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Applied Sciences
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Smart Manufacturing and Materials
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Smart Manufacturing and Materials

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

Deadline for manuscript submissions: closed (10 June 2022) | Viewed by 21830

Special Issue Editor

Prof. Dr. Marek Placzek

E-Mail Website
Guest Editor
Institute of Engineering Processes Automation and Integrated Manufacturing Systems, Silesian University of Technology, Gliwice, Poland
Interests: piezoelectricity; vibration damping; mechatronic systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In the era of industry transformation, in line with the concept of Industry 4.0, modern manufacturing technologies and modern materials are becoming the subject of interest for an increasing number of scientists, engineers and business. Increasing production efficiency and flexible changes to the assortment and product personalization pose new challenges. However, modern technologies and materials allow for the faster and faster development of industry and a change in the way people work and their role in production processes. Efficiency, flexibility and production speed translate into increased competitiveness and the reduction of production costs. To achieve this, modern manufacturing technologies are used, including additive manufacturing, systems based on virtual and augmented reality, artificial intelligence, autonomous robots, simulations, and systems integration. Operations on large data sets and cloud computing are becoming necessary, and the industrial Internet of Things is gaining importance, but cybersecurity is also becoming a key element. All these issues are inextricably linked with the concept of modern, smart manufacturing and smart factories.

The concept of more and more intelligent materials often also refers to the materials used in manufactured products and as elements of the production systems themselves. Smart materials are gaining more and more popularity and are being increasingly used in the modern world. Their applications open completely new paths of technological development and create new possibilities. This leads to the development of modern devices and technologies, and allows the development of new, previously unattainable solutions. It is extremely important to develop concepts and assumptions for action and research in laboratory conditions and on real objects of innovative systems based on the use of smart materials. At the same time, the modeling of technical means in which smart materials are used due to the complexity of the phenomena occurring in them is a complex task. The correct description of a given device in the form of a mathematical model, at the design stage, is, however, the basic condition for its proper operation. The development of mathematical models and algorithms for the analysis and determination of the characteristics of technical measures containing such materials is therefore an important element of scientific research.

For this Special Issue, I invite the submission of original papers and reviews of scientific papers presenting innovative solutions in the field of smart technologies and smart materials. Issues concerning modeling, testing, and applications can be presented. I encourage you to publish studies containing the results of conceptual work and laboratory and real object tests, to present issues, including the use of modern modeling and simulation methods.

In case you have any questions or doubts, you can contact me by email.

Prof. Dr. Marek Placzek
Guest Editor

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.

Keywords

  • smart technology;
  • smart materials;
  • simulation; modeling;
  • analysis;
  • testing;
  • big data;
  • autonomous robots;
  • system integration;
  • industrial IoT;
  • cybersecurity;
  • cloud computing;
  • additive manufacturing;
  • reverse engineering;
  • virtual and augmented reality;
  • artificial intelligence;
  • piezoelectric transducers;
  • electrostatic materials;
  • magnetostrictive materials;
  • shape memory materials;
  • variable viscosity liquids;
  • thermoelectric materials;
  • light emitting materials

Published Papers (10 papers)

