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Machines
Volume 9
Issue 8
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Machines, Volume 9, Issue 8 (August 2021) – 41 articles

Cover Story (view full-size image): This study evaluates the accuracy and generalization ability of two deep learning regressors (long-short term memory and convolutional neural network (CNN)) to generate user-oriented reference ankle torque trajectories customized according to walking speed (from 1.0 to 4.0 km/h) and users’ body height and mass (from 1.51 to 1.83 m and 52.0 to 83.7 kg, respectively). Furthermore, this study hypothesizes that regressors can estimate joint torque without resourcing to electromyography signals. The CNN was the most robust algorithm (normalized root mean square error: 0.70 ± 0.06; Spearman correlation: 0.89 ± 0.03; coefficient of determination: 0.91 ± 0.03). No statistically significant differences were found in CNN accuracy (p-value > 0.05) whether electromyography signals are included as inputs or not. View this paper.
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14 pages, 3788 KiB  
Article
Sub-Health Identification of Reciprocating Machinery Based on Sound Feature and OOD Detection
by Peng Cui, Jinjia Wang, Xiaobang Li and Chunfeng Li
Machines 2021, 9(8), 179; https://doi.org/10.3390/machines9080179 - 23 Aug 2021
Cited by 4 | Viewed by 2216
Abstract
It is inevitable that machine parts will be worn down in production, causing other mechanical failures. With the appearance of wearing, the accuracy and efficiency of machinery gradually decline. The state between healthy and impaired is defined as sub-health. By recognizing the sub-health [...] Read more.
It is inevitable that machine parts will be worn down in production, causing other mechanical failures. With the appearance of wearing, the accuracy and efficiency of machinery gradually decline. The state between healthy and impaired is defined as sub-health. By recognizing the sub-health state of machinery, accuracy and efficiency can be effectively guaranteed, and the occurrence of mechanical failure can be prevented. Compared with simple fault detection, the identification of s sub-health state has more practical significance. For this reason, the sound characteristics of large-scale reciprocating machinery, combined with the concept of OOD (out-of-distribution) detection, are used, and a model for detecting machinery sub-health state is proposed. A planer sound dataset was collected and collated, and the recognition of mechanical sub-health state was realized by a model combining a VGG network and the threshold setting scheme of OOD detection. Finally, an auxiliary decision-making module was added, and Mahalanobis distance was used to represent spatial relationships among samples, further improving the recognition effect. Full article
(This article belongs to the Section Machines Testing and Maintenance)
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19 pages, 657 KiB  
Article
Influence of Aerodynamic Preloads and Clearance on the Dynamic Performance and Stability Characteristic of the Bump-Type Foil Air Bearing
by Fabian Walter and Michael Sinapius
Machines 2021, 9(8), 178; https://doi.org/10.3390/machines9080178 - 23 Aug 2021
Cited by 3 | Viewed by 2943
Abstract
The dry lubricated bump-type foil air bearing enables a carrying load capacity due to a pressure build up in a convergent air film. Since the air bearing provides low power dissipation above the lift-off speed and the flexible foil provides an adaptivity against [...] Read more.
The dry lubricated bump-type foil air bearing enables a carrying load capacity due to a pressure build up in a convergent air film. Since the air bearing provides low power dissipation above the lift-off speed and the flexible foil provides an adaptivity against high temperatures, manufacturing errors or rotor growth, the bump-type foil air bearing is in particular suitable for high speed rotating machineries. The corresponding dynamic behavior depends on the operational parameters, the behavior of the flexible foil structure, and in particular on the circumferential clearance. In order to avoid or suppress the critical subsynchronous motion at high rotational speeds, many researchers recommend adding an aerodynamic preload to the bore shape, representing a transition from a circular to a lobed bearing bore shape. In addition to positive effects on the stability, preliminary studies demonstrated degrading effects on the stiffness and damping due to increasing preload values. This observation leads to the assumption, that the preload value meets an optimum with respect to stability, load-capacity, and lift-off speed. With the aim of deriving an appropriate lobe configuration for the design of the bump-type foil air bearing, this work performs comprehensive numerical investigations on the dynamic performance and the stability characteristic as a function of preload and minimum clearance. To this end, this work uses steady-state and transient stability analysis methods to recommend optimal aeroydnamic preload values with respect to the corresponding minimum clearance. Full article
(This article belongs to the Special Issue High Speed Air Compressor for a Fuel Cell System for Use in a Vehicle)
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18 pages, 2682 KiB  
Article
A Performance-Driven MPC Algorithm for Underactuated Bridge Cranes
by Hanqiu Bao, Qi Kang, Jing An, Xianghua Ma and Mengchu Zhou
Machines 2021, 9(8), 177; https://doi.org/10.3390/machines9080177 - 20 Aug 2021
Cited by 15 | Viewed by 3204
Abstract
A crane system often works in a complex environment. It is difficult to model or learn its true dynamics by traditional system identification approaches. If a dynamics model is created by minimizing its prediction error, its use tends to introduce inaccuracies and thus [...] Read more.
A crane system often works in a complex environment. It is difficult to model or learn its true dynamics by traditional system identification approaches. If a dynamics model is created by minimizing its prediction error, its use tends to introduce inaccuracies and thus lead to suboptimal performance. Is it possible to learn the dynamics model of a crane that can achieve the best performance, instead of learning its true dynamics? This work answers the question by presenting a performance-driven model predictive control (P-MPC) algorithm for a two-dimensional underactuated bridge crane. In the proposed dual-layer control architecture, an inner-loop controller uses a proportional–integral–derivative controller to achieve anti-sway rapidly. An outer-loop controller uses MPC to ensure accurate trolley positioning under control constraints. Compared with classical MPC, this work proposes a data-driven method for plant modeling and controller parameter updating. By considering the control target at the learning stage, the method can avoid adjusting the controller to deal with uncertainty. We use Bayesian optimization in an active learning framework where a locally linear dynamics model is learned with the intent of maximizing control performance and then used in conjunction with optimal control schemes to efficiently design a controller for a given task. The model is updated directly based on the performance observed in experiments on the physical system in an iterative manner till a desired performance is achieved. The controller parameters and prediction models of the best closed-loop performance can be found through continuous experiments and iterative optimization. Simulation and experiment results show that we can explicitly find the dynamics model that produces the best performance for an actual system, and the method can quickly suppress swing and realize accurate trolley positioning. The results verified its effectiveness, feasibility, and superior performance on comparing it with state-of-the-art methods. Full article
(This article belongs to the Special Issue Design and Control of Advanced Mechatronics Systems)
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24 pages, 940 KiB  
Article
A Unified Framework for the H∞ Mixed-Sensitivity Design of Fixed Structure Controllers through Putinar Positivstellensatz
by Valentino Razza and Abdul Salam
Machines 2021, 9(8), 176; https://doi.org/10.3390/machines9080176 - 20 Aug 2021
Cited by 1 | Viewed by 2516
Abstract
In this paper, we present a novel technique to design fixed structure controllers, for both continuous-time and discrete-time systems, through an H∞ mixed sensitivity approach. We first define the feasible controller parameter set, which is the set of the controller parameters that [...] Read more.
