A Guide to Property-Based Interoperability

TitleA Guide to Property-Based Interoperability
Publication TypeTechnical Report
Year of Publication2017
AuthorsBehandish, M., & Shapiro V.

Limited or lacking interoperability has emerged as a central unsolved technical problem in computational design, synthesis, analysis, optimization, and manufacturing. In addition to being a significant technological barrier, it has become a major economic problem within the past two decades, costing the US manufacturing industry billions of dollars every year. This guide aims to introduce the reader with challenges and opportunities that are common to most interoperability scenarios in computational design and manufacturing. Its main purpose is to provide the engineers, researchers, and other technical professionals with a systematic framework to uniformly think about, formulate, and solve interoperability problems, validate the solutions, and conceptualize extensions. The central tenet of the framework is the notion of correspondence between representations and algorithms that are deemed interchangeable with respect to explicitly declared properties. The concept of ‘property-based’ interoperability is introduced in terms of the invariance of essential properties in a given data exchange scenario. The main focus will be on geometric properties, which serve as a surrogate to various physical, material, fabrication process, and other properties pertinent to design and manufacturing applications. We provide concrete usecase scenarios for geometric interoperability to serve as examples of how the generic framework is instantiated into different applications and solution methods.


This project is supported by the Defense Advanced Research Projects Agency (DARPA) under cooperative agreement HR0011-16-2-0042, and National Science Foundation grant CMMI-1547189. The content does not necessarily reflect the position or the policy of the Government, and no official endorsement should be inferred. The authors are thankful to Saigopal Nelaturi from PARC, Andrew Taber from Intact Solutions, Xingchen Liu from ICSI, and Randi Wang from UW-Madison, and Vaidyanathan Thiagarajan from MathWorks for the discussions that contributed to the insights in this report. The naming of commercial products is for exemplification only and does not imply recommendation over other products. The responsibility of any omissions or errors solely lies with the authors. 

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