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Research

10 pages, 1596 KiB  
Article
Analytical Prediction of Molten Pool Dimensions in Powder Bed Fusion Considering Process Conditions-Dependent Laser Absorptivity
by Wenjia Wang, Jinqiang Ning, Hamid Garmestani and Steven Y. Liang
Appl. Sci. 2022, 12(23), 11926; https://0-doi-org.brum.beds.ac.uk/10.3390/app122311926 - 23 Nov 2022
Viewed by 1721
Abstract
This research proposes an analytical method for the prediction of molten pool size in laser-based powder bed fusion (LPBF) additive manufacturing with the consideration of process conditions-dependent absorptivity. Under different process conditions, the melting modes in LPBF are different, which induces the difference [...] Read more.
This research proposes an analytical method for the prediction of molten pool size in laser-based powder bed fusion (LPBF) additive manufacturing with the consideration of process conditions-dependent absorptivity. Under different process conditions, the melting modes in LPBF are different, which induces the difference in laser absorptivity. An empirical model of absorptivity was used to calculate the laser absorptivity under various process conditions. An analytical point-moving heat source model was employed to calculate the temperature distribution of the build-in LPBF, with absorptivity, material properties, and process conditions as inputs. The molten pool width, length, and depth were determined by comparing the predicted temperature profile with the melting temperature of the material. To validate the proposed method, the predicted molten pool width, and depth of Ti6Al4V were compared with the reported experimental measurements under various process conditions. The predicted molten pool widths were very close to the measured results, and the predictions of molten pool depth were also acceptable. The computational time of the presented model is less than 200s, which shows better computational efficiency than most methods based on numerical iterations, such as the finite element method (FEM). The sensitivity of molten pool width and depth to normalized enthalpy w also discussed. The presented analytical method can be a potential tool for the research of molten pool size and related defects in LPBF. Full article
(This article belongs to the Special Issue Smart Manufacturing and Materials)
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20 pages, 8134 KiB  
Article
Development of a Multi-Sensor Concept for Real-Time Temperature Measurement at the Cutting Insert of a Single-Lip Deep Hole Drilling Tool
by Johannes Ramme, Robert Wegert, Vinzenz Guski, Siegfried Schmauder and Hans-Christian Moehring
Appl. Sci. 2022, 12(14), 7095; https://0-doi-org.brum.beds.ac.uk/10.3390/app12147095 - 14 Jul 2022
Cited by 1 | Viewed by 1292
Abstract
The mechanical energy resulting from cutting processes is turned almost completely in thermal energy, which encourages thermal procedures, such as diffusion, leading to higher wear in the cutting tool and thus to higher temperatures. Furthermore, high temperatures influence the properties of the marginal [...] Read more.
The mechanical energy resulting from cutting processes is turned almost completely in thermal energy, which encourages thermal procedures, such as diffusion, leading to higher wear in the cutting tool and thus to higher temperatures. Furthermore, high temperatures influence the properties of the marginal zones in the workpiece. In this presented work, the in-process temperature of a cutting insert during single-lip deep hole drilling (SLD) is investigated. Therefore, a sensor-integrated tool with resistance temperature detectors (RTD) placed beneath the cutting insert is developed. First, the thermal properties of the cutting insert are adjusted to fit the assembled tool. Afterwards, a CEL-Simulation is obtained to examine the temperature distribution at the cutting edge of the SLD-tool. The temperatures calculated by simulation can be compared to the in-process temperatures of the sensor integrated tool. Because of the usage of a cooling lubricant, simulated temperatures can be varied with a factor to fit the experimentally measured temperature curves. The highest temperature during the process appears at the outer edge of the cutting insert. By knowing the thermal properties, the maximum process temperatures for the deep hole drilling operation are to be calculated. The results represent a contribution to an interdisciplinary research project “Surface Conditioning in Machining Processes” (SPP 2086) of the German Research Foundation (DFG). Full article
(This article belongs to the Special Issue Smart Manufacturing and Materials)
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19 pages, 5179 KiB  
Article
Effect of Process Parameters on Tensile Strength of FDM Printed Carbon Fiber Reinforced Polyamide Parts
by Kenan Muhamedagic, Lucijano Berus, David Potočnik, Ahmet Cekic, Derzija Begic-Hajdarevic, Maida Cohodar Husic and Mirko Ficko
Appl. Sci. 2022, 12(12), 6028; https://0-doi-org.brum.beds.ac.uk/10.3390/app12126028 - 14 Jun 2022
Cited by 12 | Viewed by 2061
Abstract
Reinforcing the polymer with nanoparticles and fibers improves the mechanical, thermal and electrical properties. Owing to this, the functional parts produced by the FDM process of such materials can be used in industrial applications. However, optimal parameters’ selection is crucial to produce parts [...] Read more.
