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Functional lock-in and the problem of design transformation

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Abstract

The act of introducing an innovation into an existing product by substituting or inserting new technologies is thought to be challenging due to the problem of integrating new components and sub-system architectures into existing ones. This article aims to challenge the foundation of this problem and develop new insights into the choice of functional architecture. The article will propose that the choice of functional architecture to achieve an intended purpose locks-in a design by influencing the cost of transformation. This paper studies functional lock-in based on the transformation cost of the functional architectures of products. The transformation cost for a set of biological and biologically inspired products is compared to that of engineered products. The results show that the biological and biologically inspired products have a statistically significant lower transformation cost than the engineered products. The results indicate that the structure of functions and flows in a product will constrain its transformation. More broadly, the paper proposes minimum transformation cost as an essential property of an optimal design.

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Notes

  1. The node degree is the number of edges connected to the node.

  2. This paper uses the term biological systems to refer to plant or animal species or parts thereof, but not ecosystems.

  3. It is debated that some of nature’s designs are not optimal, such as the human visual cortex. This article assumes, though, that in general nature’s designs, biological systems, are optimal.

  4. One of the challenges in performing this research is the lack of a large number of functional models of complex products. Functional models were taken from existing data sources to limit potential bias in their production by the author.

  5. The exception to this rule is the signal—status in parts of the functional models for Digger the Dog and abscission. None of the third-level descriptors correctly describe the type of signal. The second-level descriptor of signal—status was therefore used. This is not expected to alter the results significantly.

  6. For 30 product models, 1000 GED analyses per product required about 3 days of compute time on a dual-CPU Dell Precision T7500 with 16 GB of RAM.

  7. An open-loop controller is simpler to implement than a closed-loop controller since it does not require a feedback mechanism, i.e., no control signal flow and no transitive loops of energy flow between functions such as control magnitude and channel.

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Acknowledgments

Andy Dong is a recipient of an Australian Research Council Future Fellowship (FT100100376). The author acknowledges the set of functional models provided by Professor Joshua Summers of Clemson University.

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  1. Faculty of Engineering and Information Technologies, The University of Sydney, Sydney, NSW, 2006, Australia

    Andy Dong

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Correspondence to Andy Dong.

Appendix: A* algorithm for graph edit distance

Appendix: A* algorithm for graph edit distance

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Dong, A. Functional lock-in and the problem of design transformation. Res Eng Design 28, 203–221 (2017). https://doi.org/10.1007/s00163-016-0234-3

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