0
Research Papers

A Knowledge-Driven, Network-Based Computational Framework for Product Development Systems

[+] Author and Article Information
Ali A. Yassine

Engineering Management Program,
American University of Beirut,
Beirut 1107-2020, Lebanon
e-mail: ali.yassine@aub.edu.lb

Joe A. Bradley

Software Engineering Group,
Applied Research Associates,
Champaign, IL 61802
e-mail: jbradley@ara.com

Our scope is focused primarily on detailed design where an existing team and process decomposition exist.

A summary of all input matrices, output matrices, and intermediate calculations is found in the Appendix.

In matrix [Y], a connection between a person and itself implies that the individual is a subject matter expert and makes unilateral decisions in the product development process as a result of this expertise.

In this framework, impedance only applies to the individual not to the databases. We do not consider the databases to be intelligent artifacts that can impede the formation of information.

Of course, it can be argued to extend the unit of analysis to quads or larger sub-network. The justification for this approach is that as the path length between the network nodes increases, the network search and the transfer of information become more expensive and complex [21,51]. Additionally, the use of triadic relationships provides an opportunity to draw upon a vast body of the literature that has studied various properties of triads [51,57]. Furthermore, if we accept the argument of bounded rationality, then the search space of human capacity has some limitation [1].

The clustering algorithm of Yu et al. [44] is used to identify the knowledge architecture and resultant knowledge modules.

Robocode is an educational robot design game (http://robocode.sourceforge.net).

1Corresponding author.

Contributed by the Computers and Information Division of ASME for publication in the JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING. Manuscript received October 5, 2011; final manuscript received November 5, 2012; published online March 14, 2013. Assoc. Editor: Xiaoping Qian.

J. Comput. Inf. Sci. Eng 13(1), 011005 (Mar 15, 2013) (15 pages) Paper No: JCISE-11-1440; doi: 10.1115/1.4023166 History: Received October 05, 2011; Revised November 05, 2012

Today's fast-paced product development (PD) environment brings many new challenges to the PD community. These challenges are mainly due to a drastic increase in the scale and complexity of engineered systems, which require the collaboration of functionally and geographically distributed resources within and outside a firm's boundary. To address these new challenges, this paper proposes a novel theoretical and computational framework for an enterprise-wide PD management system. The proposed framework considers an integrative view of the various dependencies that co-exist in three PD domains (i.e., people, products, and processes). Additionally, it provides a computational tool that links them together in a succinct and tractable way and provides an analysis method for assessing their influence on shaping the product development process. Using this framework, we suggest that the characteristics of how an organization acquire data, interpret information, and apply knowledge will impact the final architecture of a product. We demonstrate this framework by analyzing the development efforts for a software project called robocode.

FIGURES IN THIS ARTICLE
<>
Copyright © 2013 by ASME
Your Session has timed out. Please sign back in to continue.

