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Applied Sciences
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Computer-Aided Manufacturing and Design
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Computer-Aided Manufacturing and Design

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

Deadline for manuscript submissions: closed (30 April 2020) | Viewed by 41735

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

Special Issue Editors

Prof. Seung-Kyum Choi

E-Mail Website
Guest Editor
G. W. Woodruff School of Mechanical Engineering, Georgia Insitute of Technology, 813 Ferst Drive, Atlanta, GA 30332, USA
Interests: additive manufacturing (AM); printing process; advanced materials; computer-aided design; experimental models; certification; characterization
Special Issues, Collections and Topics in MDPI journals
Dr. Recep M. Gorguluarslan

E-Mail Website
Guest Editor
Department of Mechanical Engineering, TOBB University of Economics and Technology, Ankara, Turkey
Interests: design for additive manufacturing; lightweight lattice materials; topology optimization; solid mechanics; uncertainty quantification; reliability-based design; multiscale modeling; surrogate modeling
Dr. Qi Zhou

grade E-Mail Website
Guest Editor
School of Aerospace Engineering, Huazhong University of Science & Technology, Wuhan 430074, Hubei, China
Interests: metamodel based design; design under uncertainty; robust optimization; multi-fidelity surrogate

Special Issue Information

Dear Colleagues,

Recent advancements in computer technology have allowed for designers to have direct control over the production process thorugh the help of computer-based tools, creating the possibility of a completely integrated design and manufacturing processes.
Over the last few decades, "artificial intelligence" (AI) techniques such as machine learing and deep learning have been topics of interest in computer-based design and manufacturing research fields. However, efforts to develop computer-based AI to handle big data in design and manufacturing have not yet been successful.
This Special Issue of Applied Sciences aims to collect novel articles covering artifical intelligance-based design, manufacturing, and data-driven design. Topics of interest include, but are not strictly limited to the following:

  • The application of artificial intelligence (AI) in Computer Aided Manufacturing and Design;
  • The application of deep learning and machine learning techniques for Computer Aided Manufacturing and Design;
  • Design under uncertainty;
  • Data-driven design;
  • Optimal design for manufacturing;
  • Comparison analysis among several AI techniques applied to Computer Aided Manufacturing and Design;
  • Case studies of the application of AI techniques to mechanical engineering design;
  • Design for advanced manufacturing techniques such as additive manufacturing…

Prof. Seung-Kyum Choi
Dr. Recep M. Gorguluarslan
Dr. Qi Zhou
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • AI
  • airticial intelligence
  • data-driven design
  • computer-aided design
  • computer-aided manfuacturing
  • optimal design
  • optimization
  • uncertainty
  • deep learnig

Published Papers (11 papers)

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Editorial

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2 pages, 147 KiB  
Editorial
Editorial for the Special Issue: Computer-Aided Manufacturing and Design
by Qi Zhou, Seung-Kyum Choi and Recep M. Gorguluarslan
Appl. Sci. 2020, 10(16), 5650; https://doi.org/10.3390/app10165650 - 14 Aug 2020
Cited by 1 | Viewed by 1382
Abstract
Recent advancements in computer technology have allowed designers to have direct control over the production process through the help of computer-based tools, creating the possibility of completely integrated design and manufacturing processes [...] Full article
(This article belongs to the Special Issue Computer-Aided Manufacturing and Design)

