Most modern digital approaches to engineering are based on models and their model transformations. Most of these model transformations are mathematically speaking non-bijective mappings — so-called projections — where some information of the original model is lost during the mapping. From a theoretical point of view it is therefore of great interest to exactly examine the properties of these model transformations. In this paper at first the characteristics of a model are briefly explained. Then some of the most common model-based engineering approaches are reviewed and compared regarding their models and model transformations. In this examination the missing existence of an inverse transformation (a so-called text-to-model transformation, T2M) of a typical model transformation (a so-called model-to-text transformation, M2T) is identified. That discovery may well hold the key to the realization of a so-called round-trip engineering. The required existence of the inverse transformation to this round-trip engineering is then generically postulated as having the nature of a pattern recognition problem. For illustration purposes and a better understanding of the interpretation of the inverse transformation as a pattern recognition problem, a case study for the reconstruction of an abstract model from the concrete model is given using CAD-Data of a satellite. Since CAD models belong to geometry, dimensionless geometric moment invariants play a key role in the generic solution of the pattern recognition problem contained in this example.
{"title":"From Model-Driven Architecture and Model-Based Systems Engineering via Formal Concept Analysis to Graph-Based Design Languages and Back: A Scientific Discourse","authors":"Dominik Schopper, S. Rudolph","doi":"10.1115/DETC2018-86392","DOIUrl":"https://doi.org/10.1115/DETC2018-86392","url":null,"abstract":"Most modern digital approaches to engineering are based on models and their model transformations. Most of these model transformations are mathematically speaking non-bijective mappings — so-called projections — where some information of the original model is lost during the mapping. From a theoretical point of view it is therefore of great interest to exactly examine the properties of these model transformations. In this paper at first the characteristics of a model are briefly explained. Then some of the most common model-based engineering approaches are reviewed and compared regarding their models and model transformations. In this examination the missing existence of an inverse transformation (a so-called text-to-model transformation, T2M) of a typical model transformation (a so-called model-to-text transformation, M2T) is identified. That discovery may well hold the key to the realization of a so-called round-trip engineering. The required existence of the inverse transformation to this round-trip engineering is then generically postulated as having the nature of a pattern recognition problem. For illustration purposes and a better understanding of the interpretation of the inverse transformation as a pattern recognition problem, a case study for the reconstruction of an abstract model from the concrete model is given using CAD-Data of a satellite. Since CAD models belong to geometry, dimensionless geometric moment invariants play a key role in the generic solution of the pattern recognition problem contained in this example.","PeriodicalId":338721,"journal":{"name":"Volume 1B: 38th Computers and Information in Engineering Conference","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121389922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xuyue Yin, X. Fan, Jiajie Wang, Rui Liu, Qiang Wang
Assembly process of complex electromechanical products can be quite complicated and time consuming because of high quality demands. Aiming at improving the efficiency of the manual assembly process, this paper proposes an automatic interaction method using part recognition for augmented reality (AR) assembly guidance, which improves both the accuracy of part picking and the interaction efficiency of AR guidance system. Taking sample images of similar parts as input and part types as output, a deep neural network model Part R-CNN for part recognition is build based on Faster R-CNN and is further fine-tuned by back propagation. By recognizing the assembly part, the augmented assembly guidance information of the corresponding parts assembly process is triggered in real-time without direct user interaction. Experimental results show that the deep neural network based part recognition method reaches 94% on mean average precision and the average recognition speed is 200ms per image frame. The average speed of AR guidance content triggering is about 20fps. All system performance satisfies the accuracy and real-time requirements of the AR-aided assembly system.