In this paper, we present a novel technique to design fixed structure controllers, for both continuous-time and discrete-time systems, through an H∞ mixed sensitivity approach. We first define the feasible controller parameter set, which is the set of the controller parameters that guarantee robust stability of the closed-loop system and the achievement of the nominal performance requirements. Then, thanks to Putinar positivstellensatz, we compute a convex relaxation of the original feasible controller parameter set and we formulate the original H∞ controller design problem as the non-emptiness test of a set defined by sum-of-squares polynomials. Two numerical simulations and one experimental example show the effectiveness of the proposed approach. Full article
(This article belongs to the Special Issue Design and Control of Advanced Mechatronics Systems)
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17 pages, 6845 KiB  
Article
Aeroacoustic Optimization of the Bionic Leading Edge of a Typical Blade for Performance Improvement
by Haoran Liu, Yeming Lu, Jinguang Yang, Xiaofang Wang, Jinjun Ju, Jiangang Tu, Zongyou Yang, Hui Wang and Xide Lai
Machines 2021, 9(8), 175; https://doi.org/10.3390/machines9080175 - 18 Aug 2021
Cited by 9 | Viewed by 2526
Abstract
New, innovative optimization approaches to improve turbomachine performance and reduce turbomachine noise are significant in engineering. In this paper, based on the bionic concept, a wave structure is used to shape the leading edge of the blade. Using an NACA0018 blade as the [...] Read more.
New, innovative optimization approaches to improve turbomachine performance and reduce turbomachine noise are significant in engineering. In this paper, based on the bionic concept, a wave structure is used to shape the leading edge of the blade. Using an NACA0018 blade as the basic blade, a united parametric approach controlled by three parameters is proposed to configure the wavy leading edge. Then, a new optimization strategy boosting design efficiency is established to output the optimal design results. Finally, the corresponding performance and flow mechanism are analyzed. Taking into account the existence of the hub wall and the shroud wall from the closed impeller, a near-wall adjustment factor is added, the significance of which is herein demonstrated. An optimal bionic blade is successfully obtained by the optimization strategy, which can reduce the mean drag coefficient by about 6% and the overall sound pressure level by about 3 dB, in relative to the original blade. Mechanism analysis revealed that the wave structure can induce spanwise velocity at the leading edge and cause a further delay in flow separation in the downstream region, synchronously reducing drag and noise. Full article
(This article belongs to the Special Issue Emerging Techniques and Their Application in Turbomachinery)
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17 pages, 1419 KiB  
Article
Operator-Based Nonlinear Control of Calorimetric System Actuated by Peltier Device
by Ryo Chikaraishi and Mingcong Deng
Machines 2021, 9(8), 174; https://doi.org/10.3390/machines9080174 - 18 Aug 2021
Cited by 3 | Viewed by 2131
Abstract
Recently, the development of SiC and GaN high-performance semiconductor devices has led to higher efficiency in power conversion equipment. In order to perform thermal design of power conversion equipment and evaluation of the equipment, it is necessary to measure the power loss of [...] Read more.
Recently, the development of SiC and GaN high-performance semiconductor devices has led to higher efficiency in power conversion equipment. In order to perform thermal design of power conversion equipment and evaluation of the equipment, it is necessary to measure the power loss of the equipment with high accuracy. In a previous study, a system to measure the power loss from the amount of heat emitted from power conversion devices using a Peltier device was proposed. In this study, aiming to improve the measurement accuracy, the temperature dependence of the thermal conductivity of a Peltier device, which was treated as a constant value in the previous study, was considered. The control system considering the temperature dependence of the thermal conductivity was designed based on operator theory, which is a nonlinear control theory. The simulation and experimental results show that the measurement accuracy was improved when the power loss was 10 W and 15 W compared to the case without considering the temperature dependence. In addition, the measurement time was reduced by about 100 s by considering the temperature dependence. The effectiveness of the proposed system was shown when the power loss was 10 W and 15 W. Full article
(This article belongs to the Special Issue Design and Control of Advanced Mechatronics Systems)
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19 pages, 4448 KiB  
Article
Fault Detection and Severity Level Identification of Spiral Bevel Gears under Different Operating Conditions Using Artificial Intelligence Techniques
by Syed Muhammad Tayyab, Steven Chatterton and Paolo Pennacchi
Machines 2021, 9(8), 173; https://doi.org/10.3390/machines9080173 - 18 Aug 2021
Cited by 13 | Viewed by 2826
Abstract
Spiral bevel gears are known for their smooth operation and high load carrying capability; therefore, they are an important part of many transmission systems that are designed for high speed and high load applications. Due to high contact ratio and complex vibration signal, [...] Read more.
Spiral bevel gears are known for their smooth operation and high load carrying capability; therefore, they are an important part of many transmission systems that are designed for high speed and high load applications. Due to high contact ratio and complex vibration signal, their fault detection is really challenging even in the case of serious defects. Therefore, spiral bevel gears have rarely been used as benchmarking for gears’ fault diagnosis. In this research study, Artificial Intelligence (AI) techniques have been used for fault detection and fault severity level identification of spiral bevel gears under different operating conditions. Although AI techniques have gained much success in this field, it is mostly assumed that the operating conditions under which the trained AI model is deployed for fault diagnosis are same compared to those under which the AI model was trained. If they differ, the performance of AI model may degrade significantly. In order to overcome this limitation, in this research study, an effort has been made to find few robust features that show minimal change due to changing operating conditions; however, they are fault discriminating. Artificial neural network (ANN) and K-nearest neighbors (KNN) are used as classifiers and both models are trained and tested by using the selected robust features for fault detection and severity assessment of spiral bevel gears under different operating conditions. A performance comparison between both classifiers is also carried out. Full article
(This article belongs to the Special Issue Structural Health Monitoring for Mechanical Systems)
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13 pages, 3898 KiB  
Communication
Improved Haptic Transparency of Bilateral Control Using Torque-Measured Magnetic Coupling
by Trieu-Khang Tu, I-Haur Tsai, Jia-Yush Yen, Tsu-Chin Tsao and Mi-Ching Tsai
Machines 2021, 9(8), 172; https://doi.org/10.3390/machines9080172 - 18 Aug 2021
Cited by 1 | Viewed by 2259
Abstract
The integrity and transparency of a haptic feedback in a bilateral control is crucial for precise and accurate operators’ sensation during human–machine interactions. Conventional master and slave bilateral control systems are often subject to unknown or unwanted disturbances and dynamics in the actuators [...] Read more.
