Biology is recognized as an excellent source of analogies and stimuli for engineering design. Previous work focused on the systematic identification of relevant biological analogies by searching for instances of functional keywords in biological information in natural-language format. This past work revealed that engineering keywords could not always be used to identify the most relevant biological analogies as the vocabularies between biology and engineering are sufficiently distinct. Therefore, a retrieval algorithm was developed to identify potential biologically meaningful keywords that are more effective in searching biological text than corresponding engineering keywords. In our current work, we applied and refined the retrieval algorithm to translate functional terms of the functional basis into biologically meaningful keywords. The functional basis is widely accepted as a standardized representation of engineering product functionality. Therefore, our keywords could serve as a thesaurus for engineers to find biological analogies relevant to their design problems. We also describe specific semantic relationships that can be used to identify biologically meaningful keywords in excerpts describing biological phenomena. These semantic relations were applied as criteria to identify the most useful biologically meaningful keywords. Through a preliminary validation experiment, we observed that different translators were able to apply the criteria to identify biologically meaningful keywords with a high degree of agreement to those identified by the authors. In addition, we describe how fourth-year undergraduate mechanical engineering students used the biologically meaningful keywords to develop concepts for their design projects.

Over the last two decades, consumers have become increasingly aware and desiring of sustainable products. However, little attention has been paid to developing conceptual design methods that explicitly take into account environmental impact. This paper contributes a method of automated function component generation, and guided down-selection and decision-making based upon environmental impact. The environmental impact of functions has been calculated for 17 of the products found in the Design Repository using ReCiPe scoring in SimaPRO. A hierarchical Bayesian approach is used to estimate the potential environmental impacts of specific functions when realized into components. Previously, product environmental impacts were calculated after a product was developed to the component design stage. The method developed in this paper could be used to provide a criticality ranking based on which functional solutions historically have the greatest risk of causing high environmental impact. The method is demonstrated using a simple clock system as an example. A comparative case study of two phone chargers for use in third-world countries demonstrates the decision-making capabilities of this method, and shows that it is possible to compare the environmental impact of alternative function structures during the conceptual stage of design. With the method presented in this paper, it is now possible to make early functional modeling design decisions specifically taking into account historical environmental impact of functionally similar products.

The objective of this research is to support DfX considerations in the early phases of design. In order to do conduct DfX, designers need access to pertinent downstream knowledge that is keyed to early stage design activities and problem knowledge. Product functionality is one such “key” connection between early understanding of the design problem and component choices which dictate product performance and impact, and repositories of design knowledge are one way to archive such design knowledge. However, curation of design knowledge is often a time-consuming activity requiring expertise in product modeling. In this paper, we explore a method to automate the populating of design repositories to support the overall goal of having up-to-date repositories of product design knowledge. To do this, we mine information from an existing repository to better understand the relationships between the components, functions, and flows of products. The resulting knowledge can be applied to automate functional decompositions once a product's components have been entered and thus reliably provide that “key” between early design activities and the later, component dependent characteristics.

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This paper presents a method for the systematic and automated design of flexible organic linkers for construction of metal organic-frameworks (MOFs) in which flexibility, compliance, or other mechanically exotic properties originate at the linker level rather than from the framework kinematics. Our method couples a graph grammar method for systematically generating linker like molecules with molecular dynamics modeling of linkers' mechanical response. Using this approach we have generated a candidate pool of >59,000 hypothetical linkers. We screen linker candidates according to their mechanical behaviors under large deformation, and extract fragments common to the most performant candidate materials. To demonstrate the general approach to MOF design we apply our system to designing linkers for pressure switching MOFs-MOFs that undergo reversible structural collapse after a stress threshold is exceeded.