Skip to main content
Log in

The interdisciplinary engineering knowledge genome

  • Original Paper
  • Published:
Research in Engineering Design Aims and scope Submit manuscript

Abstract

Parallel to the concept of the human genome and its impact on biology and other disciplines, we revealed a similar concept in engineering sciences, termed the “Interdisciplinary Engineering Knowledge Genome”, which is an organized collection of system and method “genes” that encode instructions for generating new systems and methods in diverse engineering disciplines. Resting on the firm mathematical foundation of combinatorial representations, the Interdisciplinary Engineering Knowledge Genome unifies many engineering disciplines, providing a basis for transforming knowledge between them, supporting new educational practices, promoting inventions, aiding design, and bootstrapping new discoveries in engineering and science. Given the formal underlying combinatorial representations, these merits could be automated. This paper elucidates this new concept and demonstrates its value and power in engineering design.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Notes

  1. We use the term interdisciplinary to denote a concept that provides an integrative framework for knowledge from different disciplines. The term multidisciplinary is closely related but is often meant to describe the parallel working of multiple disciplines without integrating their body of knowledge. Another term, transdisciplinary, might have been more appropriate, but it has recently come to refer to solving societal problems that transcend single disciplines and require different design and inquiry practices. While our long-term goal is similar, we have no example of such use of the concept we propose that supports referring to it as being transdisciplinary.

  2. This has led researchers to look at new ways to measure the amount of interdisciplinary work in a scientific discipline (Porter and Youtie 2009; Rafols and Meyer 2007).

  3. We see similar trend in the biology literature, gradually moving from studying genes, to single protein pathways, and analyzing the complete network of protein interaction (Barabási and Oltvai 2004), as well as the identification of hierarchical structures in protein pathways (Dobrin et al. 2004; Kashtan et al. 2004). Through this, the concept of the genome evolves continuously.

  4. Presently, this property is related to simple single functions. It remains to be demonstrated for complex functions.

  5. This network of relations is growing steadily with further analysis of new representations and new engineering disciplines.

  6. A provisional patent has been filed for this device.

References

  • Altshuller GS (1984) Creativity as an exact science: the theory of the solution of inventive problems. CRC Press, London

    Google Scholar 

  • Andreasen MM (1992) Designing on a “Designer’s Workbench” (DWB). In: Proceedings of the 9th WDK workshop. Rigi, Switzerland

  • Assur LV (1952) Issledovanie ploskih sterzhnevyh mehanizmov s nizkimi parami s tochki zrenija ih struktury i klassifikacii. Akad. Nauk SSSR. Arotobolevskii II (Ed)

  • Avery OT, MacLeod CM, McCarty M (1944) Induction of transformations by a desoxyribonucleic acid fraction isolated from pneumococcus type III. J Exp Med 79:137–158

    Article  Google Scholar 

  • Balabanian N, Bickart TA (1969) Electrical network theory. Wiley, New York

    MATH  Google Scholar 

  • Barabási A-L, Oltvai ZN (2004) A network biology: understanding the cell’s functional organization. Nat Rev Genet 5:101–113

    Article  Google Scholar 

  • Baxter D, Gao J, Case K, Harding J, Young B, Cochrane S, Dani S (2007) An engineering design knowledge reuse methodology using process modelling. Res Eng Des 18:37–48

    Article  Google Scholar 

  • Benyus JM (1997) Biomimicry: innovation inspired by nature. William Morrow

  • Berg P, Singer M (1992) Dealing with genes: the language of heredity. University Science Books, Mill Valley

    Google Scholar 

  • Borutzky W (2009) Bond graph modelling and simulation of multidisciplinary systems—an introduction. Simul Model Pract Theory 17(1):3–21

    Article  Google Scholar 

  • Bowen J, Bahler D (1992) Frames, quantification, perspectives, and negotiation in constraint networks for life-cycle engineering. AI Eng 7(4):199–226

