Research

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15 pages, 5728 KiB

Open AccessArticle

A Decoupling Algorithm-Based Technology for Predicting and Regulating the Unbalance of Aircraft Rotor Assembly Considering Manufacturing Errors

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Machines 2023, 11(10), 970; https://doi.org/10.3390/machines11100970 - 18 Oct 2023

Viewed by 584

Abstract

Rotor unbalance is the most important factor affecting the dynamic performance of aircraft engines. The existing unbalance prediction and control methods are insufficient for multi-stage rotors. The post-assembly unbalance of rotors in aircraft engines is a critical factor affecting their dynamic performance. In [...] Read more.

Rotor unbalance is the most important factor affecting the dynamic performance of aircraft engines. The existing unbalance prediction and control methods are insufficient for multi-stage rotors. The post-assembly unbalance of rotors in aircraft engines is a critical factor affecting their dynamic performance. In order to predict and reduce the unbalance of multi-stage rotors after assembly, this paper establishes a measurement model for the center-of-mass offset of aircraft engine rotors through decoupled calculations of the unbalance. Furthermore, it constructs an unbalance prediction model using the spatial transfer mechanism of combined rotor offset centers under the influence of manufacturing errors. Additionally, a method for measuring rotor unbalance during the assembly phase is proposed. The experimental results of the unbalance in multi-stage combined rotor assembly indicate that the degree of agreement between the predicted results and the experimental results is 91.3%, resulting in a reduction in the mean error of 15.3% compared to before the correction. The study also investigates the impact of manufacturing errors on unbalance. This research provides robust support for controlling the unbalance in multi-stage combined rotor assembly. Full article

(This article belongs to the Special Issue 10th Anniversary of Machines—Feature Papers in Advanced Manufacturing)

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19 pages, 6137 KiB

Open AccessArticle

Tool Wear Monitoring Based on the Gray Wolf Optimized Variational Mode Decomposition Algorithm and Hilbert–Huang Transformation in Machining Stainless Steel

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Machines 2023, 11(8), 806; https://doi.org/10.3390/machines11080806 - 06 Aug 2023

Viewed by 607

Abstract

The online monitoring and prediction of tool wear are important to maintain the stability of machining processes. In most cases, the tool wear condition can be evaluated by signals such as force, sound, vibration, and temperature, which are often processed via Fourier-transform based [...] Read more.

The online monitoring and prediction of tool wear are important to maintain the stability of machining processes. In most cases, the tool wear condition can be evaluated by signals such as force, sound, vibration, and temperature, which are often processed via Fourier-transform based methods, typically, the short-time Fourier transform (STFT). However, the fixed-width window function in STFT has many limitations. In this paper, a novel tool wear monitoring method based on variational mode decomposition (VMD) and Hilbert–Huang transformation (HHT) were developed to monitor the wear of carbide tools in machining stainless steel. In this method, the intrinsic mode function (IMF) was used as the fitness function, and the (K alpha) parameter sets for VMD were optimized by the gray wolf optimization (GWO). The results show that the characteristic frequency in the GWO-VMD-HHT method is more significant with no aliasing compared with the EMD-HHT method, and an obvious characteristic frequency shift phenomenon is present. By utilizing the energy value of IMF₃ as the feature to classify the wear state of the cutting tool, the increase of energy reached 85.48% when 260–315 milling passes were in severe wear state. GWO, which can accurately find the best parameters for VMD, not only solves the problem that the Entropy Function is not suitable for force signals, but also provides reference for the selection of parameters of VMD. Full article

(This article belongs to the Special Issue 10th Anniversary of Machines—Feature Papers in Advanced Manufacturing)

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12 pages, 24388 KiB

Open AccessEditor’s ChoiceArticle

Design, Realization, and Test of Ultraviolet-C LED Arrays Suitable for Long-Lasting Irradiation of Biological Samples

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Machines 2023, 11(8), 792; https://doi.org/10.3390/machines11080792 - 01 Aug 2023

Viewed by 505

Abstract

We present the electrical and optical design, assembling, and thorough experimental characterization of two compact arrays of short-wavelength ultraviolet (UV-C) light-emitting diodes (LEDs) suitable for near-field irradiation. Through a combination of technical expedients, we have achieved effective thermal management such that long-lasting irradiations [...] Read more.