Research

Jump to: Editorial

16 pages, 2524 KiB  
Article
Deep Neural Network for Automatic Image Recognition of Engineering Diagrams
by Dong-Yeol Yun, Seung-Kwon Seo, Umer Zahid and Chul-Jin Lee
Appl. Sci. 2020, 10(11), 4005; https://doi.org/10.3390/app10114005 - 09 Jun 2020
Cited by 27 | Viewed by 6373
Abstract
Piping and instrument diagrams (P&IDs) are a key component of the process industry; they contain information about the plant, including the instruments, lines, valves, and control logic. However, the complexity of these diagrams makes it difficult to extract the information automatically. In this [...] Read more.
Piping and instrument diagrams (P&IDs) are a key component of the process industry; they contain information about the plant, including the instruments, lines, valves, and control logic. However, the complexity of these diagrams makes it difficult to extract the information automatically. In this study, we implement an object-detection method to recognize graphical symbols in P&IDs. The framework consists of three parts—region proposal, data annotation, and classification. Sequential image processing is applied as the region proposal step for P&IDs. After getting the proposed regions, the unsupervised learning methods, k-means, and deep adaptive clustering are implemented to decompose the detected dummy symbols and assign negative classes for them. By training a convolutional network, it becomes possible to classify the proposed regions and extract the symbolic information. The results indicate that the proposed framework delivers a superior symbol-recognition performance through dummy detection. Full article
(This article belongs to the Special Issue Computer-Aided Manufacturing and Design)
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23 pages, 6332 KiB  
Article
An Entropy Weight-Based Lower Confidence Bounding Optimization Approach for Engineering Product Design
by Jiachang Qian, Jiaxiang Yi, Jinlan Zhang, Yuansheng Cheng and Jun Liu
Appl. Sci. 2020, 10(10), 3554; https://doi.org/10.3390/app10103554 - 21 May 2020
Cited by 10 | Viewed by 2185
Abstract
The optimization design of engineering products involving computationally expensive simulation is usually a time-consuming or even prohibitive process. As a promising way to relieve computational burden, adaptive Kriging-based design optimization (AKBDO) methods have been widely adopted due to their excellent ability for global [...] Read more.
The optimization design of engineering products involving computationally expensive simulation is usually a time-consuming or even prohibitive process. As a promising way to relieve computational burden, adaptive Kriging-based design optimization (AKBDO) methods have been widely adopted due to their excellent ability for global optimization under limited computational resource. In this paper, an entropy weight-based lower confidence bounding approach (EW-LCB) is developed to objectively make a trade-off between the global exploration and the local exploitation in the adaptive optimization process. In EW-LCB, entropy theory is used to measure the degree of the variation of the predicted value and variance of the Kriging model, respectively. Then, an entropy weight function is proposed to allocate the weights of exploration and exploitation objectively and adaptively based on the values of information entropy. Besides, an index factor is defined to avoid the sequential process falling into the local regions, which is associated with the frequencies of the current optimal solution. To demonstrate the effectiveness of the proposed EW- LCB method, several numerical examples with different dimensions and complexities and the lightweight optimization design problem of an underwater vehicle base are utilized. Results show that the proposed approach is competitive compared with state-of-the-art AKBDO methods considering accuracy, efficiency, and robustness. Full article
(This article belongs to the Special Issue Computer-Aided Manufacturing and Design)
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18 pages, 4370 KiB  
Article
A Coordination Space Model for Assemblability Analysis and Optimization during Measurement-Assisted Large-Scale Assembly
by Zhizhuo Cui and Fuzhou Du
Appl. Sci. 2020, 10(9), 3331; https://doi.org/10.3390/app10093331 - 11 May 2020
Cited by 8 | Viewed by 3004
Abstract
The assembly process is sometimes blocked due to excessive dimension deviations during large-scale assembly. It is inefficient to improve the assembly quality by trial assembly, inspection, and accuracy compensation in the case of excessive deviations. Therefore, assemblability prediction by analyzing the measurement data, [...] Read more.
The assembly process is sometimes blocked due to excessive dimension deviations during large-scale assembly. It is inefficient to improve the assembly quality by trial assembly, inspection, and accuracy compensation in the case of excessive deviations. Therefore, assemblability prediction by analyzing the measurement data, assembly accuracy requirements, and the pose of parts is an effective way to discover the assembly deviations in advance for measurement-assisted assembly. In this paper, a coordination space model is constructed based on a small displacement torsor and assembly accuracy requirements. An assemblability analysis method is proposed to check whether the assembly can be executed directly. Aiming at the incoordination problem, an assemblability optimization method based on the union coordination space is proposed. Finally, taking the space manipulator assembly as an example, the result shows that the proposed method can improve assemblability with a better assembly quality and less workload compared to the least-squares method. Full article