References

Simon, H., 1969, The Sciences of the Artificial, MIT Press, Cambridge, MA.
Alexander, C., 1964, Notes on the Synthesis of Form, Harvard University Press, Cambridge, MA.
Rechtin, E., and Maier, M., 1997, The Art of Systems Architecting, CRC Press, Boca Raton, FL.
King, N., and Majchrzak, A., 1996, “Concurrent Engineering Tools: Are the Human Issues Being Ignored?,” IEEE Trans. Eng. Manage., 43(2), pp. 189–201. [CrossRef]
Collier, W., 1997, An Integral PIM Strategy—Implementation Roadmap, PLM Road Map, September 9–11, DH Brown Associates Inc., Dearborn, Michigan.
Morelli, M. D., Eppinger, S. D., and Gulati, R. K., 1995, “Predicting Technical Communications in Product Development Organizations,” IEEE Trans. Eng. Manage., 42(3), pp. 215–222. [CrossRef]
Hellgren, B., and Stjernberg, T., 1995, “Design and Implementation in Major Investments—A Project Network Approach,” Scand. J. Manage., 11(4), pp. 377–394. [CrossRef]
Eppinger, S., and Salminen, V., 2001, “Patterns of Product Development Interactions,” Proceedings of International Conference on Engineering Design, ICED'01, August 2001.
Sosa, M. E., Eppinger, S. D., and Rowles, C. M., 2004, “The Misalignment of Product Architecture and Organizational Structure in Complex Product Development,” Manage. Sci., 50(12), pp. 1674–1689. [CrossRef]
Parashar, S., and Bloebaum, C., 2005, “Decision Support Tool for Multidisciplinary Design Optimization (MDO) Using Mutli-Domain Decomposition,” 46th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics & Materials Conference, April 18–21, Austin, Texas.
Sosa, M. E., 2008, “A Structured Approach to Predicting and Managing Technical Interactions in Software Development,” Res. Eng. Des., 19(1), pp. 47–70. [CrossRef]
Sanchez, R., and Mahoney, J., 1996, “Modularity, Flexibility, and Knowledge Management in Product and Organization Design,” IEEE Trans. Eng. Manage., 25(4), pp. 50–61.
Allen, T., 1997, “Architecture and Communication Among Product Development Engineers,” MIT Sloan School of Management Working Paper No. 3983.
Levitt, R., Thomsen, J., Christiansen, T., Kunz, J., Jin, Y., and Nass, C., 1999, “Simulating Project Work Processes and Organizations: Toward a Micro-Contingency Theory of Organizational Design,” Manage. Sci., 45(11), pp. 1479–1495. [CrossRef]
Yassine, A. A., Joglekar, N. R., Braha, D., Eppinger, S. D., and Whitney, D. E., 2003, “Information Hiding in Product Development: The Design Churn Effect,” Res. Eng. Des., 14(3), pp. 145–161. [CrossRef]
Browning, T., Deyst, J., Eppinger, S. D., and Whitney, D. E., 2002, “Adding Value in Product Development by Creating Information and Reducing Risk,” IEEE Trans. Eng. Manage., 49(4), pp. 443–458. [CrossRef]
Ford, D., and Sterman, J., 2003, “Overcoming the 90% Syndrome: Iteration Management in Concurrent Development Projects,” Concurr. Eng. Res. Appl., 111(3), pp. 177–186. [CrossRef]
Wheelwright, S., and Clark, K., 1992, Revolutionizing Product Development, Free Press, New York.
Abdel-Hamid, T., and Madnick., S., 1991, Software Project Dynamics, An Integrated Approach, Prentice-Hall, Inc, Englewood Cliffs, NJ.
Wu, T., Xie, N., and Blackhurst, J., 2004, “Design and Implementation of Distributed Information System for Collaborative Product Development,” J. Comput. Inf. Sci. Eng., 4, pp. 281–293. [CrossRef]
Monge, P. R., and Contractor, N., 1988, “Communication Networks: Measurement Techniques,” A Handbook for the Study of Human Communication, C. H.Tardy, ed., Ablex, Norwood, NJ, pp. 107–138.
Sharman, D., Yassine, A., and Carlile, P., 2002, “Architectural Optimisation Using Real Options Theory and Dependency Structure Matrix,” ASME 2002 International Design Engineering Technical Conferences, 28th Design Automation Conference, Montreal, Canada, September 29–October 2.
