and Applications, 2nd Volume)

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31 pages, 2284 KiB  

Open AccessSystematic Review

Risks of Drone Use in Light of Literature Studies

by Agnieszka A. Tubis, Honorata Poturaj, Klaudia Dereń and Arkadiusz Żurek

Sensors 2024, 24(4), 1205; https://doi.org/10.3390/s24041205 - 13 Feb 2024

Cited by 4 | Viewed by 2418

Abstract

This article aims to present the results of a bibliometric analysis of relevant literature and discuss the main research streams related to the topic of risks in drone applications. The methodology of the conducted research consisted of five procedural steps, including the planning [...] Read more.

This article aims to present the results of a bibliometric analysis of relevant literature and discuss the main research streams related to the topic of risks in drone applications. The methodology of the conducted research consisted of five procedural steps, including the planning of the research, conducting a systematic review of the literature, proposing a classification framework corresponding to contemporary research trends related to the risk of drone applications, and compiling the characteristics of the publications assigned to each of the highlighted thematic groups. This systematic literature review used the PRISMA method. A total of 257 documents comprising articles and conference proceedings were analysed. On this basis, eight thematic categories related to the use of drones and the risks associated with their operation were distinguished. Due to the high content within two of these categories, a further division into subcategories was proposed to illustrate the research topics better. The conducted investigation made it possible to identify the current research trends related to the risk of drone use and pointed out the existing research gaps, both in the area of risk assessment methodology and in its application areas. The results obtained from the analysis can provide interesting material for both industry and academia. Full article

(This article belongs to the Topic Advanced Systems Engineering: Theory and Applications, 2nd Volume)

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24 pages, 946 KiB  

Open AccessArticle

A Systematic Model to Improve Productivity in a Transformer Manufacturing Company: A Simulation Case Study

by Yung-Tsan Jou, Ming-Chang Lin, Riana Magdalena Silitonga, Shao-Yang Lu and Ni-Ying Hsu

Appl. Sci. 2024, 14(2), 519; https://doi.org/10.3390/app14020519 - 7 Jan 2024

Cited by 1 | Viewed by 1828

Abstract

The global economy’s slow recovery has led to an increased need for transformers in organizations in recent years. An optimal strategy for production line optimization is to enhance the allocation of staff at each workstation and increase the amount of operational equipment. The [...] Read more.

The global economy’s slow recovery has led to an increased need for transformers in organizations in recent years. An optimal strategy for production line optimization is to enhance the allocation of staff at each workstation and increase the amount of operational equipment. The focus of this study is the investigation of the transformer production line. This study carried out a comprehensive examination of manufacturing area one, manufacturing area two, and manufacturing area three, respectively. The findings revealed that the case factory requires enhancements in the allocation of its workers. The simulation approach allows for the implementation of multi-scenario evaluation and adjustment, ensuring optimal utilization of resources in the enhanced production line, hence enhancing production efficiency and total productivity. Implementing both rotational shifts and night shifts in manufacturing area one enhances the overall production efficiency of the manufacturing area. By redistributing the workforce in area two, it proved feasible to manage the production capacity of a manufacturing area and maintain the operation of the gas-phase drying furnace. With regard to the final aspect, it is imperative to enhance the processing time of preprocessing goods in order to guarantee a consistent supply of the appropriate quantity of products. This will effectively minimize production line delays and enhance overall production efficiency. These enhancement strategies aid the manufacturing company in optimizing resource allocation to enhance production efficiency and productivity. Full article

(This article belongs to the Topic Advanced Systems Engineering: Theory and Applications, 2nd Volume)

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25 pages, 1850 KiB  

Open AccessArticle

Multi-Objective PSO for Control-Loop Tuning of DFIG Wind Turbines with Chopper Protection and Reactive-Current Injection

by Milton E. B. Aguilar, Denis V. Coury, Romeu Reginatto, Renato M. Monaro, Paulo Thiago de Godoy and Tales G. Jahn

Energies 2024, 17(1), 28; https://doi.org/10.3390/en17010028 - 20 Dec 2023

Cited by 1 | Viewed by 835

Abstract

The control systems for the variable-speed wind turbine based on the Doubly Fed Induction Generator (DFIG) pose some tuning challenges. The performance and stability of DFIG wind turbines during faults in power grids are directly related to their controller settings. This work investigates [...] Read more.

The control systems for the variable-speed wind turbine based on the Doubly Fed Induction Generator (DFIG) pose some tuning challenges. The performance and stability of DFIG wind turbines during faults in power grids are directly related to their controller settings. This work investigates how incorporating protection via a braking-Chopper controller connected to the DC link (DC Chopper) and a reactive-current injection during the PI-tuning process affects the performance of DFIG wind turbines during electrical faults. For the tuning process, the Multi-Objective-Particle-Swarm-Optimization (MOPSO) algorithm was used. Thus, two different approaches adopting this methodology were investigated, considering sequential and simultaneous tuning. The results showed that sequential tuning presented a better performance in relation to the reactive-current injection and lower amplitude deviations of the electrical quantities during and after the fault. On the other hand, simultaneous tuning reached damping of the mechanical oscillations faster and presented better performance of the protection system. Full article

(This article belongs to the Topic Advanced Systems Engineering: Theory and Applications, 2nd Volume)

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