The integrity and transparency of a haptic feedback in a bilateral control is crucial for precise and accurate operators’ sensation during human–machine interactions. Conventional master and slave bilateral control systems are often subject to unknown or unwanted disturbances and dynamics in the actuators and powertrain linkages that hamper the haptic feedback integrity and transparency. Force sensor torque sensing and feedback control are required to mitigate these effects. In contrast to the conventional approach of introducing torque sensing using a mechanical spring, this paper introduces a magnetic coupling as a torque sensor to detect reaction torque between the human input and the master actuator. Disturbance observer-based torque feedback control is designed to suppress the disturbances and tailor the haptic transparency dynamics. Experimental results on a virtual reality interaction system, which involves the steering wheel bilateral control in a cyber-physical driving simulator system, demonstrate the feasibility and effectiveness of the proposed method with improved haptic integrity and transparency. Full article
(This article belongs to the Special Issue Design and Control of Electrical Machines)
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22 pages, 11441 KiB  
Article
A Redundantly Actuated Chewing Robot Based on Human Musculoskeletal Biomechanics: Differential Kinematics, Stiffness Analysis, Driving Force Optimization and Experiment
by Haiying Wen, Ming Cong, Zhisheng Zhang, Guifei Wang and Yan Zhuang
Machines 2021, 9(8), 171; https://doi.org/10.3390/machines9080171 - 18 Aug 2021
Cited by 9 | Viewed by 2938
Abstract
Human masticatory system exhibits optimal stiffness, energy efficiency and chewing forces needed for the food breakdown due to its unique musculoskeletal actuation redundancy. We have proposed a 6PUS-2HKP (6 prismatic-universal-spherical chains, 2 higher kinematic pairs) redundantly actuated parallel robot (RAPR) based on its [...] Read more.
Human masticatory system exhibits optimal stiffness, energy efficiency and chewing forces needed for the food breakdown due to its unique musculoskeletal actuation redundancy. We have proposed a 6PUS-2HKP (6 prismatic-universal-spherical chains, 2 higher kinematic pairs) redundantly actuated parallel robot (RAPR) based on its musculoskeletal biomechanics. This paper studies the stiffness and optimization of driving force of the bio-inspired redundantly actuated chewing robot. To understand the effect of the point-contact HKP acting on the RAPR performance, the stiffness of the RAPR is estimated based on the derived dimensionally homogeneous Jacobian matrix. In analyzing the influence of the HKP on robot dynamics, the driving forces of six prismatic joints are optimized by adopting the pseudo-inverse optimization method. Numerical results show that the 6PUS-2HKP RAPR has better stiffness performance and more homogenous driving power than its non-redundant 6-PUS counterpart, verifying the benefits that the point-contact HKP brings to the RAPR. Experiments are carried out to measure the temporomandibular joint (TMJ) force and the occlusal force that the robot can generate. The relationship between these two forces in a typical chewing movement is studied. The simulation and experimental results reveal that the existence of TMJs in human masticatory system can provide more homogenous and more efficient chewing force transmission. Full article
(This article belongs to the Special Issue Design and Control of Advanced Mechatronics Systems)
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14 pages, 6110 KiB  
Article
3D Measurement of Structured Specular Surfaces Using Stereo Direct Phase Measurement Deflectometry
by Yuemin Wang, Yongjia Xu, Zonghua Zhang, Feng Gao and Xiangqian Jiang
Machines 2021, 9(8), 170; https://doi.org/10.3390/machines9080170 - 17 Aug 2021
Cited by 15 | Viewed by 2967
Abstract
With the rapid development of modern manufacturing processes, ultra-precision structured freeform surfaces are being widely explored for components with special surface functioning. Measurement of the 3D surface form of structured specular objects remains a challenge because of the complexity of the surface form. [...] Read more.
With the rapid development of modern manufacturing processes, ultra-precision structured freeform surfaces are being widely explored for components with special surface functioning. Measurement of the 3D surface form of structured specular objects remains a challenge because of the complexity of the surface form. Benefiting from a high dynamic range and large measuring area, phase measurement deflectometry (PMD) exhibits great potential in the inspection of the specular surfaces. However, the PMD is insensitive to object height, which leads to the PMD only being used for smooth specular surface measurement. Direct phase measurement deflectometry (DPMD) has been introduced to measure structured specular surfaces, but the surface form measurement resolution and accuracy are limited. This paper presents a method named stereo-DPMD for measuring structured specular objects by introducing a stereo deflectometor into DPMD, so that it combines the advantages of slope integration of the stereo deflectometry and discontinuous height measurement from DPMD. The measured object is separated into individual continuous regions, so the surface form of each region can be recovered precisely by slope integration. Then, the relative positions between different regions are evaluated by DPMD system to reconstruct the final 3D shape of the object. Experimental results show that the structured specular surfaces can be measured accurately by the proposed stereo-DPMD method. Full article
(This article belongs to the Special Issue Precision Measurement and Machines)
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24 pages, 4504 KiB  
Article
Effects of Different Hard Finishing Processes on Gear Excitation
by Maximilian Trübswetter, Joshua Götz, Bernhard Kohn, Michael Otto and Karsten Stahl
Machines 2021, 9(8), 169; https://doi.org/10.3390/machines9080169 - 16 Aug 2021
Cited by 3 | Viewed by 3028
Abstract
Gearboxes are essential in mechanical drive trains for power transmission. A low noise emission and thus an optimized excitation behavior is a substantial design objective for many applications in terms of comfort and operational safety. There exist numerous processes for manufacturing gears, which [...] Read more.