Reinforcing the polymer with nanoparticles and fibers improves the mechanical, thermal and electrical properties. Owing to this, the functional parts produced by the FDM process of such materials can be used in industrial applications. However, optimal parameters’ selection is crucial to produce parts with optimal properties, such as mechanical strength. This paper focuses on the analysis of influential process parameters on the tensile strength of FDM printed parts. Two statistical methods, RSM and ANN, were applied to investigate the effect the layer thickness, printing speed, raster angle and wall thickness on the tensile strength of test specimens printed with a short carbon fiber reinforced polyamide composite. The reduced cubic model was developed by the RSM method, and the correlation between the input parameters and the output response was analyzed by ANOVA. The results show that the layer thickness and raster angle have the most significant influence on tensile strength. As for machine learning, among the nine different tested ANN topologies, the best configuration was found based on the lowest MAE and MSE test sample result. The results show that the proposed model could be a useful tool for predicting tensile strength. Its main advantage is the reduction in time needed for experiments with the LOSO (leave one subject out) k-fold cross validation scheme, offering better generalization ability, given the small set of learning examples. Full article
(This article belongs to the Special Issue Smart Manufacturing and Materials)
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13 pages, 21351 KiB  
Article
Effect of Process Parameters on Distortions Based on the Quantitative Model in the SLM Process
by Sheng Zou, Libao Pang, Chang Xu and Xinyi Xiao
Appl. Sci. 2022, 12(3), 1567; https://0-doi-org.brum.beds.ac.uk/10.3390/app12031567 - 31 Jan 2022
Cited by 9 | Viewed by 2287
Abstract
The selective laser melting (SLM) process provides a more extensive design space and manufacturability. However, it is still hindered by its inaccuracy in dimension and functionality. The distortion in the SLM process affects the dimensional accuracy of the component and may even hinder [...] Read more.
The selective laser melting (SLM) process provides a more extensive design space and manufacturability. However, it is still hindered by its inaccuracy in dimension and functionality. The distortion in the SLM process affects the dimensional accuracy of the component and may even hinder the SLM process. Still, the distortion mechanism has not been well explained; specifically, the effects from the process parameters and scan strategies on the distortion have not been sufficiently investigated. In this study, a quantitative model that considers displacements, plastic strains, and thermal strains on each layer is developed to analyze the distortion mechanism. The distortion is found to be induced by a residual stress gradient among the layers. Then, a transient numerical method calculates residual stress, plastic strain, and distortion in the SLM process. Different simulations with various layers, scanning speeds, stiffness of support structures, and scan strategies are performed to study the relationship between process parameters and distortion. It can be found that the distortion decreases as the height increases. The distortion increases with the scanning speed, reaching the maximum at 700 mm/s and then dropping. We concluded that increasing the stiffness of the support structures is beneficial to reduce the distortion and changing the scanning direction among layers is useless to reduce the distortion. This study gives a theoretical model to analyze the distortion and provides guidance for reducing distortions in the SLM process. Full article
(This article belongs to the Special Issue Smart Manufacturing and Materials)
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18 pages, 3792 KiB  
Article
Modelling and Study of the Effect of Geometrical Parameters of Piezoelectric Plate and Stack
by Tolera G. Degefa, Andrzej Wróbel and Marek Płaczek
Appl. Sci. 2021, 11(24), 11872; https://0-doi-org.brum.beds.ac.uk/10.3390/app112411872 - 14 Dec 2021
Cited by 5 | Viewed by 2002
Abstract
The piezoelectric stack is employed as an actuator and a sensor in a variety of technical applications. The dynamic modelling of piezoelectric plates and stack is used to investigate and search for new applications in mechatronics systems that are based on various loading [...] Read more.
The piezoelectric stack is employed as an actuator and a sensor in a variety of technical applications. The dynamic modelling of piezoelectric plates and stack is used to investigate and search for new applications in mechatronics systems that are based on various loading frequencies. Stacks are composed of series of the same size and whose plates feature the same material properties and are layered by dielectric sheets. This enables increased displacements to be achieved while freeing up more space. The major aim of this study was to investigate the feasibility of using differently modulated piezoelectric plates in a single stack. Mathematical modelling and the study of the characteristics of piezoelectric plates, as well as the stack, with respect to various geometrical parameters, enhances the utilization of the plate in mechatronics systems. The work focuses on the ability of piezoelectric stacks to generate complex vibration spectra comprising numerous frequencies. This is accomplished by utilizing different piezoelectric plates in the stack or by stimulating each plate with a distinct carrier frequency. The plate responses at a wide frequency of piezoelectric plates were investigated using several modeling environments and, finally, experimental findings were obtained. In addition to generating the hypothesis of triggering the plate in a single stack with a varied frequency spectrum, the experiment performed was employed for parameter identification. The experiment demonstrated that it is possible to increase the flexibility of systems by employing piezoelectric stacks as a mode of actuation and that piezo stacks can be used in systems that require precise actuation over a wide frequency range. Full article