Danilovic, M., and Browning, T., 2007, “Managing Complex Product Development Projects With Design Structure Matrices and Domain Mapping Matrices,” Int. J. Project Manage., 25, pp. 300–314. [CrossRef]
Yassine, A., Whitney, D., Daleiden, S., and Lavine, J., 2003, “Connectivity Maps: Modeling and Analyzing Relationships in Product Development Processes,” J. Eng. Des., 14(3), pp. 377–394. [CrossRef]
Krackhardt, D., and Carley, K., 1998, “A PCANS Model of Structure in Organization,” Proceedings of the 1998 International Symposium on Command and Control Research and Technology, Monterray, CA, Evidence Based Research, Vienna, VA, pp. 113–119.
Shooter, S., Keirouz, W., Szykman, S., and Fenves, S., 2000, “A Model for the Flow of Design Information in Product Development,” Eng. Comput., 16, pp. 178–194. [CrossRef]
Baldwin, C., and Clark, K., 2000, Design Rules. Volume 1: The Power of Modularity, MIT Press, Cambridge, MA.
Hoetker, G., 2006, “Do Modular Products Lead to Modular Organizations?,” Strategic Manage. J., 27, pp. 501–518. [CrossRef]
Sako, M., 2003, “The Nature of Co-Evolution of Product Architecture and Organization Architecture in the Global Automotive Industry,” The Business of System Integration, Oxford University Press, New York.
Stonier, T., 1997, Information and Meaning—An Evolutionary Perspective, Springer, Berlin.
Buckland, M., 1991, “Information as Thing,” J. Am. Soc. Inf. Sci., 42(5), pp. 351–360. [CrossRef]
Ess, C., 2004, “Computing in Philosophy and Religion,” A Companion to Digital Humanities, S.Schreibman, R. G.Siemens, and J.Unsworth, eds., Blackwell, Oxford, pp. 132–142.
Zins, C., 2007, “Conceptual Approach for Defining Data, Information, and Knowledge,” J. Am. Soc. Inf. Sci. Technol., 58(4), pp. 479–493. [CrossRef]
Debons, A., Horne, E., and Cronenweth, S., 1988, Information Science: An Integrated View, G.K. Hall, New York.
Davis, G., and Olson, M., 1985, Management Information Systems, McGraw-Hill, New York.
Belkin, N., and Robertson, S., 1976, “Information Science and the Phenomenon of Information,” J. Am. Soc. Inf. Sci., 27, pp. 197–204. [CrossRef]
Poli, R., 2001, “Alwis: Ontology for Knowledge Engineers,” Unpublished Doctoral Dissertation, University of Utrecht, Netherlands.
Bedward, D., and Stredwick, J., 2004, Managing Information: Core Management, Butterworth-Heinemann, London.
Halladay, S. M., and Milligan, C. A., 2006, “Knowledge Simulation via Relationship Mapping and Network Science,” IEEE Proceedings of the 39th Hawaii International Conference on System Sciences.
Wasserman, S., and Faust, K., 1994, Social Network Analysis, Cambridge University Press, New York.
Ackoff, R. L., 1989, “From Data to Wisdom,” J. Appl. Syst. Anal., 16, pp. 3–9.
Aguilar, F. J., 1967, Scanning the Business Environment, The MacMillan Company, London.
Braha, D., 2001, Data-Mining for Design and Manufacturing, Kluwer Academic Publishers, Netherlands.
Yu, T., Yassine, A., and Goldberg, A., 2007, “Developing Modular Product Architectures Using Genetic Algorithms,” Res. Eng. Des., 18(2), pp. 91–109. [CrossRef]
Holland, P., and Leinhardt, S., 1972, “Holland and Leinhardt: Some Evidence on Transitivity of Positive Interpersonal Sentiment,” Am. J. Sociol., 77, pp. 1205–1209. [CrossRef]
Whitney, D., 2004, “Connectivity Limits of Mechanical Assemblies Modeled as Networks,” ESD-WP-2004-07.
Barkmeyer, E., Christopher, N., Feng, S., Fowler, J., Frechette, S., Jones, A., Jurrens, K., McLean, C., Pratt, M., Scott, H., Senehi, M., Sriram, R., Wallace, E., 1997, SIMA Reference Architecture Part I: Activity Models, NISTIR 5939, National Institute of Standards and Technology, Gaithersburg, MD.