Gearboxes are essential in mechanical drive trains for power transmission. A low noise emission and thus an optimized excitation behavior is a substantial design objective for many applications in terms of comfort and operational safety. There exist numerous processes for manufacturing gears, which all show different properties in relation to the process variables and, therefore, differences in the resulting accuracy and quality of the gear flank. In this paper, the influence of three different manufacturing processes for hard finishing—continuous generating grinding, polish grinding and gear skiving—on the surface structure of gear flanks and the excitation behavior is investigated experimentally and analyzed by the application force level. A tactile scanning of the gear flanks determines the flank surface structure and the deviations from the desired geometry. A torsional acceleration measurement during speed ramp-ups at different load levels is used to analyze the excitation of the gears. The results show only a minor influence of the surface structure on the application force level. The excitation behavior is dominated by the influence of the flank modification and its deviation from the design values. Full article
(This article belongs to the Special Issue Structural Health Monitoring for Mechanical Systems)
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22 pages, 2803 KiB  
Article
A Simple Soft Computing Structure for Modeling and Control
by Hemza Redjimi and József Kázmér Tar
Machines 2021, 9(8), 168; https://doi.org/10.3390/machines9080168 - 14 Aug 2021
Cited by 6 | Viewed by 2408
Abstract
Using the interpolation/extrapolation skills of the core function of an iterative adaptive controller, a structurally simple single essential layer neural network-based topological structure is suggested with fast and explicit single-step teaching and data-retrieving abilities. Its operation does not assume massive parallelism, therefore it [...] Read more.
Using the interpolation/extrapolation skills of the core function of an iterative adaptive controller, a structurally simple single essential layer neural network-based topological structure is suggested with fast and explicit single-step teaching and data-retrieving abilities. Its operation does not assume massive parallelism, therefore it easily can be simulated by simple sequential program codes not needing sophisticated data synchronization mechanisms. It seems to be advantageous in approximate model-based common, robust, or adaptive controllers that can compensate for the effects of minor modeling imprecisions. In this structure a neuron can be in either a firing or a passive (i.e., producing zero output) state. In firing state its activation function realizes an abstract rotation that maps the desired kinematic data into the space of the necessary control forces. The activation function allows the use of a simple and fast incremental model modification for slowly varying dynamic models. Its operation is exemplified by numerical simulations for a van der Pol oscillator in free motion, and within a Computed Torque type control. To reveal the possibility for efficient model correction, a robust Variable Structure/Sliding Mode Controller is applied, too. The novel structure can be obtained by approximate experimental observations as e.g., the fuzzy models. Full article
(This article belongs to the Special Issue Modeling, Sensor Fusion and Control Techniques in Applied Robotics)
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17 pages, 3330 KiB  
Article
Adaptive Data-Driven Control for Linear Time Varying Systems
by Talal Abdalla
Machines 2021, 9(8), 167; https://doi.org/10.3390/machines9080167 - 13 Aug 2021
Cited by 2 | Viewed by 3370
Abstract
In this paper, we propose an adaptive data-driven control approach for linear time varying systems, affected by bounded measurement noise. The plant to be controlled is assumed to be unknown, and no information in regard to its time varying behaviour is exploited. First, [...] Read more.
In this paper, we propose an adaptive data-driven control approach for linear time varying systems, affected by bounded measurement noise. The plant to be controlled is assumed to be unknown, and no information in regard to its time varying behaviour is exploited. First, using set-membership identification techniques, we formulate the controller design problem through a model-matching scheme, i.e., designing a controller such that the closed-loop behaviour matches that of a given reference model. The problem is then reformulated as to derive a controller that corresponds to the minimum variation bounding its parameters. Finally, a convex relaxation approach is proposed to solve the formulated controller design problem by means of linear programming. The effectiveness of the proposed scheme is demonstrated by means of two simulation examples. Full article
(This article belongs to the Special Issue Design and Control of Advanced Mechatronics Systems)
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24 pages, 7038 KiB  
Article
Fault Detection and Diagnosis for Plasticizing Process of Single-Base Gun Propellant Using Mutual Information Weighted MPCA under Limited Batch Samples Modelling
by Mingyi Yang, Junyi Wang, Yinlong Zhang, Xinlin Bai, Zhigang Xu, Xiaofang Xia and Linlin Fan
Machines 2021, 9(8), 166; https://doi.org/10.3390/machines9080166 - 12 Aug 2021
Cited by 4 | Viewed by 2528
Abstract
Aiming at the lack of reliable gradual fault detection and abnormal condition alarm and evaluation ability in the plasticizing process of single-base gun propellant, a fault detection and diagnosis method based on normalized mutual information weighted multiway principal component analysis (NMI-WMPCA) under limited [...] Read more.
Aiming at the lack of reliable gradual fault detection and abnormal condition alarm and evaluation ability in the plasticizing process of single-base gun propellant, a fault detection and diagnosis method based on normalized mutual information weighted multiway principal component analysis (NMI-WMPCA) under limited batch samples modelling was proposed. In this method, the differences of coupling correlation among multi-dimensional process variables and the coupling characteristics of linear and nonlinear relationships in the process are considered. NMI-WMPCA utilizes the generalization ability of a multi-model to establish an accurate fault detection model in limited batch samples, and adopts fault diagnosis methods based on a multi-model SPE statistic contribution plot to identify the fault source. The experimental results demonstrate that the proposed method is effective, which can realize the rapid detection and diagnosis of multiple faults in the plasticizing process. Full article
(This article belongs to the Section Industrial Systems)
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26 pages, 8129 KiB  
Article
The Development of an Automated Multi-Spit Lamb Rotisserie Machine for Improved Productivity
by Xun Wei Chia, Poh Kiat Ng, Robert Jeyakumar Nathan, Jian Ai Yeow, Way Soong Lim and Yu Jin Ng
Machines 2021, 9(8), 165; https://doi.org/10.3390/machines9080165 - 11 Aug 2021
Cited by 2 | Viewed by 4370
Abstract
Innovations in food manufacturing support the agenda for sustainable development goal 9 (SDG9) on industry, innovation and infrastructure. Pursuant to this goal, this study aims to develop an automated multi-spit lamb rotisserie machine that potentially improves the lamb-roasting productivity for small and medium [...] Read more.
