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Applied Sciences
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Advanced Materials and Technology Innovation in Machine System
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Advanced Materials and Technology Innovation in Machine System

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Mechanical Engineering".

Deadline for manuscript submissions: closed (30 December 2022) | Viewed by 9892

Special Issue Editors

Dr. Chengjung Yang

E-Mail Website
Guest Editor
Program in Interdisciplinary Studies, National Sun Yat-sen University, Kaohsiung 80424, Taiwan
Interests: mechanical and sustainable design; artificial intelligence; 3D-printing technology; application of cyber-physical production systems
Prof. Dr. Richard (Chunhui) Yang

E-Mail Website
Guest Editor
School of Engineering, Design and Built Environment, Western Sydney University, Penrith, NSW 2751, Australia
Interests: additive manufacturing; advanced manufacturing; multiscale modelling and simulations of advanced engineering materials and structures; engineering numerical methods and their applications; digital material representation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent years, the booming development of Industry 4.0, green energy and advanced materials has also led to rapid evolution in the field of machinery to improve the characteristics of mechanical systems. With the development of Industry 4.0, the application of artificial intelligence makes mechanical systems more and more optimized, intelligent and diversified. For instance, the introduction of intelligent manufacturing makes the manufacturing process more optimal. Besides, the evolution of control and modeling technologies has also enabled mechanical systems to achieve more precise movements. As for advanced materials, materials with better characteristics are being developed to make mechanical systems more robust and lighter.

This Special Issue aims to publish original papers about the advanced materials and innovative technologies used to improve the characteristics of mechanical systems. The improvement can arise from material, security, robustness, control, efficiency, sustainability (especially on energy saving and carbon reduction), etc. Submissions from experts in academia and industry are both strongly encouraged.

Potential research topics include, but are not limited to:

  • Green material, materials design and applications;
  • Smart systems;
  • Intelligent manufacturing;
  • Renewable and green energy;
  • Artificial intelligence and applications;
  • Deep learning and applications;
  • Intelligent mechatronics and robotics;
  • Expert systems with applications;
  • Cyber–physical system;
  • Advanced system modeling and simulation techniques;
  • Advanced automation and process control.

Dr. Chengjung Yang
Prof. Dr. Richard (Chunhui) Yang
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. Applied Sciences 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 2400 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.

Published Papers (5 papers)

