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Machines
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Reliability of Mechatronic Systems and Machine Elements: Testing and Validation
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Reliability of Mechatronic Systems and Machine Elements: Testing and Validation

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Machines Testing and Maintenance".

Deadline for manuscript submissions: closed (31 August 2022) | Viewed by 27910

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editors

Prof. Dr. Sven Matthiesen

E-Mail Website
Guest Editor
Institute of Product Engineering, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany
Interests: validation and testing of mechatronic systems; methods and processes to support the product development of human-machine systems; development of design methodologies
Dr. Thomas Gwosch

E-Mail Website
Guest Editor
Institute of Product Engineering, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany
Interests: test and validation methods for mechatronic systems and mechatronic machine elements; reliability testing of human-machine systems; frontloading in product engineering

Special Issue Information

Dear Colleagues,

The reliability of mechatronic systems and its machine elements is a key aspect in engineering design, which will become even more important in the future due to the complexity of the mechanical and electronic control especially in human–machine systems. The advancement in mechatronics design urges for systematic test and validation methods, test environments such as test rigs, as well as modelling approaches. Effective test and validation methods are still a challenging topic for the validation of system reliability for mechatronic systems and its machine elements—especially for the human–machine interaction and mechatronized machine elements. This Special Issue of Machines will provide an international forum for professionals, academics, and researchers to present the latest reseach and developments from modelling approaches, test and validation methods, and applications of system reliability analysis of mechatronic systems.

This Special Issue will accept contributions describing innovative research and developments in “Reliability of Mechatronic Systems and Machine Elements”. The Special Issue will cover a wide range of disciplines, including mechatronic systems, robotics and advanced machines, automation and control systems, human–machine systems, and manufacturing systems. It particularly welcomes those emerging methodologies and techniques which bridge theoretical studies and applications in system reliability and test methods. Novel quantitative engineering and science studies may be considered as well.

The proposed Special Issue particularly fits the following scopes of MDPI’s Machines journal:

  • mechatronics, robotics, automation, and control systems;
  • mechatronic system modeling and simulation techniques and methodologies;
  • innovative human–machine interactions for intelligent mechatronic systems;
  • machine diagnostics and prognostics (condition monitoring);
  • mechanical systems, machines and related machine elements;
  • test and validation methods for mechatronic systems.

Prof. Dr. Sven Matthiesen
Dr. Thomas Gwosch
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. Machines 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 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.

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (12 papers)

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Editorial

Jump to: Research

4 pages, 191 KiB  
Editorial
Reliability of Mechatronic Systems and Machine Elements: Testing and Validation
by Thomas Gwosch and Sven Matthiesen
Machines 2023, 11(3), 317; https://doi.org/10.3390/machines11030317 - 21 Feb 2023
Cited by 1 | Viewed by 1559
Abstract
The design of reliable systems is a key challenge in product engineering [...] Full article
(This article belongs to the Special Issue Reliability of Mechatronic Systems and Machine Elements: Testing and Validation)