    Google Scholar 

  • Bozzo LM, Fenves GL (1994) Qualitative reasoning and the representation of fundamental principles in structural engineering. Res Eng Des 6(2):61–72

    Article  Google Scholar 

  • Bracewell RH, Sharpe JEE (1996) Functional description used in computer support for qualitative scheme generation—‘Schemebuilder’. AI EDAM 10:333–345

    Google Scholar 

  • Bradley DA, Bracewell RH, Chaplin RV (1992) Engineering design and mechatronics: the Schemebuilder project. Res Eng Des 4(4):241–248

    Article  Google Scholar 

  • Bryman A (2004) Qualitative research on leadership: a critical but appreciative review. Leadersh Q 15:729–769

    Article  Google Scholar 

  • Bucciarelli LL (2002) Between thought and object in engineering design. Des Stud 23(3):219–231

    Article  Google Scholar 

  • Chakrabarti A, Bligh TP (1994) An approach to functional synthesis of solutions in mechanical conceptual design. Part I: Introduction and knowledge representation. Res Eng Des 6(3):127–141

    Article  Google Scholar 

  • Chakrabarti A, Sarkar P, Leelavathamma B, Nataraju BS (2005) A functional representation for aiding biomimetic and artificial inspiration of new ideas. AI EDAM 19:113–132

    Google Scholar 

  • Chandrasekaran B, Goel A, Iwasaki Y (1993) Functional representation as design rationale. IEEE Comput 26(1):48–56

    Article  Google Scholar 

  • Chen K-Z, Feng X-A, Chen X-C (2005) Reverse deduction of virtual chromosomes of manufactured products for their gene-engineering-based innovative design. Comput Aided Des 37(11):1191–1203

    Article  MathSciNet  Google Scholar 

  • Chiu I, Shu LH (2007) Biomimetic design through natural language analysis to facilitate cross-domain information retrieval. AI EDAM 21(1):45–59

    Google Scholar 

  • Cowan R (2001) Expert systems: aspects of and limitations to the codifiability of knowledge. Res Policy 30:1355–1372

    Article  Google Scholar 

  • Coyne RD, Rosenman MA, Radford AD, Balachandran BM, Gero JS (1990) Knowledge-based design systems. Addison-Wesley, Reading

    Google Scholar 

  • Cramton CD (2001) The mutual knowledge problem and its consequences for dispersed collaboration. Organ Sci 12(3):346–371

    Article  Google Scholar 

  • Dasgupta D (ed) (1999) Artificial immune systems and their applications. Springer, Berlin

    MATH  Google Scholar 

  • De Jong H (2004) Qualitative simulation and related approaches for the analysis of dynamic systems. Knowl Eng Rev 19(2):93–132

    Google Scholar 

  • Dobrin R, Beg QK, Barabási A-L, Oltvai ZN (2004) Aggregation of topological motifs in the Escherichia coli transcriptional regulatory network. BMC Bioinform 5:10

    Article  Google Scholar 

  • Dorigo M, Maniezzo V, Colorni A (1996) Ant system: optimization by a colony of cooperating agents. IEEE Trans Syst Man Cybern B 26(1):29–41

    Article  Google Scholar 

  • Dorst K, Vermaas PE (2005) John Gero’s function-behaviour-structure model of designing: a critical analysis. Res Eng Des 16(1–2):17–26

    Article  Google Scholar 

  • Duffy AHB, Persidis A, Maccallum KJ (1996) NODES: a numerical and object based modelling system for conceptual engineering DESign. Knowl Based Syst 9(3):183–206

    Article  Google Scholar 

  • Erden MS, Komoto H, van Beek TJ, D’Amelio V, Echavarria E, Tomiyama T (2008) A review of function modeling: approaches and applications. AI EDAM 22(2:12):147–169

  • Fenves SJ, Branin FH (1963) Network topological formulation of structural analysis. J Struct Div ASCE 89(ST4):483–514

    Google Scholar 

  • Fu Z, de Pennington A (1993) Constraint-based design using an operational approach. Res Eng Des 5(3–4):202–217