{"title":"An Automatic Interaction Method Using Part Recognition Based on Deep Network for Augmented Reality Assembly Guidance","authors":"Xuyue Yin, X. Fan, Jiajie Wang, Rui Liu, Qiang Wang","doi":"10.1115/DETC2018-85810","DOIUrl":"https://doi.org/10.1115/DETC2018-85810","url":null,"abstract":"Assembly process of complex electromechanical products can be quite complicated and time consuming because of high quality demands. Aiming at improving the efficiency of the manual assembly process, this paper proposes an automatic interaction method using part recognition for augmented reality (AR) assembly guidance, which improves both the accuracy of part picking and the interaction efficiency of AR guidance system. Taking sample images of similar parts as input and part types as output, a deep neural network model Part R-CNN for part recognition is build based on Faster R-CNN and is further fine-tuned by back propagation. By recognizing the assembly part, the augmented assembly guidance information of the corresponding parts assembly process is triggered in real-time without direct user interaction. Experimental results show that the deep neural network based part recognition method reaches 94% on mean average precision and the average recognition speed is 200ms per image frame. The average speed of AR guidance content triggering is about 20fps. All system performance satisfies the accuracy and real-time requirements of the AR-aided assembly system.","PeriodicalId":338721,"journal":{"name":"Volume 1B: 38th Computers and Information in Engineering Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130320888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the intensification of international competition and diversification of customer tastes, the concept design and architectural design contributing to the function and products of the appearance shape has become an important issue in product development. Therefore, in addition to the manufacturing technology supported by high quality and high performance, the establishment of delight value-added manufacturing technology is required. In recent years, delight design has been attracting attention to create a design that enhances customer satisfaction. Delight design means a design with attractive quality, in addition to the conventional performance quality and must-be quality. However, attractive quality depends on the quality of the designer. Moreover, it is difficult to define such a concept because it is considered to exist in a state similar to an idea, which means that it is vague and difficult to express. Therefore, in this study, we propose a method of constructing a neural network customer value model that creates a product design from KANSEI using customer KANSEI data. Additionally, we propose a method of constructing a neural network customer evaluation model as the inverse model. The customer evaluation model analyzes the KANSEI of individual customers and creates a delight design, which is more appealing to an individual customer. In this study, this proposed method was applied to the side shape of a car’s body and the shape of a beer cup.
{"title":"Method of Emerging Delight Design Based on KANSEI","authors":"Y. Tanaka, H. Aoyama","doi":"10.1115/DETC2018-85736","DOIUrl":"https://doi.org/10.1115/DETC2018-85736","url":null,"abstract":"With the intensification of international competition and diversification of customer tastes, the concept design and architectural design contributing to the function and products of the appearance shape has become an important issue in product development. Therefore, in addition to the manufacturing technology supported by high quality and high performance, the establishment of delight value-added manufacturing technology is required. In recent years, delight design has been attracting attention to create a design that enhances customer satisfaction. Delight design means a design with attractive quality, in addition to the conventional performance quality and must-be quality. However, attractive quality depends on the quality of the designer. Moreover, it is difficult to define such a concept because it is considered to exist in a state similar to an idea, which means that it is vague and difficult to express.\u0000 Therefore, in this study, we propose a method of constructing a neural network customer value model that creates a product design from KANSEI using customer KANSEI data. Additionally, we propose a method of constructing a neural network customer evaluation model as the inverse model. The customer evaluation model analyzes the KANSEI of individual customers and creates a delight design, which is more appealing to an individual customer. In this study, this proposed method was applied to the side shape of a car’s body and the shape of a beer cup.","PeriodicalId":338721,"journal":{"name":"Volume 1B: 38th Computers and Information in Engineering Conference","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130393149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Harley Oliff, Y. Liu, Maneesh Kumar, Michael Williams
The implementation of automation has become a common occurrence in recent years, and automated robotic systems are actively used in many manufacturing processes. However, fully automated manufacturing systems are far less common, and human operators remain prevalent. The resulting scenario is one where human and robotic operators work in close proximity, and directly affect the behavior of one another. Conversely to their robotic counterparts, human beings do not share the same level of repeatability or accuracy, and as such can be a source of uncertainty in such processes. Concurrently, the emergence of intelligent manufacturing has presented opportunities for adaptability within robotic control. This work examines relevant human factors and develops a learning model to examine how to utilize this knowledge and provide appropriate adaptability to robotic elements, with the intention of improving collaborative interaction with human colleagues, and optimized performance. The work is supported by an example case-study, which explores the application of such a control system, and its performance in a real-world production scenario.
