Volume 1: 39th Computers and Information in Engineering Conference最新文献_第6页

Optimal Design of Thermo-Compression Bonding for Advanced Packaging System Under Uncertainty 不确定条件下先进封装系统热压键合优化设计

Volume 1: 39th Computers and Information in Engineering Conference Pub Date : 2019-11-25 DOI: 10.1115/detc2019-97988

Sungkun Hwang, Seung-Kyum Choi

{"title":"Optimal Design of Thermo-Compression Bonding for Advanced Packaging System Under Uncertainty","authors":"Sungkun Hwang, Seung-Kyum Choi","doi":"10.1115/detc2019-97988","DOIUrl":"https://doi.org/10.1115/detc2019-97988","url":null,"abstract":"\u0000 As the trend of miniaturization of electronic components has grown, demands for advanced microelectronics packaging development have also increased. At the same time, however, this trend raises concerns of unreliable assembly processes that are caused by defective packaging interconnections. In particular, the defects can be induced by non-coplanarity and unpredictable structural deformation of interconnections. When a slope of the die exceeds a certain degree, connectivity between components in the package may fail, which results in warpage or electrical power loss. To control this issue, thermo-compression bonding has been developed to globally apply heat and pressure into the die while the substrate is maintained at a low stage temperature. Therefore, in order to effectively handle these issues, strongly coupled thermal and structural analysis is inevitable. In this research, a simulation-based optimal design of thermo-compression bonding is developed to achieve better packaging reliability in the time transient domain. The proposed framework clearly demonstrates how the multivariate uncertain parameters can be generated. Also, it suggests how the multivariate uncertainty can be propagated through the classification approach, i.e., artificial neural network. The classification approach is then utilized to estimate the reliability of the system. The efficacy of the proposed framework is demonstrated with a practical example of an advanced packaging system which is utilized in actual commercial products. Ultimately, this study demonstrates how the strong coupling optimization method can be utilized in the actual packaging system.","PeriodicalId":352702,"journal":{"name":"Volume 1: 39th Computers and Information in Engineering Conference","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131434729","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}

引用次数: 0

Geometric Complexity Estimation of Continuous Surfaces for Fitting Processes 拟合过程中连续曲面的几何复杂度估计

Volume 1: 39th Computers and Information in Engineering Conference Pub Date : 2019-11-25 DOI: 10.1115/detc2019-98456

Hossein G. Bahabadi, A. Barari

引用次数: 1

A Spatial Linkage Exoskeleton for a Shape-Adaptive Mobile Robot 形状自适应移动机器人的空间联动外骨骼

Volume 1: 39th Computers and Information in Engineering Conference Pub Date : 2019-11-25 DOI: 10.1115/detc2019-98221

David E. Geyer, C. Turner

{"title":"A Spatial Linkage Exoskeleton for a Shape-Adaptive Mobile Robot","authors":"David E. Geyer, C. Turner","doi":"10.1115/detc2019-98221","DOIUrl":"https://doi.org/10.1115/detc2019-98221","url":null,"abstract":"\u0000 With the goal of developing a spatial linkage exoskeleton for a shape-adaptive mobile robot, capable of navigating obstacle-laden environments through changes in geometry, initial research focused on the nature of axis transformations, and parameters affecting linkages, such as the Denavit-Hartenberg (DH) parameters. Building on this background, angulated linkages are developed such that a series of scissor pairs, two angulated linkages connected at their midpoints, forming a closed-loop. Using the DH parameters, the geometries are considered in the development of a planar model. A kinematic model is also developed to replicate the design in future work. A linkage was designed using SolidWorks, and then imported into MATLAB’s Simscape Multibody software where a visual, analytical model was developed. The nominal planar model acts as the basis of a spatial model. Using the spatial model, initial prototypes were built to verify the virtual model. A concept for an actuation mechanism is discussed, with a prototype built to identify any limitations. Through experimentation and analysis of the prototypes, areas for improvement in the design are identified. Future work is discussed to further mature the design and development of this solution.","PeriodicalId":352702,"journal":{"name":"Volume 1: 39th Computers and Information in Engineering Conference","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114486057","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}

引用次数: 0

A Parametric Modeling Approach for Prediction of Load Distribution due to Fluid Structure Interaction on Aircraft Structures 飞机结构流固耦合载荷分布预测的参数化建模方法

