Research Papers

Supporting Vehicle Option Change Management Through a Graph-Based Visualization Tool

[+] Author and Article Information
Keith Phelan

Research Assistant
Department of Mechanical Engineering,
Clemson University,
134 EIB,
Clemson, SC 29634-0921
e-mail: ktphela@g.clemson.edu

Brian Pearce

Research Assistant
Department of Industrial Engineering,
Clemson University,
104A Freeman Hall,
Clemson, SC 29634
e-mail: bpearce@g.clemson.edu

Joshua Summers

Department of Mechanical Engineering,
Clemson University,
EIB 203,
Clemson, SC 29634-0921
e-mail: jsummer@clemson.edu

Mary Beth Kurz

Associate Professor
Department of Industrial Engineering,
Clemson University,
104A Freeman Hall,
Clemson, SC 29634
e-mail: mkurz@clemson.edu

Contributed by the Computers and Information Division of ASME for publication in the JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING. Manuscript received October 7, 2015; final manuscript received August 4, 2016; published online November 7, 2016. Editor: Bahram Ravani.

J. Comput. Inf. Sci. Eng 17(1), 011004 (Nov 07, 2016) (15 pages) Paper No: JCISE-15-1320; doi: 10.1115/1.4034472 History: Received October 07, 2015; Revised August 04, 2016

When implementing configuration management methods, the amount of data required can be problematic when validating changes to the database. This is especially true for rule-based configuration management techniques. This paper presents a graph visualization tool to assist in validating changes to the rule database. The development and implementation of the tool is presented, along with the execution and results of two user studies designed to test specific aspects of the support tool. The paper then presents how the visualization tool was implemented for four ongoing configuration changes at the original equipment manufacturer (OEM) to prove the effectiveness of the tool in assisting in validating configurations changes.

Copyright © 2017 by ASME
Topics: Visualization
Your Session has timed out. Please sign back in to continue.