(This article belongs to the Special Issue Smart Manufacturing and Materials)
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22 pages, 5487 KiB  
Article
Multiphysics Modeling and Material Selection Methods to Develop Optimal Piezoelectric Plate Actuators for Active Noise Cancellation
by Dessalew Molla, Marek Płaczek and Andrzej Wróbel
Appl. Sci. 2021, 11(24), 11746; https://0-doi-org.brum.beds.ac.uk/10.3390/app112411746 - 10 Dec 2021
Cited by 1 | Viewed by 2117
Abstract
The performance of a piezoelectric actuator for active noise cancellation depends primarily on the quality of the actuator material and its design approach, i.e., single-layer or multi-layer actuators, stacks, benders, or amplified actuators. In this paper, material selection and multiphysics modeling were performed [...] Read more.
The performance of a piezoelectric actuator for active noise cancellation depends primarily on the quality of the actuator material and its design approach, i.e., single-layer or multi-layer actuators, stacks, benders, or amplified actuators. In this paper, material selection and multiphysics modeling were performed to develop an optimal piezoelectric plate actuator for active noise cancellation. The material selection process was analyzed using two multi-criteria decision making (MCDM) approaches for material selection, i.e., figure of merit (FOM) for actuators and the technique for order of performance by similarity to ideal solution (TOPSIS). Of the 12 state-of-the-art piezoelectric actuator materials considered in this article, PMN–28% PT is the best material according to TOPSIS analysis, while PbIn12Nb12O324%−PbMg13Nb13O3−PbTiO3 (PIN24%-PMN-PT) is the best material according to FOM analysis. The ranking of state-of-the-art piezoelectric material categories for actuators according to the two analysis is consistent and the category of monocrystalline piezoelectric materials has the highest actuation performance. The multiphysics modeling was performed using ANSYS Mechanical using two different approaches: one using Ansys Parametric Design Language (APDL) command fragments, the other installing the PiezoAndMEMS ACT extension in ANSYS. Static structure, modal, and harmonic response analyses were performed to determine an optimal pair of piezoelectric plates to be used as an actuator for active noise cancellation. A pair of plates of the same materials, but of different dimensions turns out to be the optimal piezoelectric plate actuator for active noise reduction, according to the two multiphysics modeling methods. Full article
(This article belongs to the Special Issue Smart Manufacturing and Materials)
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19 pages, 14211 KiB  
Article
Methodology of Multicriterial Optimization of Geometric Features of an Orthopedic Implant
by Małgorzata Muzalewska
Appl. Sci. 2021, 11(22), 11070; https://0-doi-org.brum.beds.ac.uk/10.3390/app112211070 - 22 Nov 2021
Cited by 1 | Viewed by 1510
Abstract
The main purpose of the article is to describe the methodology used for multi-criteria optimization of the geometric features of the orthopedic implant used for the reconstruction of the anterior cruciate ligament located in the knee joint. The methodology includes: 1. Method of [...] Read more.
The main purpose of the article is to describe the methodology used for multi-criteria optimization of the geometric features of the orthopedic implant used for the reconstruction of the anterior cruciate ligament located in the knee joint. The methodology includes: 1. Method of development of the bones of the knee joint model; 2. Method of multi-criteria optimization of the geometric features of the orthopedic implant using an artificial immune system, the objective function and the Pareto front; 3. Expert evaluation method based on forms. The work confirmed that the assumed thesis, a multi-criteria optimization using an artificial immune system, which is a specially defined objective function, and the Pareto method, which allows to determine the geometrical features of the implant, will lead to fulfill optimal blood perfusion and sufficient strength properties of the implant simultaneously. We conclude that the described methodology allowed to achieve the optimal geometrical features of the orthopedic implant used for reconstruction of the anterior cruciate ligament located in the knee joint. Full article
(This article belongs to the Special Issue Smart Manufacturing and Materials)
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9 pages, 2949 KiB  
Article
Prediction of Belt Drive Faults in Case of Predictive Maintenance in Industry 4.0 Platform
by Artur Pollak, Sebastian Temich, Wojciech Ptasiński, Jacek Kucharczyk and Damian Gąsiorek
Appl. Sci. 2021, 11(21), 10307; https://0-doi-org.brum.beds.ac.uk/10.3390/app112110307 - 03 Nov 2021