Research

Jump to: Editorial

18 pages, 6403 KiB  
Article
Model-Based Control Design of an EHA Position Control Based on Multicriteria Optimization
by Matthias Dörr, Felix Leitenberger, Kai Wolter, Sven Matthiesen and Thomas Gwosch
Machines 2022, 10(12), 1190; https://doi.org/10.3390/machines10121190 - 8 Dec 2022
Cited by 6 | Viewed by 1676
Abstract
For the control of dynamic systems such as an Electro-Hydraulic Actuator (EHA), there is a need to optimize the control based on simulations, since a prototype or a physical system is usually not available during system design. In consequence, no system identification can [...] Read more.
For the control of dynamic systems such as an Electro-Hydraulic Actuator (EHA), there is a need to optimize the control based on simulations, since a prototype or a physical system is usually not available during system design. In consequence, no system identification can be performed. Therefore, it is unclear how well a simulation model of an EHA can be used for multicriteria optimization of the position control due to the uncertain model quality. To evaluate the suitability for control optimization, the EHA is modeled and parameterized as a grey-box model using existing parameters independent of test bench experiments. A method for multi-objective optimization of a controller is used to optimize the position control of the EHA. Finally, the step responses are compared with the test bench. The evaluation of the step responses for different loads and control parameters shows similar behavior between the simulation model and the physical system on the test bench, although the essential phenomena could not be reproduced. This means that the model quality achieved by modeling is suitable as an indication for the optimization of the control by simulation without a physical system. Full article
(This article belongs to the Special Issue Reliability of Mechatronic Systems and Machine Elements: Testing and Validation)
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16 pages, 3011 KiB  
Article
New Control Strategy for Heating Portable Fuel Cell Power Systems for Energy-Efficient and Reliable Operation
by Sebastian Zimprich, Diego Dávila-Portals, Sven Matthiesen and Thomas Gwosch
Machines 2022, 10(12), 1159; https://doi.org/10.3390/machines10121159 - 3 Dec 2022
Cited by 1 | Viewed by 1606
Abstract
Using hydrogen fuel cells for power systems, temperature conditions are important for efficient and reliable operations, especially in low-temperature environments. A heating system with an electrical energy buffer is therefore required for reliable operation. There is a research gap in finding an appropriate [...] Read more.
Using hydrogen fuel cells for power systems, temperature conditions are important for efficient and reliable operations, especially in low-temperature environments. A heating system with an electrical energy buffer is therefore required for reliable operation. There is a research gap in finding an appropriate control strategy regarding energy efficiency and reliable operations for different environmental conditions. This paper investigates heating strategies for the subfreezing start of a fuel cell for portable applications at an early development stage to enable frontloading in product engineering. The strategies were investigated by simulation and experiment. A prototype for such a system was built and tested for subfreezing start-ups and non-subfreezing start-ups. This was done by heating the fuel cell system with different control strategies to test their efficiency. It was found that operating strategies to heat up the fuel cell system can ensure a more reliable and energy-efficient operation. The heating strategy needs to be adjusted according to the ambient conditions, as this influences the required heating energy, efficiency, and reliable operation of the system. A differentiation in the control strategy between subfreezing and non-subfreezing temperatures is recommended due to reliability reasons. Full article
(This article belongs to the Special Issue Reliability of Mechatronic Systems and Machine Elements: Testing and Validation)
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14 pages, 7046 KiB  
Article
The Effect of Sensor Integration on the Load Carrying Capacity of Gears
by Luca Bonaiti, Erich Knoll, Michael Otto, Carlo Gorla and Karsten Stahl
Machines 2022, 10(10), 888; https://doi.org/10.3390/machines10100888 - 2 Oct 2022
Cited by 7 | Viewed by 2484
Abstract
Classical machine elements have been around for centuries, even millennia. However, the current advancement in Structural Health Monitoring (SHM), together with Condition Monitoring (CM), requires that machine elements should be upgraded from a not-simple object to an intelligent object, able to provide information [...] Read more.
Classical machine elements have been around for centuries, even millennia. However, the current advancement in Structural Health Monitoring (SHM), together with Condition Monitoring (CM), requires that machine elements should be upgraded from a not-simple object to an intelligent object, able to provide information about its working conditions to its surroundings, especially its health. However, the integration of electronics in a mechanical component may lead to a reduction in its load capacity since the component may need to be modified in order to accommodate them. This paper describes a case study, where, differently from other cases present in the literature, sensor integration has been developed under the gear teeth of an actual case-hardened helical gear pair to be used within an actual gearbox. This article has two different purposes. On the one hand, it aims to investigate the effect that component-level SHM/CM has on the gear load carrying capacity. On the other hand, it also aims to be of inspiration to the reader who wants to undertake the challenges of designing a sensor-integrated gear. Full article