    Article  Google Scholar 

  • Gero JS (1990) Design prototypes: a knowledge representation schema for design. AI Mag 11(4):26–36

    Google Scholar 

  • Goel AK (1997) Design, analogy, and creativity. IEEE Exp 12(3):62–70

    Article  MathSciNet  Google Scholar 

  • Goldberg DE (2002) The design of innovation: lessons from and for competent genetic algorithms. Addison-Wesley, Reading

    MATH  Google Scholar 

  • Hatchuel A, Weil B (2003) A new approach of innovative design: an introduction to C-K theory. In: CD-ROM proceedings of the 14th international conference on engineering design (ICED), The Design Society

  • Hatchuel A, Weil B (2009) C-K design theory: an advanced formulation. Res Eng Des 19(4):181–192

    Article  Google Scholar 

  • Helfman Cohen Y, Reich Y, Greenberg S (2011) What can we learn from natural systems when applying the law of system completeness? TRIZ Future 2011, Dublin, Ireland

  • Hirtz J, Stone RB, McAdams DA, Szykman S, Wood KL (2002) A functional basis for engineering design: reconciling and evolving previous efforts. Res Eng Des 13(2):65–82

    Google Scholar 

  • Horváth I, van der Vegte W (2003) Nucleus-based product conceptualization—part 1: Principles and formalization. In: Proceedings of the international conference on engineering design, ICED 03, Stockholm

  • Hubka V, Eder WE (1988) Theory of technical systems. Springer, Berlin

    Google Scholar 

  • Jackson SH (2005) Presidential address: the nexus: where science meets society. Science 310(5754):1634–1639

    Article  Google Scholar 

  • Jacobs D, Rader L, Kuhn L, Thorpe M (2001) Protein flexibility predictions using graph theory. Proteins 40:150–165

    Article  Google Scholar 

  • Jin Y, Zouein GE, Lu SC-Y (2009) A synthetic DNA based approach to design of adaptive systems. CIRP Ann Manufact Technol 58(1):153–156

    Article  Google Scholar 

  • Kashtan N, Itzkovitz S, Milo R, Alon U (2004) Topological generalizations of network motifs. Phys Rev E 70:031909

    Article  Google Scholar 

  • Katoh N, Tanigawa S (2011) A proof of the molecular conjecture. Discrete Computat Geometry 45(4):647–700

    Article  MathSciNet  MATH  Google Scholar 

  • Katzenbach JR, Smith DK (1993) The discipline of teams. Harvard Bus Rev 71(2):111–120

    Google Scholar 

  • Kayworth TR, Leidner DE (2001) Leadership effectiveness in global virtual teams. J Manage Inf Syst 18(3):7–40

    Google Scholar 

  • Kitamura Y, Mizoguchi R (2004) Ontology-based systematization of functional knowledge. J Eng Des 15:327–351

    Article  Google Scholar 

  • Konda S, Monarch I, Sargent P, Subrahmanian E (1992) Shared memory in design: a unifying theme for research and practice. Res Eng Des 4(1):23–42

    Article  Google Scholar 

  • Lenat DB, Prakash M, Shepherd M (1986) CYC: using common sense knowledge to overcome brittleness and knowledge-acquisition bottlenecks. AI Mag 6:65–85

    Google Scholar 

  • Mak TW, Shu LH (2008) Using descriptions of biological phenomena for idea generation. Res Eng Des 19(1):21–28

    Article  Google Scholar 

  • Max-Neef MA (2005) Foundations of transdisciplinarity. Ecol Econ 53:5–16

    Article  Google Scholar 

  • McMahon CA, Xianyi M (1996) A network approach to parametric design integration. Res Eng Des 8(1):14–31

    Article  Google Scholar 

  • Mullins S, Rinderle JR (1991) Grammatical approaches to engineering design, part I: an introduction and commentary. Res Eng Des 2(3):121–135