(This article belongs to the Special Issue Computer-Aided Manufacturing and Design)
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19 pages, 5789 KiB  
Article
Research on Optimized Product Image Design Integrated Decision System Based on Kansei Engineering
by Lei Xue, Xiao Yi and Ye Zhang
Appl. Sci. 2020, 10(4), 1198; https://doi.org/10.3390/app10041198 - 11 Feb 2020
Cited by 35 | Viewed by 3642
Abstract
In order to facilitate the development of product image design, the research proposes the optimized product image design integrated decision system based on Kansei Engineering experiment. The system consists of two sub-models, namely product image design qualitative decision model and quantitative decision model. [...] Read more.
In order to facilitate the development of product image design, the research proposes the optimized product image design integrated decision system based on Kansei Engineering experiment. The system consists of two sub-models, namely product image design qualitative decision model and quantitative decision model. Firstly, using the product image design qualitative decision model, the influential design elements for the product image are identified based on Quantification Theory Type I. Secondly, the quantitative decision model is utilized to predict the product total image. Grey Relation Analysis (GRA)–Fuzzy logic sub-models of influential design elements are built up separately. After that, utility optimization model is applied to obtain the multi-objective product image. Finally, the product image design integrated decision system is completed to optimize the product image design in the process of product design. A case study of train seat design is given to demonstrate the analysis results. The train seat image design integrated decision system is constructed to determine the product image. This shows the proposed system is effective and for predicting and evaluating the product image. The results provide meaningful improvement for product image design decision. Full article
(This article belongs to the Special Issue Computer-Aided Manufacturing and Design)
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15 pages, 2454 KiB  
Article
A Part Consolidation Design Method for Additive Manufacturing based on Product Disassembly Complexity
by Samyeon Kim and Seung Ki Moon
Appl. Sci. 2020, 10(3), 1100; https://doi.org/10.3390/app10031100 - 06 Feb 2020
Cited by 32 | Viewed by 6439
Abstract
Parts with complex geometry have been divided into multiple parts due to manufacturing constraints of conventional manufacturing. However, since additive manufacturing (AM) is able to fabricate 3D objects in a layer-by-layer manner, design for AM has been researched to explore AM design benefits [...] Read more.
Parts with complex geometry have been divided into multiple parts due to manufacturing constraints of conventional manufacturing. However, since additive manufacturing (AM) is able to fabricate 3D objects in a layer-by-layer manner, design for AM has been researched to explore AM design benefits and alleviate manufacturing constraints of AM. To explore more AM design benefits, part consolidation has been researched for consolidating multiple parts into fewer number of parts at the manufacturing stage of product lifecycle. However, these studies have been less considered product recovery and maintenance at end-of-life stage. Consolidated parts for the manufacturing stage would not be beneficial at end-of-life stage and lead to unnecessary waste of materials during maintenance. Therefore, in this research, a design method is proposed to consolidate parts for considering maintenance and product recovery at the end-of-life stage by extending a modular identification method. Single part complexity index (SCCI) is introduced to measure part and interface complexities simultaneously. Parts with high SCCI values are grouped into modules that are candidates for part consolidation. Then the product disassembly complexity (PDC) can be used to measure disassembly complexity of a product before and after part consolidation. A case study is performed to demonstrate the usefulness of the proposed design method. The proposed method contributes to guiding how to consolidate parts for enhancing product recovery. Full article
(This article belongs to the Special Issue Computer-Aided Manufacturing and Design)
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20 pages, 3804 KiB  
Article
Integration of Dimension Reduction and Uncertainty Quantification in Designing Stretchable Strain Gauge Sensor
by Sungkun Hwang, Recep M. Gorguluarslan, Hae-Jin Choi and Seung-Kyum Choi
Appl. Sci. 2020, 10(2), 643; https://doi.org/10.3390/app10020643 - 16 Jan 2020
Cited by 6 | Viewed by 2416
Abstract
Interests in strain gauge sensors employing stretchable patch antenna have escalated in the area of structural health monitoring, because the malleable sensor is sensitive to capturing strain variation in any shape of structure. However, owing to the narrow frequency bandwidth of the patch [...] Read more.