We present the electrical and optical design, assembling, and thorough experimental characterization of two compact arrays of short-wavelength ultraviolet (UV-C) light-emitting diodes (LEDs) suitable for near-field irradiation. Through a combination of technical expedients, we have achieved effective thermal management such that long-lasting irradiations are possible without appreciable deterioration of UV-C emission. We successfully used these compact UV-C LED arrays for long lasting irradiation tests aimed at generating the biosynthesis of defensive metabolites that enhance the resistance of plants and fruits to pathogen attacks. Finally, we comment on the possibility of implementing these compact UV-C sources on robotic systems to make an automated device suitable to reduce pesticide use in agricultural crops. Full article

(This article belongs to the Special Issue 10th Anniversary of Machines—Feature Papers in Advanced Manufacturing)

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22 pages, 7117 KiB

Open AccessArticle

Turning Chatter Detection Using a Multi-Input Convolutional Neural Network via Image and Sound Signal

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Van Thanh Tien Nguyen

Machines 2023, 11(6), 644; https://doi.org/10.3390/machines11060644 - 13 Jun 2023

Cited by 2 | Viewed by 903

Abstract

In mechanical cutting and machining, self-excited vibration known as “Chatter” often occurs, adversely affecting a product’s quality and tool life. This article proposes a method to identify chatter by applying a machine learning model to classify data, determining whether the machining process is [...] Read more.

In mechanical cutting and machining, self-excited vibration known as “Chatter” often occurs, adversely affecting a product’s quality and tool life. This article proposes a method to identify chatter by applying a machine learning model to classify data, determining whether the machining process is stable or vibrational. Previously, research studies have used detailed surface image data and sound generated during the machining process. To increase the specificity of the research data, we constructed a two-input model that enables the inclusion of both acoustic and visual data into the model. Data for training, testing, and calibration were collected from machining flanges SS400 in the form of thin steel sheets, using electron microscopes for imaging and microphones for sound recording. The study also compares the accuracy of the two-input model with popular models such as a visual geometry group network (VGG16), residual network (Restnet50), dense convolutional network (DenseNet), and Inception network (InceptionNet). The results show that the DenseNet model has the highest accuracy of 98.8%, while the two-input model has a 98% higher accuracy than other models; however, the two-input model is more appreciated due to the generality of the input data of the model. Experimental results show that the recommended model has good results in this work. Full article

(This article belongs to the Special Issue 10th Anniversary of Machines—Feature Papers in Advanced Manufacturing)

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21 pages, 11410 KiB

Open AccessArticle

Effects of Tooth Modification in the Involute Helical Gear Form-Grinding Process on Loaded Transmission Character with Consideration of Tooth Axial Inclination Error

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Machines 2023, 11(2), 305; https://doi.org/10.3390/machines11020305 - 17 Feb 2023

Cited by 1 | Viewed by 1272

Abstract

Due to the existence of machining and installation errors, axis parallelism error of gear pairs occurs, which causes eccentric load and mesh in-out impact, thus weakening loaded transmission character. To solve this problem, the axis parallelism error of gear pairs was equated with [...] Read more.

Due to the existence of machining and installation errors, axis parallelism error of gear pairs occurs, which causes eccentric load and mesh in-out impact, thus weakening loaded transmission character. To solve this problem, the axis parallelism error of gear pairs was equated with tooth axial inclination error based on the gear-meshing principle. On this basis, we established the tooth modification model with tooth axial inclination error as the variable according to involute helical gear form-grinding process. Then, the degradation of loaded transmission character caused by axis parallelism error of gear pairs was quantitatively analyzed. The gear grinding, gear measuring, and gearbox vibration measuring were, respectively, performed on high-precision CNC horizontal gear form-grinding machine tool L300G, Gleason 350 GMS, and JWY-II multifunctional gearbox loading test bench. The results show that the proposed method can effectively reduce eccentric load and mesh in-out impact and significantly improve loaded transmission character. Therefore, it can provide a theoretical and experimental basis for the research of high-performance gear-grinding technology of gear-grinder machines. Full article

(This article belongs to the Special Issue 10th Anniversary of Machines—Feature Papers in Advanced Manufacturing)

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19 pages, 4039 KiB

Open AccessArticle

zPasteurAIzer: An AI-Enabled Solution for Product Quality Monitoring in Tunnel Pasteurization Machines

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Samuel Olaiya Afolaranmi

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Stefanos H. Panagiotou

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Konstantinos Timpilis

Machines 2023, 11(2), 191; https://doi.org/10.3390/machines11020191 - 01 Feb 2023

Viewed by 1276

Abstract

In the food and beverage industry, many foods, beers, and soft drinks need to be pasteurized in order to minimize the effect of micro-organisms on the physical stability, quality, and flavour of the product. Although modern tunnel pasteurizers provide integrated solutions for precise [...] Read more.