Innovations in food manufacturing support the agenda for sustainable development goal 9 (SDG9) on industry, innovation and infrastructure. Pursuant to this goal, this study aims to develop an automated multi-spit lamb rotisserie machine that potentially improves the lamb-roasting productivity for small and medium enterprises (SMEs). The conceptualisation involved patents, scholarly literature and product reviews of lamb-roasting devices. The design and analysis are performed using Autodesk Inventor 2019. A scaled-down prototype is developed and tested with (1) roasting output, (2) roasting time and (3) temperature stability tests. The data for test (1) are analysed by comparing the means between control and experimental groups. The data for tests (2) and (3) are analysed using the t-test and Mann–Whitney U test, respectively. Significant differences are observed in tests (1) and (2), with outcomes being in favour of the proposed invention. The prototype cooks 92.27% faster with 700% more meat than a regular lamb roaster. It also cooks at a stable temperature. The cost analysis indicated that this invention could be sold at USD 278 if mass-produced. The design is structurally simple, inexpensive and easy to manufacture, allowing SMEs that rely on traditional spit-based machines to enhance their ability in producing roast lamb. Full article
(This article belongs to the Collection Machines, Mechanisms and Robots: Theory and Applications)
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13 pages, 3748 KiB  
Article
Behavior of Rotary Ultrasonic Machining of Ceramic Materials at a Wide Range of Cutting Speeds
by Marcel Kuruc and Jozef Peterka
Machines 2021, 9(8), 164; https://doi.org/10.3390/machines9080164 - 11 Aug 2021
Cited by 1 | Viewed by 3023
Abstract
The paper deals with the behavior of the rotary ultrasonic machining process at different cutting speeds of ceramic materials. This process is relatively new; therefore, there are gaps in information about its behavior at near-critical parameters. We adjusted cutting speeds 10 times lower [...] Read more.
The paper deals with the behavior of the rotary ultrasonic machining process at different cutting speeds of ceramic materials. This process is relatively new; therefore, there are gaps in information about its behavior at near-critical parameters. We adjusted cutting speeds 10 times lower and 10 times higher than the recommended one. The observed parameters were machine load, tool wear, and surface roughness. Alumina and zirconia ceramics were used as materials. The results will help with the optimization of the cutting parameters of the rotary ultrasonic machining process. Full article
(This article belongs to the Section Advanced Manufacturing)
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18 pages, 1839 KiB  
Article
Study on the Importance of a Slicer Selection for the 3D Printing Process Parameters via the Investigation of G-Code Readings
by Jakub Bryła and Adam Martowicz
Machines 2021, 9(8), 163; https://doi.org/10.3390/machines9080163 - 11 Aug 2021
Cited by 10 | Viewed by 4303
Abstract
The work deals with the investigation of the variation of the selected 3D printing process properties that originate from the choice of a slicer. Specifically, the main aim of the present study was to assess the induced changes of the kinematic and geometric [...] Read more.
The work deals with the investigation of the variation of the selected 3D printing process properties that originate from the choice of a slicer. Specifically, the main aim of the present study was to assess the induced changes of the kinematic and geometric properties considered by the slicer for the printing process making use of the G-code readings. The paper provides adequate definitions and formulas required to characterize the slicer’s configuration. Next, the selected cases of the process parameters’ changes were studied, primarily taking into account varying layer height and infill. The authors performed a detailed analysis regarding the geometric implications at the mesoscale due to the slicer’s settings. Appropriate modifications of the slicer’s properties were also proposed and verified, making it possible to match the geometric and kinematic characteristics of the printed part. Full article
(This article belongs to the Special Issue Advances and Trends in Non-conventional, Abrasive and Precision Machining 2021)
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19 pages, 2322 KiB  
Article
Analysis and Control of Vibrations of a Cartesian Cutting Machine Using an Equivalent Robotic Model
by Matteo Bottin, Giulio Cipriani, Domenico Tommasino and Alberto Doria
Machines 2021, 9(8), 162; https://doi.org/10.3390/machines9080162 - 10 Aug 2021
Cited by 4 | Viewed by 2501
Abstract
The vibrations of a Cartesian cutting machine caused by the pneumatic tool are studied with a sub-system approach. The cutting head is modeled as an equivalent robot arm which is able to mimic the measured resonances. The Cartesian structure is modeled according to [...] Read more.
The vibrations of a Cartesian cutting machine caused by the pneumatic tool are studied with a sub-system approach. The cutting head is modeled as an equivalent robot arm which is able to mimic the measured resonances. The Cartesian structure is modeled according to the mode superposition approach. A global analytical model is obtained coupling the aforementioned models, and is solved in MATLAB. The full model is able to predict the variations in the response of the machine to tool excitation that are caused by the motion of the head along the rails of the Cartesian structure. Comparisons with experimental results are made. Full article
(This article belongs to the Section Robotics, Mechatronics and Intelligent Machines)
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23 pages, 5402 KiB  
Article
Integral Modeling for Deviation Correction Trajectory of the Mechanical Vertical Drilling System
by Lin Chai, Kai Zhang, Dengwen Yang, Baolin Liu and Delong Zhang
Machines 2021, 9(8), 161; https://doi.org/10.3390/machines9080161 - 9 Aug 2021
Cited by 5 | Viewed by 2995
Abstract
The deviation correction trajectory of the mechanical vertical drilling system (MVDS) is very important because it is the final embodiment of performance. However, it is impossible to obtain it at the design stage, except when using simulation methods. In this paper, tool face [...] Read more.
The deviation correction trajectory of the mechanical vertical drilling system (MVDS) is very important because it is the final embodiment of performance. However, it is impossible to obtain it at the design stage, except when using simulation methods. In this paper, tool face angle model and other theoretical models were established, respectively, and the trajectory simulation method was created through model coupling. Next, the method was used to simulate the trajectory of MVDS under two typical working conditions. The results indicate that the critical deviation angle is the deviation control accuracy of the MVDS. The existence of critical deflection angle makes MVDS correct deviation and change azimuth at the same time, resulting in the trajectory being a three-dimensional curve, which has the tendency of drifting to the left. Furthermore, the deviation and azimuth change rate are constantly changing in the process of drilling. The results also show that the MVDS is unable to correct the horizontal displacement of the downhole. The proposed method and analysis results are helpful to find out and solve the problem of the current design as soon as possible, and to provide guidance for the subsequent structure optimization. Full article
(This article belongs to the Special Issue Dynamics and Diagnostics of Heavy-Duty Industrial Machines)
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15 pages, 3975 KiB  
Article
Research on Vehicle Adaptive Cruise Control Method Based on Fuzzy Model Predictive Control
by Jin Mao, Lei Yang, Yuanbo Hu, Kai Liu and Jinfu Du
Machines 2021, 9(8), 160; https://doi.org/10.3390/machines9080160 - 8 Aug 2021
Cited by 17 | Viewed by 3766
Abstract
Under complex working conditions, vehicle adaptive cruise control (ACC) systems with fixed weight coefficients cannot guarantee good car following performance under all conditions. In order to improve the tracking and comfort of vehicles in different modes, a fuzzy model predictive control (Fuzzy-MPC) algorithm [...] Read more.