Volume 1: 39th Computers and Information in Engineering Conference Pub Date : 2019-11-25 DOI: 10.1115/detc2019-98008

A. Barutcu, R. Gorguluarslan

{"title":"A Parametric Modeling Approach for Prediction of Load Distribution due to Fluid Structure Interaction on Aircraft Structures","authors":"A. Barutcu, R. Gorguluarslan","doi":"10.1115/detc2019-98008","DOIUrl":"https://doi.org/10.1115/detc2019-98008","url":null,"abstract":"\u0000 The Fluid Structure Interaction (FSI) is a critical multi-physics phenomenon in the aerospace applications for computing loads. Including the FSI effects on the analysis requires high computational cost. A computationally efficient framework is presented in this study for predicting the FSI effects. The high-fidelity structural model is reduced on the elastic axis by using an efficient structural idealization technique. A parametric model generation process is developed by using Bezier surface control vertices (CVs) to estimate the changing load distribution under deformation. The aircraft wing outer surface is created by using Bezier surface modeling method for this purpose. The CVs of the surfaces are perturbed to predict the effect of the deformed shape on the load distribution. This method allows to predict the load distribution by using a few CVs instead of using all grid points. The Aerodynamic Influence Coefficients (AIC) matrix is generated based on the predicted loads based on this parametric modeling approach instead of conducting computationally expensive fluid flow analysis. The presented framework is implemented for an aircraft wing design to show its efficacy.","PeriodicalId":352702,"journal":{"name":"Volume 1: 39th Computers and Information in Engineering Conference","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128407257","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}

引用次数: 0

A Performance Comprehension of Various Numerical Estimators for Variance-Based Sensitivity Analysis in Building Energy Simulations 建筑能耗模拟中基于方差的敏感性分析中各种数值估计器的性能综述

Volume 1: 39th Computers and Information in Engineering Conference Pub Date : 2019-11-25 DOI: 10.1115/detc2019-98490

Rasool Koosha, F. Shahsavari

引用次数: 0

Model Based Root Cause Analysis of Manufacturing Quality Problems Using Uncertainty Quantification and Sensitivity Analysis 基于模型的制造质量问题根本原因分析——不确定性量化和敏感性分析

Volume 1: 39th Computers and Information in Engineering Conference Pub Date : 2019-11-25 DOI: 10.1115/detc2019-97766

K. Otto, J. Mosqueda

{"title":"Model Based Root Cause Analysis of Manufacturing Quality Problems Using Uncertainty Quantification and Sensitivity Analysis","authors":"K. Otto, J. Mosqueda","doi":"10.1115/detc2019-97766","DOIUrl":"https://doi.org/10.1115/detc2019-97766","url":null,"abstract":"\u0000 Diagnosing faulty performance deviations of electro-mechanical systems can be difficult, given the multitude of components and features which could contribute as root causes. Yet this is often a problem in manufacturing, where only some of the units built do not meet performance requirements only some of the time. In this context, product and process simulation studies can aid in diagnosis. This paper aims to develop a practical workflow and toolchain to guide use of uncertainty quantification and sensitivity analysis methods for root cause analysis of manufacturing processes. This approach offers more rapid diagnosis than the typical approach using some form of iterative experimentation such as Red-X, fault tree analysis and when in high volume production, statistical analysis and potentially machine learning. Here, part processes, features and assembly deviations are used as inputs to product performance simulation to understand their detrimental impact. The large set of possible process inputs can be systematically varied and contributions to system performance deviation computed. To do this simply using uncertainty quantification and sensitivity analysis is impractical, as the problem is too large. Rather, a sequential refinement workflow is developed to define the problem and possible causes, understand ability model causes, screen causal variables, and then apply quasi-Monte-Carlo uncertainty quantification sampling and global sensitivity analysis. This provides computational guidance to ascertain which manufacturing process inputs are more likely causes of performance deviations on manufactured units.","PeriodicalId":352702,"journal":{"name":"Volume 1: 39th Computers and Information in Engineering Conference","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122199716","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}

引用次数: 3

Physics-Based Function Features for a Set of Material-Processing Verbs 一组材料处理动词的基于物理的功能特征

Volume 1: 39th Computers and Information in Engineering Conference Pub Date : 2019-11-25 DOI: 10.1115/detc2019-98343