{"title":"Integrating Intelligence and Knowledge of Human Factors to Facilitate Collaboration in Manufacturing","authors":"Harley Oliff, Y. Liu, Maneesh Kumar, Michael Williams","doi":"10.1115/DETC2018-85805","DOIUrl":"https://doi.org/10.1115/DETC2018-85805","url":null,"abstract":"The implementation of automation has become a common occurrence in recent years, and automated robotic systems are actively used in many manufacturing processes. However, fully automated manufacturing systems are far less common, and human operators remain prevalent. The resulting scenario is one where human and robotic operators work in close proximity, and directly affect the behavior of one another. Conversely to their robotic counterparts, human beings do not share the same level of repeatability or accuracy, and as such can be a source of uncertainty in such processes.\u0000 Concurrently, the emergence of intelligent manufacturing has presented opportunities for adaptability within robotic control. This work examines relevant human factors and develops a learning model to examine how to utilize this knowledge and provide appropriate adaptability to robotic elements, with the intention of improving collaborative interaction with human colleagues, and optimized performance. The work is supported by an example case-study, which explores the application of such a control system, and its performance in a real-world production scenario.","PeriodicalId":338721,"journal":{"name":"Volume 1B: 38th Computers and Information in Engineering Conference","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130512506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Barone, M. Bordegoni, F. Cucinotta, Serena Graziosi, A. Razionale, F. Sfravara
3D virtual reconstruction of human body parts is nowadays a common practice in many research fields such as the medical one, the manufacturing of customized products or the creation of personal avatar for gaming purpose. The acquisition can be performed with the use of an active stereo system (i.e., laser scanner, structured light sensors) or with the use of a passive image-based approach. While the former represents a consolidated approach in human modeling, the second is still an active research field. Usually, the reconstruction of a body part through a scanning system is expensive and requests to project light on the patient’s body. On the other hand, the image-based approach could use multi-photo technique to reconstruct a real scene and provides some advantages: low equipment costs (only one camera) and rapid acquisition process of the photo set. In this work, the use of the photogrammetry approach for the reconstruction of humans’ face has been investigated as an alternative to active scanning systems. Two different photogrammetric approaches have been tested to verify their potentiality and their sensitivity to configuration parameters. An initial comparison among them has been performed, considering the overall number of points detected (sparse point cloud reconstruction, dense point cloud reconstruction). Besides, to evaluate the accuracy of the reconstruction, a set of measures used in the design of wearable head-related products has been assessed.
{"title":"Human Face Reconstruction in Biomedical Applications","authors":"S. Barone, M. Bordegoni, F. Cucinotta, Serena Graziosi, A. Razionale, F. Sfravara","doi":"10.1115/DETC2018-85971","DOIUrl":"https://doi.org/10.1115/DETC2018-85971","url":null,"abstract":"3D virtual reconstruction of human body parts is nowadays a common practice in many research fields such as the medical one, the manufacturing of customized products or the creation of personal avatar for gaming purpose. The acquisition can be performed with the use of an active stereo system (i.e., laser scanner, structured light sensors) or with the use of a passive image-based approach. While the former represents a consolidated approach in human modeling, the second is still an active research field. Usually, the reconstruction of a body part through a scanning system is expensive and requests to project light on the patient’s body. On the other hand, the image-based approach could use multi-photo technique to reconstruct a real scene and provides some advantages: low equipment costs (only one camera) and rapid acquisition process of the photo set. In this work, the use of the photogrammetry approach for the reconstruction of humans’ face has been investigated as an alternative to active scanning systems. Two different photogrammetric approaches have been tested to verify their potentiality and their sensitivity to configuration parameters. An initial comparison among them has been performed, considering the overall number of points detected (sparse point cloud reconstruction, dense point cloud reconstruction). Besides, to evaluate the accuracy of the reconstruction, a set of measures used in the design of wearable head-related products has been assessed.","PeriodicalId":338721,"journal":{"name":"Volume 1B: 38th Computers and Information in Engineering Conference","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128298287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study addresses one solution for determining the optimal delivery of a box. The delivering task is divided into five subtasks: lifting, initial transition step, carrying, final transition step, and unloading. Each task is simulated independently with appropriate boundary conditions so that they can be stitched together to render a complete delivering task. Each task is formulated as an optimization problem. The design variables are joint angle profiles. For lifting and carrying tasks, the objective function is the dynamic effort. In contrast, for transition task, the objective function is the combination of dynamic effort and joint angle discomfort. For unloading, it is a reverse process of lifting motion. A viable optimization motion is generated from the simulation results. The joint torque, joint angle, and ground reactive forces are analyzed for the delivering motion which is also empirically validated.