In the food and beverage industry, many foods, beers, and soft drinks need to be pasteurized in order to minimize the effect of micro-organisms on the physical stability, quality, and flavour of the product. Although modern tunnel pasteurizers provide integrated solutions for precise process monitoring and control, a great number of packaging plants continue to operate with legacy pasteurizers that require irregular manual measurements to be performed by shop floor operators in order to monitor the process. In this context, the present paper presents zPasteurAIzer, an end-to-end system that provides real-time quality monitoring for legacy tunnel pasteurization machines and constitutes a low-cost alternative to replacement or the upgrading of installed equipment by leveraging IoT technologies and AI-enabled virtual sensing techniques. We share details on the design and implementation of the system, which is based on a microservice-oriented architecture and includes functionalities such as configuration of the pasteurizer machine, data acquisition, and preprocessing methodology as well as machine learning-based estimation and live dashboard monitoring of the process parameters. Experimental work has been conducted in a real-world use case at a large brewing manufacturing plant in Greece, and the results indicate the value and potential of the proposed system. Full article

(This article belongs to the Special Issue 10th Anniversary of Machines—Feature Papers in Advanced Manufacturing)

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15 pages, 6076 KiB

Open AccessArticle

Application of Flowsheet Simulation Methodology to Improve Productivity and Sustainability of Porcelain Tile Manufacturing

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Carine Lourenco Alves

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Vasyl Skorych

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Agenor De Noni Jr.

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Dachamir Hotza

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Sergio Yesid Gómez González

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Stefan Heinrich

Machines 2023, 11(2), 137; https://doi.org/10.3390/machines11020137 - 19 Jan 2023

Viewed by 1718

Abstract

Porcelain tile manufacturing is an energy-intensive industry that is in dire need of increasing productivity, minimizing costs, and reducing CO₂ emissions, while keeping the product quality intact to remain competitive in today’s environment. In this contribution, alternative processing parameters for the porcelain [...] Read more.

Porcelain tile manufacturing is an energy-intensive industry that is in dire need of increasing productivity, minimizing costs, and reducing CO₂ emissions, while keeping the product quality intact to remain competitive in today’s environment. In this contribution, alternative processing parameters for the porcelain tile production sequence were proposed based on simulation-based process optimization. Flowsheet simulations in the Dyssol framework were used to study the impact of the milling and firing process parameters on the electrical and thermal energy consumption, final product quality, and productivity of the entire processing sequence. For this purpose, a new model of gas flow consumption in the sintering stage was proposed and implemented. During optimization, the primary condition was to maintain the product quality by keeping the final open porosity of the tile within the specified industrial range. The proposed simulation methodology proved to be effective in predicting the influence of the processing parameters on the intermediate and final products of the manufacturing sequence, as well as in estimating the production costs for the Brazilian and Spanish economic conditions. This approach has shown great potential to promote digitalization and establish digital twins in ceramic tile manufacturing for further in-line process control. Full article

(This article belongs to the Special Issue 10th Anniversary of Machines—Feature Papers in Advanced Manufacturing)

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19 pages, 888 KiB

Open AccessArticle

A Digital Twin Model of Three-Dimensional Shading for Simulation of the Ironmaking Process

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Yongxiang Lei

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Hamid Reza Karimi

Machines 2022, 10(12), 1122; https://doi.org/10.3390/machines10121122 - 27 Nov 2022

Cited by 1 | Viewed by 1266

Abstract

Advanced manufacturing is a new trend for sustainable industrial development, and digital twin is a new technology that has attracted attention. Blast furnace smelting is an effective method in the manufacturing of iron and steel. Comprehensive and dependable surveillance of the blast furnace [...] Read more.