Phelan, K. , Wilson, C. , Summers, J. D. , and Kurz, M. E. , 2014, “ A Case Study of Configuration Management Methods in a Major Automotive OEM,” ASME Paper No. DETC2014-34186.
Urban, S. S. , and Rangan, R. , 2004, “ From Engineering Information Management (EIM) to Product Lifecycle Management (PLM),” ASME J. Comput. Inf. Sci. Eng., 4(4), pp. 279–280. [CrossRef]
Heer, J. , Bostock, M. , and Ogievetsky, V. , 2010, “ A Tour Through the Visualization Zoo,” Commun. ACM, 53(6), pp. 59–67. [CrossRef]
van Wijk, J. J. , 2005, “ The Value of Visualization,” VIS 05 IEEE Visualization, IEEE, Minneapolis, MN, pp. 79–86.
Chen, C. , and Yu, Y. , 2000, “ Empirical Studies of Information Visualization: A Meta-Analysis,” Int. J. Hum. Comput. Stud., 53(5), pp. 851–866. [CrossRef]
Gonzalez, V. , and Kobsa, A. , 2003, “ Benefits of Information Visualization Systems for Administrative Data Analysts,” International Conference on Information Visualization, IEEE Computer Society, London, UK, pp. 331–336.
Herman, I. , Melancon, G. , and Marshall, M. S. , 2000, “ Graph Visualization and Navigation in Information Visualization: A Survey,” IEEE Trans. Visualization Comput. Graphics, 6(1), pp. 24–43. [CrossRef]
Keller, R. , Eckert, C. M. , and Clarkson, P. J. , 2006, “ Matrices or Node-Link Diagrams: Which Visual Representation is Better for Visualizing Connectivity Models?,” Inf. Visualization, 5(6), pp. 62–76. [CrossRef]
Becker, R. A. , Eick, S. G. , and Wilks, A. R. , 1995, “ Visualizing Network Data,” IEEE Trans. Visualization Comput. Graphics, 1(1), pp. 16–28. [CrossRef]
Lee, B. , Plaisant, C. , Parr, C. S. , Fekete, J.-D. , and Henry, N. , 2006, “ Task Taxonomy for Graph Visualization,” Proceedings of BELIV '06, AVI Workshop on Beyond Time and Errors: Novel Evaluation Methods for Information Visualization, Venezia, Italy, May 23–26, pp. 1–5.
Keller, R. , Eckert, C. M. , and Clarkson, P. J. , 2005, “ Multiple Views to Support Engineering Change Management for Complex Products,” Third International Conference on Coordinated and Multiple Views in Exploratory Visualization (CMV 2005), pp. 33–41.
Ghoniem, M. , Fekete, J.-D. , and Castagliola, P. , 2004, “ A Comparison of the Readability of Graphs Using Node-Link and Matrix-Based Representations,” IEEE Symposium on Information Visualization, Austin, TX, pp. 17–24.
Keller, R. , Eger, T. , Eckert, C. M. , and Clarkson, P. J. , 2005, “ Visualising Change Propagation,” International Conference on Engineering Design, Melbourne, Australia, pp. 1–12.
Schaub, M. , Matthes, F. , and Roth, S. , 2012, “ Towards a Conceptual Framework for Interactive Enterprise Architecture Management Visualizations,” Modellierung, pp. 75–90.
Kurtoglu, T. , and Tumer, I. , 2008, “ A Graph-Based Fault Identification and Propagation Framework for Functional Design of Complex Systems,” ASME J. Mech. Des., 130(5), pp. 1–8. [CrossRef]
Sorger, J. , Buhler, K. , Schulze, F. , Liu, T. , and Dickson, B. , 2013, “ neuroMAP—Interactive Graph-Visualization of the Fruit Fly's Neural Circuit,” IEEE Symposium on Biological Data Visualization, Atlanta, GA, Oct. 13–14.
Teacher, A. G. F. , and Griffiths, D. J. , 2011, “ HapStar: Automated Haplotype Network Layout and Visualization,” Mol. Ecol. Resour., 11(1), pp. 151–153. [CrossRef] [PubMed]
Xu, K. , Rooney, C. , Passmore, P. , Ham, D.-H. , and Nguyen, P. H. , 2012, “ A User Study on Curved Edges in Graph Visualization,” IEEE Trans. Visualization Comput. Graphics, 18(12), pp. 2449–2456. [CrossRef]
Ware, C. , Purchase, H. C. , Colpoys, L. , and McGill, M. , 2002, “ Cognitive Measurements of Graph Aesthetics,” Inf. Visualization, 1(2), pp. 103–110. [CrossRef]
Purchase, H. C. , 2014, “ A Healthy Critical Attitude: Revisiting the Results of a Graph Drawing Study,” J. Graph Algorithms Appl., 18(2), pp. 281–311. [CrossRef]
Purchase, H. C. , Carrington, D. , and Allder, J.-A. , 2002, “ Empirical Evaluation of Aesthetics-Based Graph Layout,” Empirical Software Eng., 7(3), pp. 233–255.
Archambault, D. , Purchase, H. C. , and Pinaud, B. , 2011, “ Difference Map Readability for Dynamic Graphs,” Graph Drawing, U. Brandes, S. Cornelsen, eds., Springer, Berlin, Chapt. 5, pp. 50–61.
Holten, D. , Isenberg, P. , van Wijk, J. J. , and Fekete, J.-D. , 2011, “ An Extended Evaluation of the Readability of Tapered, Animated, and Textured Directed-Edge Representations in Node-Link Graphs,” IEEE Pacific Visualization Symposium, Hong Kong, China, pp. 195–202.
Brewer, C. A. , 1999, “ Color Use Guidelines for Data Representation,” Section on Statistical Graphics, American Statistical Association, Alexandria, VA, pp. 55–60.
Wong, B. , 2010, “ Color Coding,” Nat. Methods, 7(8), p. 573. [CrossRef] [PubMed]
Lee, S. , Sips, M. , and Seidel, H.-P. , 2013, “ Perceptually Driven Visibility Optimization for Categorical Data Visualization,” IEEE Trans. Visualization Comput. Graphics, 19(10), pp. 1746–1757. [CrossRef]
Purchase, H. C. , 1998, “ The Effects of Graph Layout,” Australasian Computer Human Interaction Conference, IEEE Computer Society, pp. 80–86.
Gibson, H. , Faith, J. , and Vickers, P. , 2012, “ A Survey of Two-Dimensional Graph Layout Techniques for Information Visualisation,” Inf. Visualization, 12(3–4), pp. 324–357.
Bastian, M. , Heymann, S. , and Jacomy, M. , 2009, “ Gephi: An Open Source Software for Exploring and Manipulating Networks,” Third International Conference on Weblogs and Social Media, San Jose, CA, pp. 361–362.
Bostock, M. , Ogievetsky, V. , and Heer, J. , 2011, “ D3 Data-Driven Documents,” IEEE Trans. Visualization Comput. Graphics, 17(12), pp. 2301–2309. [CrossRef]
Reas, C. , and Fry, B. , 2006, “ Processing: Programming for the Media Arts,” AI Soc., 20(4), pp. 526–538. [CrossRef]
Phelan, K. , Wilson, C. , Pearce, B. , Summers, J. D. , and Kurz, M. E. , 2015, “ Graph Visualization Styles for Use in Configuration Management: A User Study,” ASME Paper No. DETC2015–46288.
North, C. , Saraiya, P. , and Duca, K. , 2011, “ A Comparison of Benchmark Task and Insight Evaluation Methods for Information Visualization,” Inf. Visualization, 10(3), pp. 162–181. [CrossRef]
Huang, W. , Eades, P. , and Hong, S.-H. , 2009, “ Measuring Effectiveness of Graph Visualizations: A Cognitive Load Perspective,” Inf. Visualization, 8(3), pp. 139–152. [CrossRef]
Noor, K. B. M. , 2008, “ Case Study: A Strategic Research Methodology,” Am. J. Appl. Sci., 5(11), pp. 1602–1604. [CrossRef]
Griffee, D. , 2005, “ Research Tips: Interview Data Collection,” J. Dev. Educ., 28(3) pp. 36–37. http://eric.ed.gov/?id=EJ718580
Schraw, G. , 1993, “ Constraints on the Calibration of Performance,” Contemp. Educ. Psychol., 18(4), pp. 455–463. [CrossRef]
Dinsmore, D. L. , and Parkinson, M. M. , 2012, “ What Are Confidence Judgments Made of? Students' Explanations for Their Confidence Ratings and What That Means for Calibration,” Learn. Instr., 24, pp. 4–14. [CrossRef]
Thimmaiah, S. , Phelan, K. T. , and Summers, J. D. , 2013, “ User Study: Influence of Number of Design Errors on Ability to Predict Performance With and Without Controls,” ASME Paper No. DETC2013-12294.
Motyka, M. , Maier, J. R. A. , and Fadel, G. M. , 2010, “ Representing the Complexity of Engineering Systems: A Multidisciplinary Perceptual Approach,” Unifying Themes in Complex Systems, A. Minai , D. Braha , and Y. Bar-Yam , eds., Springer, Berlin, pp. 564–571.
Phelan, K. T. , Pearce, B. , Summers, J. D. , and Kurz, M. E. , 2016, “ Evaluating Configuration Rule Implementation Through a Graph-Based User Interface,” Tools and Methods for Competitive Engineering, Aix-en-Provence, France, Paper No. 69.


