Indianapolis, Indiana
June 15, 2014
June 15, 2014
June 18, 2014
2153-5965
Engineering Design Graphics
15
24.750.1 - 24.750.15
10.18260/1-2--20642
https://peer.asee.org/20642
1036
Chen Guo serves as a Teaching Assistant in the Department of Computer Graphics Technology at Purdue University. She is currently pursuing her PhD in CGT from the College of Technology. Since 2011 she has taught courses in Construction Graphics, Computer Graphics, Product Design, Simulation and Visualization. Her research interest includes in the area of Graphic Design, Information Visualization and Interactive Media.
Dr. Yingjie Chen is an assistant professor in the department of computer graphics technology of Purdue university. He received his Ph.D. degree in the areas of human-computer interaction, information visualization, and visual analytics from the School of Interactive Arts and Technology at Simon Fraser University (SFU) in Canada. He earned Bachelor degree of Engineering from the Tsinghua University (China), and a Master of Science degree in Information Technology from SFU. His research covers interdisciplinary domains of Information Visualization, Visual Analytics, Digital Media, and Human Computer Interaction. He seeks to design, model, and construct new forms of interaction in visualization and system design, by which the system can minimize its influence on design and analysis, and become a true free extension of human’s brain and hand.
Nathan Hartman is an Associate Professor in the Department of Computer Graphics Technology at Purdue University, and Director of the Purdue University PLM Center of Excellence. Dr. Hartman is also Director of Advanced Manufacturing in the College of Technology. His research focuses on examining the use of 3D CAD tools in the product lifecycle, the process and methodology for model-based definition and the model-based enterprise, geometry automation, and data interoperability and re-use. He currently teaches courses in 3D modeling, virtual collaboration, 3D data interoperability, and graphics standards and data exchange. Professor Hartman also leads a team in the development and delivery of the online Purdue PLM Certificate Program and in the development of the next-generation manufacturing curriculum at Purdue focusing on manufacturing systems and the holistic product lifecycle.
Amy B Mueller is a Clinical Assistant Professor in the College of Technology, Purdue University, West Lafayette campus. She received her BS in ME from Purdue University and her MBA in Information Systems from the University of Toledo. Before joining the faculty in 2012, Ms. Mueller spent over 30 years in industry and her career parallels the progression of CAD/CAM to PDM to PLM. She has held industry positions with Owens-Illinois, Parametric Technology, Cummins, Faurecia and Toyota Industrial Equipment as well as a VAR and a consulting firm. She has held previous adjunct teaching positions with the University of Toledo and Ivy Tech Community College. Ms. Mueller also worked as the Director of Minds on Math for the Bartholomew County School Corporation which is an after school math enrichment program for fourth graders. She is a member of ASEE, ACM and SWE.
Patrick Connolly is a Professor and Interim Head of the Department of Computer Graphics Technology with Purdue University at West Lafayette, Indiana. He received his Bachelor of Science degree in Design and Graphics Technology and Master of Science degree in Computer Integrated Manufacturing from Brigham Young University in Provo, Utah. He completed his Ph.D. in Educational Technology at Purdue University. Dr. Connolly has been teaching at Purdue since 1996, and is active in several professional organizations. Prior to entering academia, he worked for twelve years in the aerospace and computer software industries and has extensive experience in CAD applications and design, CAE software support, and customer service management. His interests include solid modeling applications, virtual and augmented reality, visualization techniques, innovative teaching methods, and distance learning.
EmployaVisualAnalyticsApproachtoDecodeProductManagementDataIn this paper, we propose a visual analytics approach to help designers and engineers analyze andinterpret product management data, and to guide the direction of product improvements. A product maybe a system that contains thousands or even millions of parts, joined together in many levels ofsubassemblies with different configurations, to define a working product structure. The relationshipsamong parts, assemblies, and products make a complex network of interdependencies manifested in boththe virtual and physical definition of the product. Currently there are just a few methods to represent andhandle such complicated product data. The most popular ones are 3D computer models for parts andassemblies and spreadsheet tables of BOM (Bill of Material). We propose to use the Visual Analytics(VA) approach to visually represent and manage product data, allowing the users to navigate in thehierarchy and generate insights from the visualizations.Visual Analytics is the science of analytical reasoning supported by highly interactive visual interfaces. Ithas been proven to be efficient at handling massive, dynamic, and often conflicting data in different kindsof analysis domains. The complexity of the data and challenges in communication make the product datamanagement (PDM) tool a significant roadblock to productive data usage due to its typically inflexibledata presentation options and its lack of robust user experience design. The 3D model is superior forunderstanding the product and parts in context. But those complex products, the big number of parts andhuge volume of data impair the reading and understanding the product models. We suggest that addingabstract data visualizations of as a supplement of the 3D models can effectively improve the interpretationof the product and its management system.In this paper, we will demonstrate several visual analytics methods that can help users to understand andanalyze the product data. For example, A tree or network graph to represent product’s hierarchical structure: Many PLM systems use a tree to visualize the structure of product components. With a tree graph or enriched network graph, it is possible to visualize individual part’s property as well as mating relations among parts. The product designers and engineers can easily identify the weakest links in the product and make improvement decisions. A treemap to visualize quantitative measurements: A treemap visualization shows hierarchical data of product structure as a set of nested rectangles. Quantities and qualities of parts can visualized simultaneously in a treemap to let the managers get the real-time overall status of the whole product. A geo-temporal visualization to demonstrate the geographical and history data. A product is assembled by parts created around the world. Across the time, there are different versions of design, managers need to use the geo-temporal visualizations to manage the supply chain.Engineers, designers, managers, and agents, people in the entire product life cycle may benefit from thenew approach. We envision that our approach will accommodate the communication across groups,catalyze creative ideas, support exploratory management process, and improve the full product lifecyclefrom design and manufacturing to service.
Guo, C., & Chen, Y. V., & Miller, C. L., & Hartman, N. W., & Mueller, A. B., & Connolly, P. E. (2014, June), Information Visualization for Product Lifecycle Management (PLM) Data Paper presented at 2014 ASEE Annual Conference & Exposition, Indianapolis, Indiana. 10.18260/1-2--20642
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