Advanced manufacturing is a new trend for sustainable industrial development, and digital twin is a new technology that has attracted attention. Blast furnace smelting is an effective method in the manufacturing of iron and steel. Comprehensive and dependable surveillance of the blast furnace smelting process is essential for ensuring the smooth operation and improving of iron and steel output quality. The current technology makes it difficult to monitor the entire process of blast furnace ironmaking. Based on Unity 3D, this study presents a digital-twin virtual reality simulation system of blast furnace ironmaking. First, shading modeling creates a three-dimensional dynamic geometric model in different ironmaking system scenarios. Then, we script the animation and call particle system according to the motion mode of distinct geometric objects to give the dynamic effect of geometric objects. Shaders are the focus of the design and contributions. In addition, shader optimization technology can reduce hardware resource consumption and increase system fluency. Vertex shaders are used for all types of coordinate space transformation and vertex output; fragment shaders are used for texture sampling, light model calculation, normal calculation, noise superposition, and color output. The shader rendering technique allows for more realistic lighting effects. The presented dynamic digital twin system implements more realistic lighting analyzed in the ironmaking process. Virtual interaction logic’s design and deployment process is based on HTC VIVE hardware and VRTK toolkit. In the actual simulation process, the typical animation frame rate is stable at about 75 FPS (frames per second). The simulation system runs smoothly and a cutting-edge and state-of-the-art method for observing the blast furnace ironmaking process is suggested. Full article

(This article belongs to the Special Issue 10th Anniversary of Machines—Feature Papers in Advanced Manufacturing)

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19 pages, 1473 KiB

Open AccessArticle

A Nonlinear Control of Linear Slider Considering Position Dependence of Interlinkage Flux

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Tomoya Hoshina

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Mingcong Deng

Machines 2022, 10(7), 522; https://doi.org/10.3390/machines10070522 - 27 Jun 2022

Cited by 2 | Viewed by 1082

Abstract

Linear sliders are linear actuators using linear motors. It is used in many applications, such as factory lines and linear motor cars. In recent years, the demand for smaller semiconductor devices has been increasing due to the proliferation of smartphones. High-precision positioning of [...] Read more.

Linear sliders are linear actuators using linear motors. It is used in many applications, such as factory lines and linear motor cars. In recent years, the demand for smaller semiconductor devices has been increasing due to the proliferation of smartphones. High-precision positioning of linear motors is needed because manufacturing semiconductor devices uses the stage with linear motors. However, linear motors have nonlinearity due to the position dependence of interlinkage flux. It affects precise positioning. In this study, the nonlinear characteristics due to the position dependence of the flux are expressed as a mathematical model by using a distributed constant magnetic circuit. A method compensating it using an operator-based feedback controller with the obtained mathematical model is proposed. The effectiveness of the proposed method is confirmed by simulating and experimenting with the reference following disturbance elimination. Full article

(This article belongs to the Special Issue 10th Anniversary of Machines—Feature Papers in Advanced Manufacturing)

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22 pages, 8422 KiB

Open AccessArticle

Developing a Novel Fully Automated Concept to Produce Bowden Cables for the Automotive Industry

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Vitor Fernando Crespim Sousa

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Francisco José Gomes da Silva

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Raul Duarte Salgueiral Gomes Campilho

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Arnaldo Guedes Pinto

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Luís Pinto Ferreira

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Nuno Martins

Machines 2022, 10(5), 290; https://doi.org/10.3390/machines10050290 - 21 Apr 2022

Cited by 3 | Viewed by 1756

Abstract

The automotive industry is one of the driving forces of the global industry; thus, it is a very competitive sector which creates a constant need for process improvement, regarding productivity, quality, and flexibility. Automation has proven to be a viable solution for these [...] Read more.

The automotive industry is one of the driving forces of the global industry; thus, it is a very competitive sector which creates a constant need for process improvement, regarding productivity, quality, and flexibility. Automation has proven to be a viable solution for these production problems, with the rising adoption of these automated system by companies that try to design and implement more flexible systems, while reducing costs and improving process quality. Furthermore, the use of automation reduces the manpower factor and its associated variability. In the present work, a new concept for a Bowden cable production process is presented by employing the design science research (DSR) methodology. The project starts with the analysis of the previous production concept, determining possible problems and improvements, as well as setting objectives/requirements for a possible new concept/equipment. This information was used to develop a new automated Bowden cable production equipment, implementing several changes to the old concept and filling a gap in the literature in this field. The developed system was implemented and tested. A considerable reduction in cycle time was registered by 25%, which resulted in an increase of 30% in process productivity. Full article