    Article  Google Scholar 

  • Pechter T, Reich Y (2003) A method for finding the structure and tuning parameters of systems. In: Proceedings of the 29th Israel conference on mechanical engineering, Haifa, Israel

  • Porter AL, Rafols I (2009) Is science becoming more interdisciplinary? Measuring and mapping six research fields over time. Scientometrics (in press)

  • Porter AL, Youtie J (2009) How interdisciplinary is nanotechnology? J Nanopart Res 11(5):1023–1041

    Article  Google Scholar 

  • Rafols I, Meyer M (2007) How cross-disciplinary is bionanotechnology? Explorations in the specialty of molecular motors. Scientometrics 70(3):633–650

    Article  Google Scholar 

  • Recski A (1989) Matroid theory and its applications in electric network theory and in statics. Springer, Berlin

    Google Scholar 

  • Reich Y, Subrahmanian E, Cunningham D, Dutoit A, Konda S, Patrick R, Westerberg A, The n-dim group (1999) Building agility for developing agile design information systems. Res Eng Des 11(2):67–83

    Article  Google Scholar 

  • Reich Y, Shai O, Subrahmanian E, Hatchuel A, Le Masson P (2008) The interplay between design and mathematics: Introduction to bootstrapping effects. In: Proceedings of the 9th biennial ASME conference on engineering systems design and analysis ESDA2008, Haifa, Israel

  • Roman G (2005) Cross domain conceptual design, M.Sc. Thesis. Mechanical Engineering School, Tel Aviv University

  • Root-Bernstein RS, Root-Bernstein MM (2001) Sparks of genius. Mariner Books, USA

    Google Scholar 

  • Sargent P, Subrahmanian E, Downs M, Greene R, Rishel D (1992) Materials’ information and conceptual data modeling. In: Barry TI, Reynard KW (eds) Computerization and Networking of Materials Databases: Third Volume, ASTM STP 1140. American Society for Testing and Materials, USA

    Google Scholar 

  • Schmidt LC, Cagan J (1997) GGREADA: a graph grammar-based machine design algorithm. Res Eng Des 9(4):195–213

    Article  Google Scholar 

  • Schummer J (2004) Multidisciplinarity, interdisciplinarity, and patterns of research collaboration in nanoscience and nanotechnology. Scientometrics 59(3):425–465

    Article  Google Scholar 

  • Servatius B, Shai O, Whiteley W (2010) Combinatorial characterization of the Assur Graphs from engineering. Eur J Combinator 31(4):1091–1104

    Article  MathSciNet  MATH  Google Scholar 

  • Shai O (2001a) The multidisciplinary combinatorial approach and its applications in engineering. AI EDAM 15(2):109–144

    MATH  Google Scholar 

  • Shai O (2001b) Combinatorial representations in structural analysis. Comput Civil Eng 15(3):193–207

    Article  Google Scholar 

  • Shai O (2009) The canonical form of all planar linkage topologies. ASME Design Engineering Technical Conferences, San Diego

    Google Scholar 

  • Shai O, Mohr Y (2004) Towards transferring engineering knowledge through graph representations: transferring Willis method to mechanisms and trusses. Eng Comput 20(1):2–10

    Article  Google Scholar 

  • Shai O, Polansky I (2006) Finding dead-point positions of planar pin-connected linkages through graph theoretical duality principle. J Mech Des Spatial Mech Robot Manipulat Trans ASME 128(3):599–609

    Google Scholar 

  • Shai O, Reich Y (2004a) Infused design. I Theory. Res Eng Des 15(2):93–107

    Google Scholar 

  • Shai O, Reich Y (2004b) Infused design. II Practice. Res Eng Des 15(2):108–121

    Google Scholar 

  • Shai O, Reich Y (2009) Inventing a new method in statics through knowledge in kinematics. In: Proceedings of the ASME 2009 international design engineering technical conferences & computers and information in engineering conference, IDETC/CIE, San Diego, CA