Cited by 15 | Viewed by 2209
Abstract
Continuous production maintenance cost is among one of the highest operational expenses for manufacturing companies. Proper planning of maintenance interventions results in optimized equipment use, higher product quality, and reduced costs. For a belt drive usefulness, it is important that it is properly [...] Read more.
Continuous production maintenance cost is among one of the highest operational expenses for manufacturing companies. Proper planning of maintenance interventions results in optimized equipment use, higher product quality, and reduced costs. For a belt drive usefulness, it is important that it is properly stretched and has no defects. However, manual condition assessment requires a production line stop, which in turn causes production to stop with associated consequences. Continuous fault diagnosis for anomalies is a fundamental step in estimating a component’s remaining service life and then obtaining a reliable predictive maintenance system that reduces production costs. The presented work presents an approach to anomaly detection based on the vibrations obtained from the operation of the belt transmission. Full article
(This article belongs to the Special Issue Smart Manufacturing and Materials)
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17 pages, 3624 KiB  
Article
Frequency Converter as a Node for Edge Computing of Big Data, Related to Drive Efficiency, in Industrial Internet of Things
by Mariusz Piotr Hetmańczyk and Julian Malaka
Appl. Sci. 2021, 11(21), 9784; https://0-doi-org.brum.beds.ac.uk/10.3390/app11219784 - 20 Oct 2021
Viewed by 1288
Abstract
The article presents a method of generating key performance indicators related to electric motor energy efficiency on the basis of Big Data gathered and processed in a frequency converter. The authors proved that using the proposed solution, it is possible to specify the [...] Read more.
The article presents a method of generating key performance indicators related to electric motor energy efficiency on the basis of Big Data gathered and processed in a frequency converter. The authors proved that using the proposed solution, it is possible to specify the relation between the control mode of an electric drive and the control quality-energy consumption ratio in the start-up phase as well as in the steady operation with various mechanical loads. The tests were carried out on a stand equipped with two electric motors (one driving, the other used to apply the load by adjusting the parameters of the built-in brake). The measurements were made in two load cases, for motor control modes available in industrially applied frequency converters (scalar V/f, vector Voltage flux control without encoder, vector voltage flux control with encoder, vector current flux control, and vector current flux control with torque control). During the experiments, values of the current intensities (active and output), the actual frequency value, IxT utilization factor, relative torque, and the current rotational speed were measured and processed. Based on the data, the level of energy efficiency was determined for various control modes. Full article
(This article belongs to the Special Issue Smart Manufacturing and Materials)
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14 pages, 5115 KiB  
Article
Strength Enhancement in Fused Filament Fabrication via the Isotropy Toolpath
by Xinyi Xiao, Byeong-Min Roh and Feng Zhu
Appl. Sci. 2021, 11(13), 6100; https://0-doi-org.brum.beds.ac.uk/10.3390/app11136100 - 30 Jun 2021
Cited by 27 | Viewed by 2559
Abstract
The fused filament fabrication (FFF) process deposits thermoplastic material in a layer-by-layer manner, expanding the design space and manufacturing capability compared with traditional manufacturing. However, the FFF process is inherently directional as the material is deposited in a layer-wise manner. Therefore, the in-plane [...] Read more.
The fused filament fabrication (FFF) process deposits thermoplastic material in a layer-by-layer manner, expanding the design space and manufacturing capability compared with traditional manufacturing. However, the FFF process is inherently directional as the material is deposited in a layer-wise manner. Therefore, the in-plane material cannot reach the isotropy character when performing the tensile test. This would cause the strength of the print components to vary based on the different process planning selections (building orientation, toolpath pattern). The existing toolpaths, primarily used in the FFF process, are linear, zigzag, and contour toolpaths, which always accumulate long filaments and are unidirectional. Thus, this would create difficulties in improving the mechanical strength from the existing toolpath strategies due to the material in-plane anisotropy. In this paper, an in-plane isotropy toolpath pattern is generated to enhance the mechanical strength in the FFF process. The in-plane isotropy can be achieved through continuous deposition while maintaining randomized distribution within a layer. By analyzing the tensile strength on the specimens made by traditional in-plane anisotropy toolpath and the proposed in-plane isotropy toolpath, our results suggest that the mechanical strength can be reinforced by at least 20% using our proposed toolpath strategy in extrusion-based additive manufacturing. Full article
(This article belongs to the Special Issue Smart Manufacturing and Materials)
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