Borgatti, S. P., Everett, M. G., and Freeman, L. C., 2002, UCInet for Windows: Software for Social Analysis, Harvard Analytic Technologies, Lexington, KY.
Lindemann, U., and Maurer, M., 2007, “Facing Multi-Domain Complexity in Product Development,” The Future of Product Development, Proceedings of the 17th CIRP Design Conference, pp. 351–361.
Gokpinar, B., Hopp, W., and Iravani, S., 2010, “The Impact of Misalignment of Organizational Structure and Product Architecture on Quality in Complex Product Development, Management Science,” 56(3), pp. 468–484.
Gruninger, M., and Menzel, C., 2003, “The Process Specification Language (PSL) Theory and Applications,” AI Mag., 24(3), pp. 63–73.
Salamon, W., and Wallace, D., 1994, “Quality Characteristics and Metrics for Reusable Software (Preliminary Report),” U.S. Department of Commerce-Technology Administration, National Institute of Standards and Technology, Gaitherburg, MD.
Conway, M., 1968, “How Do Committees Invent?,” Datamation, 14(4), pp. 28–31.
Borgatti, S. P., and Cross, R., 2003, “A Relational View of Information Seeking and Learning in Social Networks,” Manage. Sci., 49(4), pp. 432–445. [CrossRef]
Papa, M., 1990, “Communication Network Patterns and Employee Performance With New Technology,” Commun. Res., 17, pp. 344–368. [CrossRef]
Berry, M., and Brown, M., 2005, Understanding Search Engines: Mathematical Modeling and Text Retrieval, Society of Industrial and Applied Mathematics, Philadelphia, PA.
Kogut, B., and Meitu, A., 2001, “Open-Source Software Development and Distributed Innovation,” Oxford Rev. Econ. Policy, 17, pp. 248–264. [CrossRef]
Sangal, N., Jordan, E., Sinha, V., and Jackson, D., 2005, “Using Dependency Models to Manage Complex Software Architecture,” Presented at 20th ACM SIGPLAN Conference on Object-Oriented Programming, Systems, Languages And Applications (OOPSLA), San Diego, CA.
Bradley, J., 2009, “A Multi-Domain Analysis Framework for Product Development: The “Mediating Links” of Data, Information, and Knowledge in Complex Engineered Product Systems,” Unpublished Ph.D. dissertation, University of Illinois at Urbana-Champaign, Urbana, IL.
Yassine, A., Kim, K., Roemer, T., and Holweg, M., 2004, “Investigating the Role of Information Technology in Customized Product Design,” Int. J. Prod. Plann. Control, 14(4), pp. 422–434. [CrossRef]

Figures

Grahic Jump Location
Fig. 1

Model of product development

Grahic Jump Location
Fig. 2

Network and matrix representation (a) five node network (b) corresponding five node binary matrix

Grahic Jump Location
Fig. 3

Data → Information → Knowledge → Product Framework (a) robocode Development Team (social matrix) [TM] (b) robocode database matrix [DB] (c) robocode expert matrix [EP] (d) robocode query matrix [QR]

Grahic Jump Location
Fig. 4

Input data for the software-development example

Grahic Jump Location
Fig. 5

Dyads in information layer

Grahic Jump Location
Fig. 6

Information matrix (Y), calculated using Eq. (2)

Grahic Jump Location
Fig. 7

Person 2 ego network

Grahic Jump Location
Fig. 8

robocode knowledge matrix [Z], knowledge impact [KI], and knowledge weight [KW] (computed using Eqs. (6)(8), respectively)

Grahic Jump Location
Fig. 9

Representative knowledge node network

Grahic Jump Location
Fig. 11

Partial knowledge network representation

Grahic Jump Location
Fig. 12

robocode knowledge network

Grahic Jump Location
Fig. 13

Theoretical mapping

Grahic Jump Location
Fig. 14

Summary input–output flow chart

Tables

Errata

Discussions

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