(This article belongs to the Special Issue Reliability of Mechatronic Systems and Machine Elements: Testing and Validation)
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15 pages, 3849 KiB  
Article
Degeneration Effects of Thin-Film Sensors after Critical Load Conditions of Machine Components
by Rico Ottermann, Tobias Steppeler, Folke Dencker and Marc Christopher Wurz
Machines 2022, 10(10), 870; https://doi.org/10.3390/machines10100870 - 27 Sep 2022
Cited by 4 | Viewed by 2381
Abstract
In the context of intelligent components in industrial applications in the automotive, energy or construction sector, sensor monitoring is crucial for security issues and to avoid long and costly downtimes. This article discusses component-inherent thin-film sensors for this purpose, which, in contrast to [...] Read more.
In the context of intelligent components in industrial applications in the automotive, energy or construction sector, sensor monitoring is crucial for security issues and to avoid long and costly downtimes. This article discusses component-inherent thin-film sensors for this purpose, which, in contrast to conventional sensor technology, can be applied inseparably onto the component’s surface via sputtering, so that a maximum of information about the component’s condition can be generated, especially regarding deformation. This article examines whether the sensors can continue to generate reliable measurement data even after critical component loads have been applied. This extends their field of use concerning plastic deformation behavior. Therefore, any change in sensor properties is necessary for ongoing elastic strain measurements. These novel fundamentals are established for thin-film constantan strain gauges and platinum temperature sensors on steel substrates. In general, a k-factor decrease and an increase in the temperature coefficient of resistance with increasing plastic deformation could be observed until a sensor failure above 0.5% plastic deformation (constantan) occurred (1.3% for platinum). Knowing these values makes it possible to continue measuring elastic strains after critical load conditions on a machine component in terms of plastic deformation. Additionally, a method of sensor-data fusion for the clear determination of plastic deformation and temperature change is presented. Full article
(This article belongs to the Special Issue Reliability of Mechatronic Systems and Machine Elements: Testing and Validation)
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16 pages, 5798 KiB  
Article
Investigation of the Voltage-Induced Damage Progression on the Raceway Surfaces of Thrust Ball Bearings
by André Harder, Anatoly Zaiat, Florian Michael Becker-Dombrowsky, Steffen Puchtler and Eckhard Kirchner
Machines 2022, 10(10), 832; https://doi.org/10.3390/machines10100832 - 21 Sep 2022
Cited by 11 | Viewed by 2188
Abstract
In the course of the electrification of powertrains, rolling element bearings are increasingly subject to electrical damage. In contrast to mechanically generated pittings, voltage-induced surface damage is a continuous process. Though several approaches for the description of the damage state of a bearing [...] Read more.
In the course of the electrification of powertrains, rolling element bearings are increasingly subject to electrical damage. In contrast to mechanically generated pittings, voltage-induced surface damage is a continuous process. Though several approaches for the description of the damage state of a bearing are known, a generally accepted quantification for the bearing damage has not been established yet. This paper investigates surface properties, which can be used as a metric damage scale for the quantification of the electric bearing damage progression. For this purpose, the requirements for suitable surface properties are defined. Afterwards, thrust ball bearings are installed on a test rig, with constantly loaded mechanically and periodically damaged electrically in multiple phases. After each phase, the bearings are disassembled, the bearing surfaces are graded and measured for 45 different standardized surface properties. These properties are evaluated with the defined requirements. For the ones meeting the requirements, critical levels are presented, which allow for a quantified distinction between grey frosting and corrugation surfaces. These values are compared with measurements presented in the literature showing that the identified surface properties are suitable for the quantification of electrical bearing damages. Full article
(This article belongs to the Special Issue Reliability of Mechatronic Systems and Machine Elements: Testing and Validation)
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16 pages, 4351 KiB  
Article
Reliability-Based Robust Design Optimization for Maximizing the Output Torque of Brushless Direct Current (BLDC) Motors Considering Manufacturing Uncertainty
by Kyunghun Jeon, Donghyeon Yoo, Jongjin Park, Ki-Deok Lee, Jeong-Jong Lee and Chang-Wan Kim
Machines 2022, 10(9), 797; https://doi.org/10.3390/machines10090797 - 10 Sep 2022
Cited by 8 | Viewed by 2346
Abstract
In recent years, the deterministic design optimization method has been widely used to improve the output performance of brushless direct current (BLDC) motors. However, it does not contribute to reducing the failure rate and performance variation of products because it cannot determine the [...] Read more.