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Research

21 pages, 14463 KiB  
Article
A Wind-Turbine-Tower-Climbing Robot Prototype Operating at Various Speeds and Payload Capacity: Development and Validation
by Kathleen Ebora Padrigalan and Jui-Hung Liu
Appl. Sci. 2023, 13(3), 1381; https://0-doi-org.brum.beds.ac.uk/10.3390/app13031381 - 20 Jan 2023
Viewed by 1597
Abstract
The development of control technology on wind turbine application robots has played an integral role in facilitating the digitization of inspection and maintenance in the wind energy industry. This paper presents a wind-turbine-climbing robot that determines the service lifespan of the wind turbine [...] Read more.
The development of control technology on wind turbine application robots has played an integral role in facilitating the digitization of inspection and maintenance in the wind energy industry. This paper presents a wind-turbine-climbing robot that determines the service lifespan of the wind turbine components subject to its payload capacity. The model has four rubber wheels, as the driving mechanism for its locomotion is being supported by a Bowden cable as a winding mechanism for its adhesion. The design further incorporates an Arduino microcontroller, distance sensors, motors, and a step motor to form its electromechanical structure. The overall capability of the robot has been analyzed through its kinematics and dynamics. Practical indoor experiments using a wind turbine tower mockup have been conducted for the validation of the various speeds and payload capacity of the prototype. The results indicate the effectiveness of its driving and winding mechanism to climb at the various speeds and with or without a payload. The advantage of the operations of its mechanism conformed with the wind turbine application robots. Full article
(This article belongs to the Special Issue Advanced Materials and Technology Innovation in Machine System)
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14 pages, 2516 KiB  
Article
Sustainable Manufacturing Decisions through the Optimization of Printing Parameters in 3D Printing
by Cheng-Jung Yang and Sin-Syuan Wu
Appl. Sci. 2022, 12(19), 10060; https://0-doi-org.brum.beds.ac.uk/10.3390/app121910060 - 06 Oct 2022
Cited by 4 | Viewed by 1499
Abstract
The 3D printers integrated with fused filament fabrication (FFF) are highly valued worldwide because of their properties, which include fast proofing, compatibility with various materials, and low printing cost. The competitiveness of FFF can be enhanced by improving printing quality. However, due to [...] Read more.
The 3D printers integrated with fused filament fabrication (FFF) are highly valued worldwide because of their properties, which include fast proofing, compatibility with various materials, and low printing cost. The competitiveness of FFF can be enhanced by improving printing quality. However, due to the increasing sustainability issues worldwide, there is an urgent need to lower energy consumption. In this study, we focused on fan rate, printing speed, nozzle temperature, build plate temperature, and layer thickness as factors that directly impact the dimensional accuracy, carbon dioxide emissions, and printing cost of FFF printers. Several single-objective and multiobjective optimization tasks were performed using the Taguchi method and desirability approach to implement sustainable manufacturing decisions. In single-objective optimization, the inner width, outer width, material cost, and labor cost were most easily affected by the layer thickness. The outer length, carbon dioxide emissions, and electricity cost were significantly affected by the build plate temperature. In multiobjective optimization, a different set of printing parameters can be used to optimize dimensional accuracy, carbon dioxide emissions, material cost, labor cost, and electricity cost. This study helps users to obtain optimal solutions under different optimization requirements to cope with diverse manufacturing characteristics. Full article
(This article belongs to the Special Issue Advanced Materials and Technology Innovation in Machine System)
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12 pages, 2023 KiB  
Article
Wind Turbine Anomaly Detection Using Mahalanobis Distance and SCADA Alarm Data
by Jui-Hung Liu, Nelson T. Corbita, Jr., Rong-Mao Lee and Chun-Chieh Wang
Appl. Sci. 2022, 12(17), 8661; https://0-doi-org.brum.beds.ac.uk/10.3390/app12178661 - 29 Aug 2022
Cited by 5 | Viewed by 2122
Abstract
Wind energy is becoming a common source of renewable energy in the world. Wind turbines are increasing in number, both for onshore and offshore applications. One challenge with wind turbines is in detecting anomalies that cause their breakdown. Due to the complex nature [...] Read more.
Wind energy is becoming a common source of renewable energy in the world. Wind turbines are increasing in number, both for onshore and offshore applications. One challenge with wind turbines is in detecting anomalies that cause their breakdown. Due to the complex nature of the wind turbine assembly, it is quite an extensive process to detect causes of malfunctions in the system. This study uses the Mahalanobis distance (MD) to detect anomalies in wind turbine operation, using SCADA alarm data as a comparison. Different predictive models were generated as the bases for analyses in MD computations. Using the SCADA alarm data as a reference, trend patterns that deviated from the threshold value were compared. Results showed that the MD could be used to detect anomalies within a group of data sets, with behaviors learned based on the model used. A large portion of those data sets deviated from the threshold level, corresponding to serious alarms in the SCADA data. We concluded that the MD can detect anomalies in different wind turbine components, based on this study. MD analysis of models can be used in conditions monitoring systems of wind turbines. Full article
(This article belongs to the Special Issue Advanced Materials and Technology Innovation in Machine System)
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22 pages, 9053 KiB  
Article
Identification Approach for Nonlinear MIMO Dynamics of Closed-Loop Active Magnetic Bearing System
by Hsin-Lin Chiu
Appl. Sci. 2022, 12(17), 8556; https://0-doi-org.brum.beds.ac.uk/10.3390/app12178556 - 26 Aug 2022
Cited by 2 | Viewed by 1163
Abstract
A systematic identification approach for the rotor/radial active magnetic bearing (rotor/RAMB) system is presented in this study. First, the system identification of the controller of commercial TMP is undertaken, and the corresponding linear dynamic models are constructed. To perfectly excite the nonlinearities of [...] Read more.
A systematic identification approach for the rotor/radial active magnetic bearing (rotor/RAMB) system is presented in this study. First, the system identification of the controller of commercial TMP is undertaken, and the corresponding linear dynamic models are constructed. To perfectly excite the nonlinearities of the rotor/RAMB system, a parallel amplitude-modulated pseudo-random binary sequence (PAPRBS) generator, which possesses the merits of no correlation among the perturbation signals, is employed. The dynamics of the rotor/RAMB system is identified with a Hammerstein–Wiener model. To reduce the difficulty of the identified two nonlinear blocks, the output nonlinear characteristics are estimated prior to the recursive process. Two conventional nonlinear model structures, i.e., NARX and NARMAX, are employed for comparison to verify the effectiveness of the identified Hammerstein–Wiener model. The averaged fit values of the Hammerstein–Wiener model, NARX model, and NARMAX model are 93.25%, 88.36%, and 76.91%, respectively. Full article
(This article belongs to the Special Issue Advanced Materials and Technology Innovation in Machine System)
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15 pages, 5109 KiB  
Article
A Rule-Based Control Strategy of Driver Demand to Enhance Energy Efficiency of Hybrid Electric Vehicles
by Kuohsiu David Huang, Minh-Khoa Nguyen and Po-Tuan Chen
Appl. Sci. 2022, 12(17), 8507; https://0-doi-org.brum.beds.ac.uk/10.3390/app12178507 - 25 Aug 2022
Cited by 5 | Viewed by 2715
Abstract
In recent years, hybrid electric vehicles (HEVs) have increased significantly due to climate change and the demand for high-efficiency power sources. HEVs that combine an internal combustion engine (ICE) and an electric motor (EM) can improve the power output of the ICE and [...] Read more.
In recent years, hybrid electric vehicles (HEVs) have increased significantly due to climate change and the demand for high-efficiency power sources. HEVs that combine an internal combustion engine (ICE) and an electric motor (EM) can improve the power output of the ICE and overcome the challenges of the insufficient battery life of electric vehicles. In this study, a parallel HEV with a power distribution mechanism is developed for energy saving and carbon reduction. The driver′s power demands are used as input sources, and a rule-based control strategy is used to determine the power distribution of the generator, EM, and ICE. The NEDC2000 driving cycle is used as the test benchmark to demonstrate the performance of the HEV. In comparison to ICE vehicles, the fuel efficiency of HEVs significantly improved. In addition, other parameters, including the average brake-specific fuel consumption (BSFC), brake-specific carbon monoxide emission (BSCO), and brake-specific hydrocarbons (BSHCs), were lower, which can effectively save fossil fuel and reduce air pollution. Full article
(This article belongs to the Special Issue Advanced Materials and Technology Innovation in Machine System)
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