Grahic Jump Location
Fig. 1

Example of a visualization graph (provided to groups 1 and 7)

Grahic Jump Location
Fig. 2

Modified 100 mm confidence scale

Grahic Jump Location
Fig. 3

Graph of the correctness for each question based on availability of information

Grahic Jump Location
Fig. 4

Graph of the correctness for each question based on color-coding

Grahic Jump Location
Fig. 5

Graph for the correctness of each question based on layout

Grahic Jump Location
Fig. 6

Graph of the correctness for each question based on order

Grahic Jump Location
Fig. 7

Example graph node input file

Grahic Jump Location
Fig. 8

Example graph edge input file

Grahic Jump Location
Fig. 9

Rule and corresponding graph for an inclusive, binary relationship

Grahic Jump Location
Fig. 10

Rule and corresponding graph for an exclusive, binary relationship

Grahic Jump Location
Fig. 11

Rule and corresponding graph for a relationship requiring an OR node

Grahic Jump Location
Fig. 12

Rule and corresponding graph for a relationship with an AND node

Grahic Jump Location
Fig. 13

Another rule and corresponding graph for a relationship with an AND node

Grahic Jump Location
Fig. 14

Graph visualization for a specific change

Grahic Jump Location
Fig. 15

Rule system graph provided to the experimental groups

Grahic Jump Location
Fig. 16

Percent correct responses for change 1

Grahic Jump Location
Fig. 17

Percent correct responses for change 2

Grahic Jump Location
Fig. 18

Percent correct responses for change 3

Grahic Jump Location
Fig. 19

Visualization graph for windshield option change (case 1)

Grahic Jump Location
Fig. 20

Visualization graph for existing model

Grahic Jump Location
Fig. 21

Visualization graph for replacement model

Grahic Jump Location
Fig. 22

Existing model graph with the Australian country option already available

Grahic Jump Location
Fig. 23

Graph of the model to which the country option will be added



Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In