Under complex working conditions, vehicle adaptive cruise control (ACC) systems with fixed weight coefficients cannot guarantee good car following performance under all conditions. In order to improve the tracking and comfort of vehicles in different modes, a fuzzy model predictive control (Fuzzy-MPC) algorithm is proposed. Based on the comprehensive consideration of safety, comfort, fuel economy and vehicle limitations, the objective function and constraints are designed. A relaxation factor vector is introduced to soften the hard constraint boundary in order to solve this problem, for which there was previously no feasible solution. In order to maintain driving stability under complex conditions, a multi-objective optimization method, which can update the weight coefficient online, is proposed. In the numerical simulation, the values of velocity, relative distance, acceleration and acceleration change rate under different conditions are compared, and the results show that the proposed algorithm has better tracking and stability than the traditional algorithm. The effectiveness and reliability of the Fuzzy-MPC algorithm are verified by co-simulation with the designed PID lower layer control algorithm with front feedforward and feedback. Full article
(This article belongs to the Special Issue Advances in Vehicle Dynamics Control and Motion Planning for Autonomous/Semi-autonomous Vehicles)
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23 pages, 4645 KiB  
Article
An Almost Comprehensive Approach for the Choice of Motor and Transmission in Mechatronic Applications: Torque Peak of the Motor
by Giancarlo Cusimano and Federico Casolo
Machines 2021, 9(8), 159; https://doi.org/10.3390/machines9080159 - 8 Aug 2021
Cited by 3 | Viewed by 1942
Abstract
The choice of motor and transmission to move a joint must ensure that the torque peaks of the motor lie inside its dynamic operating range. With this aim, this paper proposes an approach in which all the candidate transmissions are processed one by [...] Read more.
The choice of motor and transmission to move a joint must ensure that the torque peaks of the motor lie inside its dynamic operating range. With this aim, this paper proposes an approach in which all the candidate transmissions are processed one by one to find among all the candidate motors those they could execute the reference task with. Consequently, all the transmission parameters, and not only its transmission ratio, are taken into consideration in advance. For rectangular dynamic operating ranges, this approach allows a direct and precise evaluation of all the admissible motor-transmission couples, without any approximation and further check. Apart from an entirely automated procedure, the method also provides diagrams through which the designer can concisely compare the admissible solutions. Furthermore, the method provides a solution for the drive systems in which the limit torque of the dynamic operating range does depend on the motor speed. Full article
(This article belongs to the Section Machine Design and Theory)
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15 pages, 9913 KiB  
Article
Numerical Investigation of Nozzle Jet Flow in a Pelton Microturbine
by Dorian Nedelcu, Vasile Cojocaru and Raoul-Cristian Avasiloaie
Machines 2021, 9(8), 158; https://doi.org/10.3390/machines9080158 - 8 Aug 2021
Cited by 5 | Viewed by 3871
Abstract
The characterization of flow through Pelton hydro turbines allows the optimization of their operation and maximization of energy performance. The flow in the injector of Pelton turbines and in the free jet area (the area from the injector outlet surface to the runner [...] Read more.
The characterization of flow through Pelton hydro turbines allows the optimization of their operation and maximization of energy performance. The flow in the injector of Pelton turbines and in the free jet area (the area from the injector outlet surface to the runner bucket inlet surface) is influenced by several parameters: the geometry of injector components (nozzle and injector spear), the injector opening, and the turbine head. The parameters of the free jet flow (velocity distribution, pressure distribution, and jet spread) are reflected in the turbine efficiency. The research presented in this paper focuses on the numerical characterization of flow in the injector and the free jet of a Pelton microturbine. Three injector geometries were considered, with different nozzle diameters: 13.3 mm, 14.4 mm, and 16.3 mm. For each of these geometries, the flow was analyzed for five values of turbine head (H = 15 m, H = 20 m, H = 25 m, H = 30 m, H = 35 m) and six values of injector opening (S = 3 mm, S = 6 mm, S = 9 mm, S = 12 mm, S = 15 mm, S = 18 mm). The results of numerical simulations were used to plot injector flow-rate characteristics and injector force characteristics (the resultant force on the injector spear and the resultant force on the injector nozzle). The highest influence on the flow rate variation is given by the variation of turbine head, followed by the variation of the injector opening and the variation of the nozzle diameter. Increasing the nozzle diameter accentuates the variation of the flow rate versus the turbine head. The variation of axial velocity and pressure in the free jet is presented for four sections parallel to the outlet section of the injector. The injector openings that generate the highest values of velocity/pressure on the runner inlet surface are highlighted. The results allow optimization of functional parameters for increasing turbine efficiency and optimizing the design process of Pelton microturbines. Full article
(This article belongs to the Section Turbomachinery)
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15 pages, 4361 KiB  
Article
Digital Twin-Driven Mating Performance Analysis for Precision Spool Valve
by Wenbin Tang, Guangshen Xu, Shoujing Zhang, Shoufeng Jin and Runxiao Wang
Machines 2021, 9(8), 157; https://doi.org/10.3390/machines9080157 - 7 Aug 2021
Cited by 17 | Viewed by 2775
Abstract
The precision spool valve is the core component of the electro-hydraulic servo control system, and its performance has an important influence on the flight control of aviation and aerospace products. The non-uniform surface topography error causes a non-uniform mating gap field inside the [...] Read more.