{"title":"Human Box Delivering Simulation by Subtask Division","authors":"Paul Owens, Y. Xiang","doi":"10.1115/DETC2018-86195","DOIUrl":"https://doi.org/10.1115/DETC2018-86195","url":null,"abstract":"This study addresses one solution for determining the optimal delivery of a box. The delivering task is divided into five subtasks: lifting, initial transition step, carrying, final transition step, and unloading. Each task is simulated independently with appropriate boundary conditions so that they can be stitched together to render a complete delivering task. Each task is formulated as an optimization problem. The design variables are joint angle profiles. For lifting and carrying tasks, the objective function is the dynamic effort. In contrast, for transition task, the objective function is the combination of dynamic effort and joint angle discomfort. For unloading, it is a reverse process of lifting motion. A viable optimization motion is generated from the simulation results. The joint torque, joint angle, and ground reactive forces are analyzed for the delivering motion which is also empirically validated.","PeriodicalId":338721,"journal":{"name":"Volume 1B: 38th Computers and Information in Engineering Conference","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124916648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Birnbaum, J. Steuben, A. Iliopoulos, J. Michopoulos
Simulating hypervelocity impact introduces a host of complexities due to inherent strain, pressure and strain rate sensitivities. Brittle materials, and glasses in particular, exhibit significant deviations from their respective quasi-static responses, displaying permanent densification, gradual softening, and significant variation in response depending on the degree of material damage. This work seeks to examine the evolution of material failure due to hypervelocity impact of a spherical steel projectile in to a soda-lime target plate over a range of impact velocities via the utilization of a scalable, explicit finite element code, Velodyne, and a high strain rate, brittle material model. It is shown that, by analyzing both the evolutionary instantaneous and accumulated failure behaviors, the resulting performance is profoundly effected by target/projectile geometries, as well as the complex behaviors observed with respect to shock propagation, reflection and interference.
{"title":"Simulating Hypervelocity Impact and Material Failure in Glass","authors":"A. Birnbaum, J. Steuben, A. Iliopoulos, J. Michopoulos","doi":"10.1115/DETC2018-85948","DOIUrl":"https://doi.org/10.1115/DETC2018-85948","url":null,"abstract":"Simulating hypervelocity impact introduces a host of complexities due to inherent strain, pressure and strain rate sensitivities. Brittle materials, and glasses in particular, exhibit significant deviations from their respective quasi-static responses, displaying permanent densification, gradual softening, and significant variation in response depending on the degree of material damage. This work seeks to examine the evolution of material failure due to hypervelocity impact of a spherical steel projectile in to a soda-lime target plate over a range of impact velocities via the utilization of a scalable, explicit finite element code, Velodyne, and a high strain rate, brittle material model. It is shown that, by analyzing both the evolutionary instantaneous and accumulated failure behaviors, the resulting performance is profoundly effected by target/projectile geometries, as well as the complex behaviors observed with respect to shock propagation, reflection and interference.","PeriodicalId":338721,"journal":{"name":"Volume 1B: 38th Computers and Information in Engineering Conference","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122149399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Austin M. McKeand, R. Gorguluarslan, Seung-Kyum Choi
Efficient modeling of uncertainty introduced by the manufacturing process is critical in the design of the components of the aircraft engines. In this study, a stochastic approach is presented to efficiently account for the geometric uncertainty, associated with the manufacturing process, in the accurate performance prediction of aircraft engine components. A semivariogram analysis procedure is proposed in this approach to quantify spatial variability of the uncertain geometric parameters based on the manufactured specimens. Karhunen-Loeve expansion is utilized to create a set of correlated random variables from the uncertainty data obtained by variogram analysis. The detailed model of the component is created accounting for the uncertainties quantified by these correlated random variables. A stochastic upscaling method is then utilized to form a simplified model that can represent this detailed model with high accuracy under uncertainties. Specifically, a parametric model generation process is developed to represent the detailed model using Bezier curves and the uncertainties are upscaled to the parameters of this parametric representation. The modal frequency-based reliability analysis of a turbine blade example is used to demonstrate the efficacy of the proposed approach. The application results show that the proposed method effectively captures the geometric uncertainties introduced by manufacturing while providing accurate predictions under uncertainties.