In recent years, the deterministic design optimization method has been widely used to improve the output performance of brushless direct current (BLDC) motors. However, it does not contribute to reducing the failure rate and performance variation of products because it cannot determine the manufacturing uncertainty. In this study, we proposed reliability-based robust design optimization to improve the output torque of a BLDC motor while reducing the failure rate and performance variation. We calculated the output torque and vibration response of the BLDC motor using the electromagnetic–structural coupled analysis. We selected the tooth thickness, slot opening width, slot radius, slot depth, tooth width, magnet thickness, and magnet length as the design variables related to the shape of the stator and rotor that affect the output torque. We considered the distribution of design variables with manufacturing tolerances. We performed a reliability analysis of the BLDC motor considering the distribution of design variables with manufacturing tolerances. Using the reliability analysis results, we performed reliability-based robust design optimization (RBRDO) to maximize the output torque; consequently, the output torque increased by 8.8% compared to the initial BLDC motor, the standard deviation in output performance decreased by 46.9% with improved robustness, and the failure rate decreased by 99.2% with enhanced reliability. The proposed reliability-based robust design optimization is considered to be useful in the actual product design field because it can evaluate both the reliability and robustness of the product and improve its performance in the design stage. Full article
(This article belongs to the Special Issue Reliability of Mechatronic Systems and Machine Elements: Testing and Validation)
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16 pages, 3335 KiB  
Article
Optimizing System Reliability in Additive Manufacturing Using Physics-Informed Machine Learning
by Sören Wenzel, Elena Slomski-Vetter and Tobias Melz
Machines 2022, 10(7), 525; https://doi.org/10.3390/machines10070525 - 29 Jun 2022
Cited by 6 | Viewed by 2358
Abstract
Fused filament fabrication (FFF), an additive manufacturing process, is an emerging technology with issues in the uncertainty of mechanical properties and quality of printed parts. The consideration of all main and interaction effects when changing print parameters is not efficiently feasible, due to [...] Read more.
Fused filament fabrication (FFF), an additive manufacturing process, is an emerging technology with issues in the uncertainty of mechanical properties and quality of printed parts. The consideration of all main and interaction effects when changing print parameters is not efficiently feasible, due to existing stochastic dependencies. To address this issue, a machine learning method is developed to increase reliability by optimizing input parameters and predicting system responses. A structure of artificial neural networks (ANN) is proposed that predicts a system response based on input parameters and observations of the system and similar systems. In this way, significant input parameters for a reliable system can be determined. The ANN structure is part of physics-informed machine learning and is pretrained with domain knowledge (DK) to require fewer observations for full training. This includes theoretical knowledge of idealized systems and measured data. New predictions for a system response can be made without retraining but by using further observations from the predicted system. Therefore, the predictions are available in real time, which is a precondition for the use in industrial environments. Finally, the application of the developed method to print bed adhesion in FFF and the increase in system reliability are discussed and evaluated. Full article
(This article belongs to the Special Issue Reliability of Mechatronic Systems and Machine Elements: Testing and Validation)
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20 pages, 5788 KiB  
Article
Analysis of Load Inhomogeneity of Two-Tooth Difference Swing-Rod Movable Teeth Transmission System under External Excitation
by Rui Wei, Yali Yi, Menglei Wu, Meiyu Chen and Herong Jin
Machines 2022, 10(7), 502; https://doi.org/10.3390/machines10070502 - 22 Jun 2022
Cited by 1 | Viewed by 1600
Abstract
In order to improve the load state of the two-tooth difference swing-rod movable teeth transmission system, in this paper, a dynamic equivalent calculation model of the transmission system is established based on lumped parameter theory, and then a calculation method of system dynamic [...] Read more.
In order to improve the load state of the two-tooth difference swing-rod movable teeth transmission system, in this paper, a dynamic equivalent calculation model of the transmission system is established based on lumped parameter theory, and then a calculation method of system dynamic load is derived. The influence of external excitation on load inhomogeneity of the transmission system is analyzed from a dynamic point of view. The theoretical results are verified by Adams dynamic load simulation analysis and strain test based on a test bench. The results show that when errors of the transmission system are fixed, the system load inhomogeneity is improved effectively with the increase of load torque, while the system load inhomogeneity becomes worse as input speed increases. This study provides a theoretical reference for improving the load inhomogeneity of the two-tooth difference swing-rod movable teeth transmission system. Full article
(This article belongs to the Special Issue Reliability of Mechatronic Systems and Machine Elements: Testing and Validation)
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18 pages, 1962 KiB  
Article
Analysis of the Influence of Component Type and Operating Condition on the Selection of Preventive Maintenance Strategy in Multistage Industrial Machines: A Case Study
by Francisco Javier Álvarez García and David Rodríguez Salgado
Machines 2022, 10(5), 385; https://doi.org/10.3390/machines10050385 - 17 May 2022
Cited by 10 | Viewed by 2749
Abstract
The study of industrial multistage component’s reliability, availability and efficiency poses a constant challenge for the manufacturing industry. Components that suffer wear and tear must be replaced according to the times recommended by the manufacturers and users of the machines. This paper studies [...] Read more.