  • Shai O, Reich Y (2011) Understanding engineering systems through the engineering knowledge genome: structural genes of systems topologies. In: Proceedings of the international conference on engineering design, ICED11, Copenhagen, Denmark

  • Shai O, Rubin D (2003) Representing and analyzing integrated engineering systems through combinatorial representations. Eng Comput 19(4):221–232

    Article  Google Scholar 

  • Shai O, Reich Y, Rubin D (2009a) Creative conceptual design: extending the scope by infused design. Comput Aided Des 41(3):117–135

    Article  Google Scholar 

  • Shai O, Reich Y, Hatchuel A, Subrahmanian E (2009b) Creativity theories and scientific discovery: a study of C-K theory and infused design. In: CD proceedings of the international conference on engineering design, ICED’09, Stanford, CA (Received the Outstanding paper award)

  • Shai O, Tehori I, Bronfeld A, Slavutin M, Ben-Hanan U (2009c) Adjustable tensegrity robot based on assur graph principle. In: ASME international mechanical engineering congress and exposition, November 13–19, Lake Buena Vista, Florida, USA

  • Shai O, Reich Y, Hatchuel A, Subrahmanian E (2012) Creativity theories and scientific discovery: a study of infused design and C-K theory. Res Eng Des (in press)

  • Sim SK, Duffy AHB (2003) Towards an ontology of generic engineering design activities. Res Eng Des 14(4):200–223

    Article  Google Scholar 

  • Smith PG, Blanck EL (2002) From experience: leading dispersed teams. J Product Innovat Manage 19:294–304

    Article  Google Scholar 

  • Subrahmanian E, Konda SL, Levy SN, Reich Y, Westerberg AW, Monarch IA (1993) Equations aren’t enough: informal modeling in design. Artif Intell Eng Des Anal Manufact 7(4):257–274

    Article  Google Scholar 

  • Subrahmanian E, Reich Y, Konda SL, Dutoit A, Cunningham D, Patrick R, Thomas M, Westerberg AW (1997) The n-dim approach to building design support systems. In: Proceedings of ASME design theory and methodology DTM’97, ASME, New York, NY

  • Szostak R (2009) The causes of economic growth: interdisciplinary perspectives. Springer, Berlin

    Google Scholar 

  • Tomiyama T, Kiriyama T, Takeda H, Xue D, Yoshikawa H (1989) Metamodel: a key to intelligent CAD systems. Res Eng Des 1(1):19–34

    Article  Google Scholar 

  • van Eck D (2010) On the conversion of functional models: bridging differences between functional taxonomies in the modeling of user actions. Res Eng Des 21(2):99–111

    Article  MathSciNet  Google Scholar 

  • Watson JD, Crick FHC (1953) A structure for deoxyribose nucleic acid. Nature 171:737–738

    Google Scholar 

  • Whiteley W (1999) Rigidity of molecular structures: generic and geometric analysis. In: Duxbury PM, Thorpe MF (eds) Rigidity theory and applications. Kluwer/Plenum, New York

    Google Scholar 

  • Yan H-S, Wu L–L (1989) On the dead-center positions of planar linkage mechanisms. J Mech Transmissions Automat Des 111:40–46

    Article  Google Scholar 

  • Yang G, Chen I-M, Lin W, Angeles J (2001) Singularity analysis of three-legged parallel robots based on passive-joint velocities. IEEE Trans Robot Automat 17(4):413–422

    Google Scholar 

  • Zdrahal Z, Mulholland P, Valasek M, Bernardi A (2007) Worlds and transformations: supporting the sharing and reuse of engineering design knowledge. Int J Hum Comput Stud 65:959–982

    Article  Google Scholar 

Download references

Acknowledgments

This research was partially funded by the Fleischman Foundation.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yoram Reich.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Reich, Y., Shai, O. The interdisciplinary engineering knowledge genome. Res Eng Design 23, 251–264 (2012). https://doi.org/10.1007/s00163-012-0129-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00163-012-0129-x

Keywords

Navigation