(This article belongs to the Special Issue 10th Anniversary of Machines—Feature Papers in Advanced Manufacturing)

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Review

Jump to: Research

33 pages, 5641 KiB

Open AccessReview

A Review of Electrode Manufacturing Methods for Electrical Discharge Machining: Current Status and Future Perspectives for Surface Alloying

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Elhuseini Garba

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Ahmad Majdi Abdul-Rani

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Nurul Azhani Yunus

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Abdul Azeez Abdu Aliyu

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Iqtidar Ahmed Gul

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Md Al-Amin

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Ruwaida Aliyu

Machines 2023, 11(9), 906; https://doi.org/10.3390/machines11090906 - 12 Sep 2023

Viewed by 939

Abstract

In electrical discharge machining (EDM), the tool electrode is one of the substantial components of the system, and it ensures the success or failure of the EDM process. The electrode’s role is to conduct electrical charges and erode the workpiece to the desired [...] Read more.

In electrical discharge machining (EDM), the tool electrode is one of the substantial components of the system, and it ensures the success or failure of the EDM process. The electrode’s role is to conduct electrical charges and erode the workpiece to the desired shape. Different electrode materials have different impacts on machining. Certain electrode materials remove metal quickly but wear out rapidly, while others degrade slowly but the material removal is too slow. The choice of the electrode has an influence on both the mechanical properties, such as metal removal rate (MRR), wear rate, surface finish, surface modification and machinability, and the electrical properties, such as sparking initiation, time lag, gap contamination and process stability. There are factors to consider when fabricating an electrode, which include the type of workpiece materials, the metallurgical alloying of the materials, the choice of fabrication techniques, the intended use of the electrode, and material cost. Considerable challenges in EDM electrode fabrication have been reported, which include excessive tool wear for green compact electrodes, high toughness for sintered electrodes, and poor rigidity for additively manufactured electrodes. To address these issues, researchers have explored different manufacturing methods, such as casting, conventional machining, electrodeposition, powder metallurgy and additive manufacturing. In this paper, the various techniques attempted and adopted in EDM electrode manufacturing are analyzed and discussed. This paper also sought to give insight into EDM, its various forms, the dielectric fluid’s properties, EDM electrode’s size and shape, the effects of the electrode on the EDM process, material removal, electrode wear, present technologies for electrode fabrication, and the limitations of these technologies. Finally, directions for future research are highlighted. Full article

(This article belongs to the Special Issue 10th Anniversary of Machines—Feature Papers in Advanced Manufacturing)

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20 pages, 2767 KiB

Open AccessReview

A Brief Review of Computational Product Design: A Brand Identity Approach

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Athanasios Manavis

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Konstantinos Kakoulis

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Panagiotis Kyratsis

Machines 2023, 11(2), 232; https://doi.org/10.3390/machines11020232 - 04 Feb 2023

Cited by 1 | Viewed by 2032

Abstract

On the way to designing customized products as one of the core activities of Industry 4.0, the strategy of computational design emerges as a unique design process due to its flexibility and simplicity. More specifically, the aforementioned strategy is concerned with the study [...] Read more.

On the way to designing customized products as one of the core activities of Industry 4.0, the strategy of computational design emerges as a unique design process due to its flexibility and simplicity. More specifically, the aforementioned strategy is concerned with the study of brand identity and its description in the development of commercial industrial products. The proposed design approach is focused on the study of branded product forms following computational design methodologies, i.e., employing textual or/and visual programming languages. The paper presents an overview of in-depth research studies which deal with the systematic way of creation, evolution, and transformation of industrial products with modern digital tools. Through the review, 100 studies have been analyzed over the last 15 years. The background of this research includes definitions from the specific four pillars of the modern theory of industrial design, e.g., product design, digital design, visual representation, and product identity. Furthermore, the current paper combines the use of computational design with specific parameters of visual brand elements in order to develop a methodological tool for the mass customization of industrial products. Moreover, the proposed framework offers a great deal of flexibility in both design and manufacturing, while many design alternatives could become available in a very short time. Finally, the impact of this paper is the correlation between computational design techniques and the theoretical background of brand identity principles (i.e., shapes, geometries, styles, textures, colors, and materials) for inspiring novel ideas among engineers, designers, and marketers. Full article

(This article belongs to the Special Issue 10th Anniversary of Machines—Feature Papers in Advanced Manufacturing)

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