The study of industrial multistage component’s reliability, availability and efficiency poses a constant challenge for the manufacturing industry. Components that suffer wear and tear must be replaced according to the times recommended by the manufacturers and users of the machines. This paper studies the influence of the individual maintenance values of Main Time To Repair (MTTR), Time To Provisioning (TTPR) and Time Lost Production (TLP) of each component, including the type of component and operation conditions as variables that can influence deciding on the best preventive maintenance strategy for each component. The comparison between different preventive maintenance strategies, Preventive Programming Maintenance (PPM) and Improve Preventive Programming Maintenance (IPPM) provide very interesting efficiency and availability results in the components. A case study is evaluated using PPM and IPPM strategies checking the improvement in availability and efficiency of the components. However, the improvement of stock cost of components by adopting IPPM strategy supposes the search of another more optimal solution. This paper concludes with the creation of a multidimensional matrix, for that purpose, to select the best preventive maintenance strategy (PPM, IPPM or interval between PPM and IPPM) for each component of the multistage machine based on its operating conditions, type of component and individual maintenance times. The authors consider this matrix can be used by other industrial manufacturing multistage machines to decide on the best maintenance strategy for their components. Full article
(This article belongs to the Special Issue Reliability of Mechatronic Systems and Machine Elements: Testing and Validation)
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16 pages, 3798 KiB  
Article
Functional Investigation of Geometrically Scaled Drive Components by X-in-the-Loop Testing with Scaled Prototypes
by Michael Steck, Sven Matthiesen and Thomas Gwosch
Machines 2022, 10(3), 165; https://doi.org/10.3390/machines10030165 - 22 Feb 2022
Cited by 1 | Viewed by 1867
Abstract
Validation is important for a high product quality of drive components. An X-in-the-Loop test bench enables the integration of scaled prototypes through coupling systems and scaling models even before serial parts are available. In the context of X-in-the-loop investigations, it is still unclear [...] Read more.
Validation is important for a high product quality of drive components. An X-in-the-Loop test bench enables the integration of scaled prototypes through coupling systems and scaling models even before serial parts are available. In the context of X-in-the-loop investigations, it is still unclear whether a scaling model enables the early investigation of geometry variants in powertrain subsystems. In this paper, scaled geometry experiments taking into account the interacting system are considered to evaluate the scaling model in terms of early investigation of geometry variants. The aim of this paper is the functional investigation of geometrically scaled drive components by integrating scaled prototypes in an X-in-the-Loop test bench. Using an overload clutch with detents, component variants of different size levels are investigated in scaled experiments with a scaling model. The results confirm possibilities of X-in-the-Loop integration of scaled prototypes and their investigation on geometrically scaled drive components. The investigations show, therefore, the opportunities of integrating scaled drive components through the scaling model to support the investigation of geometry variants before serial parts are available. Scaled geometry investigations considering the interacting system can, thus, support product development. Full article
(This article belongs to the Special Issue Reliability of Mechatronic Systems and Machine Elements: Testing and Validation)
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18 pages, 10331 KiB  
Article
Dynamic Analysis of a High-Contact-Ratio Spur Gear System with Localized Spalling and Experimental Validation
by Zhenbang Cheng, Kang Huang, Yangshou Xiong and Meng Sang
Machines 2022, 10(2), 154; https://doi.org/10.3390/machines10020154 - 18 Feb 2022
Cited by 10 | Viewed by 3090
Abstract
The dynamic characteristics and tooth spalling fault features are studied for the high-contact-ratio spur gear bearing system. The bending torsional dynamic model is proposed in this study for the gear bearing system with an ellipsoid spalling fault. This model also considers time-varying meshing [...] Read more.
The dynamic characteristics and tooth spalling fault features are studied for the high-contact-ratio spur gear bearing system. The bending torsional dynamic model is proposed in this study for the gear bearing system with an ellipsoid spalling fault. This model also considers time-varying meshing stiffness, tooth friction, fractal gear backlash, and comprehensive transmission error. The meshing stiffness of the system is evaluated using the potential energy method. The bifurcation diagram, time-domain waveform, Poincaré map, phase map, frequency spectrum, and related three-dimensional map are used as tools to analyze the system’s dynamic response qualitatively. The results reveal that the system’s motion with ellipsoid tooth spalling defect exhibits rich dynamic behavior. The response of the proposed dynamic model is consistent with experimental results in the frequency domain. Therefore, the developed dynamic model can predict the system’s vibration behavior with localized spalling fault. Hence, it could also provide a theoretical foundation for future spall defect diagnosis of the gear transmission system. Full article
(This article belongs to the Special Issue Reliability of Mechatronic Systems and Machine Elements: Testing and Validation)
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