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

\bibitem{asee_peer_20642}
  Guo, C., \& Chen, Y. V., \& Miller, C. L., \& Hartman, N. W., \& Mueller, A. B., \& Connolly, P. E. (2014, June), \emph{Information Visualization for Product Lifecycle Management (PLM) Data }
  Paper presented at 2014 ASEE Annual Conference \& Exposition, Indianapolis, Indiana.
  10.18260/1-2--20642

Chen Guo, Yingjie Victor Chen, Craig L. Miller, Nathan W. Hartman, Amy B. Mueller, and Patrick E. Connolly.  "Information Visualization for Product Lifecycle Management (PLM) Data ".  2014 ASEE Annual Conference & Exposition, Indianapolis, Indiana, 2014, June.  ASEE Conferences, 2014.  https://peer.asee.org/20642 Internet.  07 Jun, 2024

\bibitem{asee_peer_20642}
  Chen Guo, Yingjie Victor Chen, Craig L. Miller, Nathan W. Hartman, Amy B. Mueller, and Patrick E. Connolly.
  "Information Visualization for Product Lifecycle Management (PLM) Data ".
  \emph{2014 ASEE Annual Conference \& Exposition, Indianapolis, Indiana, 2014, June}.
  ASEE Conferences, 2014.
  https://peer.asee.org/20642 Internet.  07 Jun, 2024

@INPROCEEDINGS{asee_peer_20642
author = "Chen Guo, Yingjie Victor Chen, Craig L. Miller, Nathan W. Hartman, Amy B. Mueller, and Patrick E. Connolly"
title = "Information Visualization for Product Lifecycle Management (PLM) Data "
booktitle = "2014 ASEE Annual Conference \& Exposition"
year = "2014"
month = "June"
address = "Indianapolis, Indiana"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/20642}
number = {10.18260/1-2--20642}
}

TY  - CPAPER
AB  - 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.
AU  - Chen Guo
AU  - Yingjie Victor Chen
AU  - Craig L. Miller
AU  - Nathan W. Hartman
AU  - Amy B. Mueller
AU  - Patrick E. Connolly
CY  - Indianapolis, Indiana
DA  - 2014/06/15
PB  - ASEE Conferences
TI  - Information Visualization for Product Lifecycle Management (PLM) Data 
UR  - https://peer.asee.org/20642
DO  - 10.18260/1-2--20642
ER  -