Interests in strain gauge sensors employing stretchable patch antenna have escalated in the area of structural health monitoring, because the malleable sensor is sensitive to capturing strain variation in any shape of structure. However, owing to the narrow frequency bandwidth of the patch antenna, the operation quality of the strain sensor is not often assured under structural deformation, which creates unpredictable frequency shifts. Geometric properties of the stretchable antenna also severely regulate the performance of the sensor. Especially rugged substrate created by printing procedure and manual fabrication derives multivariate design variables. Such design variables intensify the computational burden and uncertainties that impede reliable analysis of the strain sensor. In this research, therefore, a framework is proposed not only to comprehensively capture the sensor’s geometric design variables, but also to effectively reduce the multivariate dimensions. The geometric uncertainties are characterized based on the measurements from real specimens and a Gaussian copula is used to represent them with the correlations. A dimension reduction process with a clear decision criterion by entropy-based correlation coefficient dwindles uncertainties that inhibit precise system reliability assessment. After handling the uncertainties, an artificial neural network-based surrogate model predicts the system responses, and a probabilistic neural network derives a precise estimation of the variability of complicated system behavior. To elicit better performance of the stretchable antenna-based strain sensor, a shape optimization process is then executed by developing an optimal design of the strain sensor, which can resolve the issue of the frequency shift in the narrow bandwidth. Compared with the conventional rigid antenna-based strain sensors, the proposed design brings flexible shape adjustment that enables the resonance frequency to be maintained in reliable frequency bandwidth and antenna performance to be maximized under deformation. Hence, the efficacy of the proposed design framework that employs uncertainty characterization, dimension reduction, and machine learning-based behavior prediction is epitomized by the stretchable antenna-based strain sensor. Full article
(This article belongs to the Special Issue Computer-Aided Manufacturing and Design)
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15 pages, 2941 KiB  
Article
Data-Driven Design Solution of a Mismatch Problem between the Specifications of the Multi-Function Console in a Jangbogo Class Submarine and the Anthropometric Dimensions of South Koreans Users
by Jihwan Lee, Namwoo Cho, Myung Hwan Yun and Yushin Lee
Appl. Sci. 2020, 10(1), 415; https://doi.org/10.3390/app10010415 - 06 Jan 2020
Cited by 4 | Viewed by 3862
Abstract
The naval multi-function console provides various types of information to the operator. It is equipment that is key for submarine navigation, and fatal human errors can occur due to the mismatch between the console specifications and the operator’s body size. This study proposes [...] Read more.
The naval multi-function console provides various types of information to the operator. It is equipment that is key for submarine navigation, and fatal human errors can occur due to the mismatch between the console specifications and the operator’s body size. This study proposes a method for deriving console specifications suitable for the body size of Korean users. The seat height, seat width, seat depth, upper edge of backrest, and worktable height were selected as the target design variables. Using six anthropometric dimensions, a mismatch equation for each target design variable was developed. Anthropometric measures of 2027 Korean males were obtained, and the optimal specifications of the console were derived via an algorithmic approach. As a result, the match rate, considering all the target design variables, was improved from 2.57% to 76.96%. In previous studies and standards, the optimal console specifications were suggested based on the anthropometric data of a specific percentile of users, and it was impossible to quantitatively confirm the suitability of the console design for the target users. However, the method used in this study calculated the match rate using the mismatch equation devised for comfortable use of the console and a large amount of anthropometric data that represented the user population, and therefore the improvement effect of the recommended specification can be directly identified when compared to the current specifications. Moreover, the methodology and results of this study could be used for deciding the specifications of multi-function consoles in several fields, including nuclear power plants or disaster situation rooms. Full article
(This article belongs to the Special Issue Computer-Aided Manufacturing and Design)
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25 pages, 8842 KiB  
Article
An Intelligent CFD-Based Optimization System for Fluid Machinery: Automotive Electronic Pump Case Application
by Qiaorui Si, Rong Lu, Chunhao Shen, Shuijing Xia, Guochen Sheng and Jianping Yuan
Appl. Sci. 2020, 10(1), 366; https://doi.org/10.3390/app10010366 - 03 Jan 2020
Cited by 19 | Viewed by 4856
Abstract
Improving the efficiency of fluid machinery is an eternal topic, and the development of computational fluid dynamics (CFD) technology provides an opportunity to achieve optimal design in limited time. A multi-objective design process based on CFD and an intelligent optimization method is proposed [...] Read more.