Lakshmi N. A. Venkatanarasimhan, Xiaoyang Mao, Ahmed Chowdhury, Chiradeep Sen

引用次数: 3

Domain Randomization for Detection and Position Estimation of Multiples of a Single Object With Applications to Localizing Bolts on Structures 基于区域随机化的多目标检测与位置估计及其在结构螺栓定位中的应用

Volume 1: 39th Computers and Information in Engineering Conference Pub Date : 2019-11-25 DOI: 10.1115/detc2019-97393

Ezra Ameperosa, Pranav A. Bhounsule

{"title":"Domain Randomization for Detection and Position Estimation of Multiples of a Single Object With Applications to Localizing Bolts on Structures","authors":"Ezra Ameperosa, Pranav A. Bhounsule","doi":"10.1115/detc2019-97393","DOIUrl":"https://doi.org/10.1115/detc2019-97393","url":null,"abstract":"\u0000 Periodic replacement of fasteners such as bolts are an integral part of many structures (e.g., airplanes, cars, ships) and require periodic maintenance that may involve either their tightening or replacement. Current manual practices are time consuming and costly especially due to the large number of bolts. Thus, an automated method that is able to visually detect and localize bolt positions would be highly beneficial. In this paper, we demonstrate the use of deep neural network using domain randomization for detecting and localizing multiple bolts on a workpiece. In contrast to previous deep learning approaches that require training on real images, the use of domain randomization allows for all training to be done in simulation. The key idea here is to create a wide variety of computer generated synthetic images by varying the texture, color, camera position and orientation, distractor objects, and noise, and train the neural network on these images such that the neural network is robust to scene variability and hence provides accurate results when deployed on real images. Using domain randomization, we train two neural networks, a faster regional convolutional neural network for detecting the bolt and predicting a bounding box, and a regression convolutional neural network for estimating the x- and y-position of the bolt relative to the coordinates fixed to the workpiece. Our results indicate that in the best case we are able to detect bolts with 85% accuracy and are able to predict the position of 75% of bolts within 1.27 cm. The novelty of this work is in the use of domain randomization to detect and localize: (1) multiples of a single object, and (2) small sized objects (0.6 cm × 2.5 cm).","PeriodicalId":352702,"journal":{"name":"Volume 1: 39th Computers and Information in Engineering Conference","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127575879","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}

引用次数: 1

Reinforcement Learning Content Generation for Virtual Reality Applications 虚拟现实应用的强化学习内容生成

Volume 1: 39th Computers and Information in Engineering Conference Pub Date : 2019-11-25 DOI: 10.1115/detc2019-97711

C. López, O. Ashour, Conrad S. Tucker

{"title":"Reinforcement Learning Content Generation for Virtual Reality Applications","authors":"C. López, O. Ashour, Conrad S. Tucker","doi":"10.1115/detc2019-97711","DOIUrl":"https://doi.org/10.1115/detc2019-97711","url":null,"abstract":"\u0000 This work presents a Procedural Content Generation (PCG) method based on a Neural Network Reinforcement Learning (RL) approach that generates new environments for Virtual Reality (VR) learning applications. The primary objective of PCG methods is to algorithmically generate new content (e.g., environments, levels) in order to improve user experience. Researchers have started exploring the integration of Machine Learning (ML) algorithms into their PCG methods. These ML approaches help explore the design space and generate new content more efficiently. The capability to provide users with new content has great potential for learning applications. However, these ML algorithms require large datasets to train their generative models. In contrast, RL based methods take advantage of simulation to train their models. Moreover, even though VR has become an emerging technology to engage users, there have been few studies that explore PCG for learning purposes and fewer in the context of VR. Considering these limitations, this work presents a method that generates new VR environments by training an RL agent using a simulation platform. This PCG method has the potential to maintain users’ engagement over time by presenting them with new environments in VR learning applications.","PeriodicalId":352702,"journal":{"name":"Volume 1: 39th Computers and Information in Engineering Conference","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127296599","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}

引用次数: 8

Review of Models and Robotic Devices for Stroke Survivors’ Upper Extremity Rehabilitation 脑卒中幸存者上肢康复的模型和机器人设备综述

Volume 1: 39th Computers and Information in Engineering Conference Pub Date : 2019-11-25 DOI: 10.1115/detc2019-97223

Shadman Tahmid, Jie Yang, J. M. Font-Llagunes

引用次数: 1