{"title":"A Stochastic Approach for Performance Prediction of Aircraft Engine Components Under Manufacturing Uncertainty","authors":"Austin M. McKeand, R. Gorguluarslan, Seung-Kyum Choi","doi":"10.1115/DETC2018-85415","DOIUrl":"https://doi.org/10.1115/DETC2018-85415","url":null,"abstract":"Efficient modeling of uncertainty introduced by the manufacturing process is critical in the design of the components of the aircraft engines. In this study, a stochastic approach is presented to efficiently account for the geometric uncertainty, associated with the manufacturing process, in the accurate performance prediction of aircraft engine components. A semivariogram analysis procedure is proposed in this approach to quantify spatial variability of the uncertain geometric parameters based on the manufactured specimens. Karhunen-Loeve expansion is utilized to create a set of correlated random variables from the uncertainty data obtained by variogram analysis. The detailed model of the component is created accounting for the uncertainties quantified by these correlated random variables. A stochastic upscaling method is then utilized to form a simplified model that can represent this detailed model with high accuracy under uncertainties. Specifically, a parametric model generation process is developed to represent the detailed model using Bezier curves and the uncertainties are upscaled to the parameters of this parametric representation. The modal frequency-based reliability analysis of a turbine blade example is used to demonstrate the efficacy of the proposed approach. The application results show that the proposed method effectively captures the geometric uncertainties introduced by manufacturing while providing accurate predictions under uncertainties.","PeriodicalId":338721,"journal":{"name":"Volume 1B: 38th Computers and Information in Engineering Conference","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125681282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Salman Ahmed, M. Gawand, Lukman Irshad, H. Demirel
Computational human factors tools are often not fully-integrated during the early phases of product design. Often, conventional ergonomic practices require physical prototypes and human subjects which are costly in terms of finances and time. Ergonomics evaluations executed on physical prototypes has the limitations of increasing the overall rework as more iterations are required to incorporate design changes related to human factors that are found later in the design stage, which affects the overall cost of product development. This paper proposes a design methodology based on Digital Human Modeling (DHM) approach to inform designers about the ergonomics adequacies of products during early stages of design process. This proactive ergonomics approach has the potential to allow designers to identify significant design variables that affect the human performance before full-scale prototypes are built. The design method utilizes a surrogate model that represents human product interaction. Optimizing the surrogate model provides design concepts to optimize human performance. The efficacy of the proposed design method is demonstrated by a cockpit design study.
{"title":"Exploring the Design Space Using a Surrogate Model Approach With Digital Human Modeling Simulations","authors":"Salman Ahmed, M. Gawand, Lukman Irshad, H. Demirel","doi":"10.1115/DETC2018-86323","DOIUrl":"https://doi.org/10.1115/DETC2018-86323","url":null,"abstract":"Computational human factors tools are often not fully-integrated during the early phases of product design. Often, conventional ergonomic practices require physical prototypes and human subjects which are costly in terms of finances and time. Ergonomics evaluations executed on physical prototypes has the limitations of increasing the overall rework as more iterations are required to incorporate design changes related to human factors that are found later in the design stage, which affects the overall cost of product development. This paper proposes a design methodology based on Digital Human Modeling (DHM) approach to inform designers about the ergonomics adequacies of products during early stages of design process. This proactive ergonomics approach has the potential to allow designers to identify significant design variables that affect the human performance before full-scale prototypes are built. The design method utilizes a surrogate model that represents human product interaction. Optimizing the surrogate model provides design concepts to optimize human performance. The efficacy of the proposed design method is demonstrated by a cockpit design study.","PeriodicalId":338721,"journal":{"name":"Volume 1B: 38th Computers and Information in Engineering Conference","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133120531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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