Improving the efficiency of fluid machinery is an eternal topic, and the development of computational fluid dynamics (CFD) technology provides an opportunity to achieve optimal design in limited time. A multi-objective design process based on CFD and an intelligent optimization method is proposed in this study to improve the energy transfer efficiency, using the application of an automotive electronic pump as an example. Firstly, the three-dimensional CFD analysis of the prototype is carried out to understand the flow loss mechanism inside the pump and establish the numerical prediction model of pump performance. Secondly, an automatic optimization platform including fluid domain modeling, meshing, solving, post-processing, and design of experiment (DOE) is built based on three-dimensional parametric design method. Then, orthogonal experimental design and the multi-island genetic algorithm (MIGA) are utilized to drive the platform for improving the efficiency of the pump at three operating flowrates. Finally, the optimal impeller geometries are obtained within the limited 375 h and manufactured into a prototype for verification test. The results show that the highest efficiency of the pump increased by 4.2%, which verify the effectiveness of the proposed method. Overall, the flow field has been improved significantly after optimization, which is the fundamental reason for performance improvement. Full article
(This article belongs to the Special Issue Computer-Aided Manufacturing and Design)
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17 pages, 10121 KiB  
Article
Integrated Optimum Layout of Conformal Cooling Channels and Optimal Injection Molding Process Parameters for Optical Lenses
by Chen-Yuan Chung
Appl. Sci. 2019, 9(20), 4341; https://doi.org/10.3390/app9204341 - 15 Oct 2019
Cited by 26 | Viewed by 4446
Abstract
Plastic lenses are light and can be mass-produced. Large-diameter aspheric plastic lenses play a substantial role in the optical industry. Injection molding is a popular technology for plastic optical manufacturing because it can achieve a high production rate. Highly efficient cooling channels are [...] Read more.
Plastic lenses are light and can be mass-produced. Large-diameter aspheric plastic lenses play a substantial role in the optical industry. Injection molding is a popular technology for plastic optical manufacturing because it can achieve a high production rate. Highly efficient cooling channels are required for obtaining a uniform temperature distribution in mold cavities. With the recent advent of laser additive manufacturing, highly efficient three-dimensional spiral channels can be realized for conformal cooling technique. However, the design of conformal cooling channels is very complex and requires optimization analyses. In this study, finite element analysis is combined with a gradient-based algorithm and robust genetic algorithm to determine the optimum layout of cooling channels. According to the simulation results, the use of conformal cooling channels can reduce the surface temperature difference of the melt, ejection time, and warpage. Moreover, the optimal process parameters (such as melt temperature, mold temperature, filling time, and packing time) obtained from the design of experiments improved the fringe pattern and eliminated the local variation of birefringence. Thus, this study indicates how the optical properties of plastic lenses can be improved. The major contribution of present proposed methods can be applied to a mold core containing the conformal cooling channels by metal additive manufacturing. Full article
(This article belongs to the Special Issue Computer-Aided Manufacturing and Design)
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12 pages, 1324 KiB  
Article
Product Service System Availability Improvement through Field Repair Kit Optimization: A Case Study
by Eun Suk Suh
Appl. Sci. 2019, 9(20), 4272; https://doi.org/10.3390/app9204272 - 12 Oct 2019
Cited by 7 | Viewed by 1955
Abstract
Product service system (PSS) is becoming a popular business model, where companies offer product based service to customers to realize steady recurring revenue. However, to provide PSS-based service to customers in reliable way, PSS need to be supplemented with a field repair kit [...] Read more.
Product service system (PSS) is becoming a popular business model, where companies offer product based service to customers to realize steady recurring revenue. However, to provide PSS-based service to customers in reliable way, PSS need to be supplemented with a field repair kit onsite, in case of parts failure and PSS shutdown. The field repair kit consists of frequently used spare parts in multiple quantities. However, mismatch in spare parts type and quantities in the field repair kit will results in sub-par performance of PSS for both customer and company. In this paper, a case study involving industrial PSS repair kit optimization is presented. In the case study, the field repair kit for complex industrial printing system is cost optimized, while satisfying the system availability requirement, specified by the maintenance contract between the company and the customer. Key analysis steps and results are presented to offer insight into the PSS field repair kit optimization, offering useful references to industrial practitioners. Full article
(This article belongs to the Special Issue Computer-Aided Manufacturing and Design)
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