The precision spool valve is the core component of the electro-hydraulic servo control system, and its performance has an important influence on the flight control of aviation and aerospace products. The non-uniform surface topography error causes a non-uniform mating gap field inside the spool valve, which causes oil leakage and leads to deterioration of the spool valve performance. However, the current oil leakage calculation method only considers the influence of size errors, which is not comprehensive. Thus, how to characterize the mating behavior of the spool valve and its effect on oil leakage with consideration of surface topography errors is the key to evaluating the performance of the spool valve. This paper proposes a new way of analyzing the mating performance of precision spool valves, which considers the surface topography errors based on digital twin technology. Firstly, a general framework for the analysis of mating performance of precision spool valve based on a digital twin is proposed. Then, key technologies of assembly interface geometry modeling, matching behavior modeling and performance analysis are studied. Finally, a quantitative correlation between the mating parameters and the oil leakage of the precision spool valve is revealed. The method is tested on a practical case. This proposed method can provide theoretical support for the accurate prediction and evaluation of the mating performance of the precision spool valve. Full article
(This article belongs to the Section Machine Design and Theory)
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16 pages, 4225 KiB  
Article
A Hybrid Multi-Objective Optimization Method Based on NSGA-II Algorithm and Entropy Weighted TOPSIS for Lightweight Design of Dump Truck Carriage
by Rongchao Jiang, Shukun Ci, Dawei Liu, Xiaodong Cheng and Zhenkuan Pan
Machines 2021, 9(8), 156; https://doi.org/10.3390/machines9080156 - 7 Aug 2021
Cited by 23 | Viewed by 4794
Abstract
The lightweight design of vehicle components is regarded as a complex optimization problem, which usually needs to achieve two or more optimization objectives. It can be firstly solved by a multi-objective optimization algorithm for generating Pareto solutions, before then seeking the optimal design. [...] Read more.
The lightweight design of vehicle components is regarded as a complex optimization problem, which usually needs to achieve two or more optimization objectives. It can be firstly solved by a multi-objective optimization algorithm for generating Pareto solutions, before then seeking the optimal design. However, it is difficult to determine the optimal design for lack of engineering knowledge about ideal and nadir values. Therefore, this paper proposes a multi-objective optimization procedure combined with the NSGA-II algorithm with entropy weighted TOPSIS for the lightweight design of the dump truck carriage. The finite element model of the dump truck carriage was firstly developed for modal analysis under unconstrained free state and strength analysis under the full load and lifting conditions. On this basis, the multi-objective lightweight optimization of the dump truck carriage was carried out based on the Kriging surrogate model and the NSGA-II algorithm. Then, the entropy weight TOPSIS method was employed to select the optimal design of the dump truck from Pareto solutions. The results show that the optimized dump truck carriage achieves a remarkable mass reduction of 81 kg, as much as 3.7%, while its first-order natural frequency and strength performance are slightly improved compared with the original model. Accordingly, the proposed procedure provides an effective way for vehicle lightweight design. Full article
(This article belongs to the Special Issue Dynamics and Diagnostics of Heavy-Duty Industrial Machines)
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15 pages, 4161 KiB  
Article
Mathematical Validation of Experimentally Optimised Parameters Used in a Vibration-Based Machine-Learning Model for Fault Diagnosis in Rotating Machines
by Natalia Espinoza-Sepulveda and Jyoti Sinha
Machines 2021, 9(8), 155; https://doi.org/10.3390/machines9080155 - 7 Aug 2021
Cited by 10 | Viewed by 3048
Abstract
Mathematical models have been widely used in the study of rotating machines. Their application in dynamics has eased further research since they can avoid time-consuming and exorbitant experimental processes to simulate different faults. The earlier vibration-based machine-learning (VML) model for fault diagnosis in [...] Read more.
Mathematical models have been widely used in the study of rotating machines. Their application in dynamics has eased further research since they can avoid time-consuming and exorbitant experimental processes to simulate different faults. The earlier vibration-based machine-learning (VML) model for fault diagnosis in rotating machines was developed by optimising the vibration-based parameters from experimental data on a rig. Therefore, a mathematical model based on the finite-element (FE) method is created for the experimental rig, to simulate several rotor-related faults. The generated vibration responses in the FE model are then used to validate the earlier developed fault diagnosis model and the optimised parameters. The obtained results suggest the correctness of the selected parameters to characterise the dynamics of the machine to identify faults. These promising results provide the possibility of implementing the VML model in real industrial systems. Full article
(This article belongs to the Special Issue Structural Health Monitoring for Mechanical Systems)
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18 pages, 3424 KiB  
Article
Kinematics, Speed, and Anthropometry-Based Ankle Joint Torque Estimation: A Deep Learning Regression Approach
by Luís Moreira, Joana Figueiredo, João Paulo Vilas-Boas and Cristina Peixoto Santos
Machines 2021, 9(8), 154; https://doi.org/10.3390/machines9080154 - 6 Aug 2021
Cited by 19 | Viewed by 4386
Abstract
Powered Assistive Devices (PADs) have been proposed to enable repetitive, user-oriented gait rehabilitation. They may include torque controllers that typically require reference joint torque trajectories to determine the most suitable level of assistance. However, a robust approach able to automatically estimate user-oriented reference [...] Read more.
Powered Assistive Devices (PADs) have been proposed to enable repetitive, user-oriented gait rehabilitation. They may include torque controllers that typically require reference joint torque trajectories to determine the most suitable level of assistance. However, a robust approach able to automatically estimate user-oriented reference joint torque trajectories, namely ankle torque, while considering the effects of varying walking speed, body mass, and height on the gait dynamics, is needed. This study evaluates the accuracy and generalization ability of two Deep Learning (DL) regressors (Long-Short Term Memory and Convolutional Neural Network (CNN)) to generate user-oriented reference ankle torque trajectories by innovatively customizing them according to the walking speed (ranging from 1.0 to 4.0 km/h) and users’ body height and mass (ranging from 1.51 to 1.83 m and 52.0 to 83.7 kg, respectively). Furthermore, this study hypothesizes that DL regressors can estimate joint torque without resourcing electromyography signals. CNN was the most robust algorithm (Normalized Root Mean Square Error: 0.70 ± 0.06; Spearman Correlation: 0.89 ± 0.03; Coefficient of Determination: 0.91 ± 0.03). No statistically significant differences were found in CNN accuracy (p-value > 0.05) whether electromyography signals are included as inputs or not, enabling a less obtrusive and accurate setup for torque estimation. Full article
(This article belongs to the Special Issue Smart Machines: Applications and Advances in Human Motion Analysis)
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18 pages, 7700 KiB  
Article
Iterative Parameter Optimization for Multiple Switching Control Applied to a Precision Stage for Microfabrication
by Fu-Cheng Wang, Jun-Fu Lu, Tien-Tung Chung and Jia-Yush Yen
Machines 2021, 9(8), 153; https://doi.org/10.3390/machines9080153 - 3 Aug 2021
Viewed by 1953
Abstract
This paper proposes an iteration procedure to derive optimal parameters for a multiple switching control architecture. Control design is usually a compromise between various performance requirements; therefore, switching between multiple controllers that achieve a particular performance under different conditions can potentially improve the [...] Read more.
This paper proposes an iteration procedure to derive optimal parameters for a multiple switching control architecture. Control design is usually a compromise between various performance requirements; therefore, switching between multiple controllers that achieve a particular performance under different conditions can potentially improve the overall system behavior. In this paper, we consider a control-switching mechanism that can automatically switch controllers based on the prediction of future responses, and we develop an iteration procedure that can optimize the mechanism parameters, such as the number of controllers and the prediction horizon. We then implement the proposed mechanism in a long-stroke precision stage, and demonstrate the effectiveness of switching robust control with simulations and experiments. Lastly, we integrate the stage with a two-photon polymerization system to fabricate microlenses. The optical properties confirm that the proposed iterative parameter optimization procedure is effective in improving the performance of microfabrication employing multiple switching control. Full article
(This article belongs to the Special Issue Design and Control of Electrical Machines)
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24 pages, 2643 KiB  
Article
Synchronization Control of a Dual-Cylinder Lifting Gantry of Segment Erector in Shield Tunneling Machine under Unbalance Loads
by Litong Lyu, Xiao Liang and Jingbo Guo
Machines 2021, 9(8), 152; https://doi.org/10.3390/machines9080152 - 2 Aug 2021
Cited by 5 | Viewed by 3003
Abstract
Segment assembling is one of the principle processes during tunnel construction using shield tunneling machines. The segment erector is a robotic manipulator powered by a hydraulic system to assemble prefabricated concrete segments onto the excavated tunnel surface. Nowadays, automation of the segment erector [...] Read more.
Segment assembling is one of the principle processes during tunnel construction using shield tunneling machines. The segment erector is a robotic manipulator powered by a hydraulic system to assemble prefabricated concrete segments onto the excavated tunnel surface. Nowadays, automation of the segment erector has become one of the definite developing trends to further improve the efficiency and safety during construction; thus, closed-loop motion control is an essential technology. Within the segment erector, the lifting gantry is driven by dual cylinders to lift heavy segments in the radial direction. Different from the dual-cylinder mechanism used in other machines such as forklifts, the lifting gantry usually works at an inclined angle, leading to unbalanced loads on the two sides. Although strong guide rails are applied to ensure synchronization, the gantry still occasionally suffers from chattering, “pull-and-drag”, or even being stuck in practice. Therefore, precise motion tracking control as well as high-level synchronization of the dual cylinders have become essential for the lifting gantry. In this study, a complete dynamics model of the dual-cylinder lifting gantry is constructed, considering the linear motion as well as the additional rotational motion of the crossbeam, which reveals the essence of poor synchronization. Then, a two-level synchronization control scheme is synthesized. The thrust allocation is designed to coordinate the dual cylinders and keep the rotational angle of the crossbeam within a small range. The motion tracking controller is designed based on the adaptive robust control theory to guarantee the linear motion tracking precision. The theoretical performance is analyzed with corresponding proof. Finally, comparative simulations are conducted and the results show that the proposed scheme achieves high-precision motion tracking performance and simultaneous high-level synchronization of dual cylinders under unbalanced loads. Full article
(This article belongs to the Special Issue Advanced Control of Industrial Electro-Hydraulic Systems)
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13 pages, 3747 KiB  
Article
Online Nonlinear Error Compensation Circuit Based on Neural Networks
by Zhenyi Gao, Bin Zhou, Chunge Ju, Qi Wei, Xinxi Zhang and Rong Zhang
Machines 2021, 9(8), 151; https://doi.org/10.3390/machines9080151 - 31 Jul 2021
Cited by 1 | Viewed by 2006
Abstract
Nonlinear errors of sensor output signals are common in the field of inertial measurement and can be compensated with statistical models or machine learning models. Machine learning solutions with large computational complexity are generally offline or implemented on additional hardware platforms, which are [...] Read more.
Nonlinear errors of sensor output signals are common in the field of inertial measurement and can be compensated with statistical models or machine learning models. Machine learning solutions with large computational complexity are generally offline or implemented on additional hardware platforms, which are difficult to meet the high integration requirements of microelectromechanical system inertial sensors. This paper explored the feasibility of an online compensation scheme based on neural networks. In the designed solution, a simplified small-scale network is used for modeling, and the peak-to-peak value and standard deviation of the error after compensation are reduced to 17.00% and 16.95%, respectively. Additionally, a compensation circuit is designed based on the simplified modeling scheme. The results show that the circuit compensation effect is consistent with the results of the algorithm experiment. Under SMIC 180 nm complementary metal-oxide semiconductor (CMOS) technology, the circuit has a maximum operating frequency of 96 MHz and an area of 0.19 mm2. When the sampling signal frequency is 800 kHz, the power consumption is only 1.12 mW. This circuit can be used as a component of the measurement and control system on chip (SoC), which meets real-time application scenarios with low power consumption requirements. Full article
(This article belongs to the Section Micro/Nano Electromechanical Systems (MEMS/NEMS))
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12 pages, 2585 KiB  
Article
Evaluation of the Ability to Accurately Produce Angular Details by 3D Printing of Plastic Parts
by Andrei Marius Mihalache, Gheorghe Nagîț, Laurențiu Slătineanu, Adelina Hrițuc, Angelos Markopoulos and Oana Dodun
Machines 2021, 9(8), 150; https://doi.org/10.3390/machines9080150 - 29 Jul 2021
Cited by 2 | Viewed by 2046
Abstract
3D printing is a process that has become widely used in recent years, allowing the production of parts with relatively complicated shapes from metallic and non-metallic materials. In some cases, it is challenging to evaluate the ability of 3D printers to make fine [...] Read more.
3D printing is a process that has become widely used in recent years, allowing the production of parts with relatively complicated shapes from metallic and non-metallic materials. In some cases, it is challenging to evaluate the ability of 3D printers to make fine details of parts. For such an assessment, the printing of samples showing intersections of surfaces with low angle values was considered. An experimental plan was designed and materialized to highlight the influence of different factors, such as the thickness of the deposited material layer, the printing speed, the cooling and filling conditions of the 3D-printed part, and the thickness of the sample. Samples using areas in the form of isosceles triangles with constant height or bases with the same length, respectively, were used. The mathematical processing of the experimental results allowed the determination of empirical mathematical models of the power-function type. It allowed the detection of both the direction of actions and the intensity of the influence exerted by the input factors. It is concluded that the strongest influence on the printer’s ability to produce fine detail, from the point of view addressed in the paper, is exerted by the vertex angle, whose reduction leads to a decrease in printing accuracy. Full article
(This article belongs to the Special Issue Advances and Trends in Non-conventional, Abrasive and Precision Machining 2021)
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