Modeling and structuring design rationale to enable knowledge reuse

Siddharth, L.; Chakrabarti, Amaresh; Ranganath, R. V.

doi:10.1002/sys.21515

Cited by 6 publications

(3 citation statements)

References 32 publications

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“…Scholars initially aimed to extract design requirements as meaningful terms, phrases and segments from internal reports to reuse these in the design process. Such requirements shall also be derived from the past cases of failure in which violated constraints were recorded (Siddharth, Chakrabarti, and Ranganath 2019a). As mentioned below, scholars initially encountered some challenges while extracting design requirements from internal reports.…”

Section: Requirement Extractionmentioning

confidence: 99%

“…To represent design rationale, 11 scholars have proposed a variety of prescriptivegeneric ontologies (Ebrahimipour, Rezaie, and Shokravi 2010;Liu et al 2010;Zhang et al 2013;Aurisicchio, Bracewell, and Hooey 2016;Siddharth, Chakrabarti, and Ranganath 2019a) that build upon the fundamental idea of entity-relationship models (Taleb-Bendiab et al 1993). While generic ontologies are capable of capturing rationale from a variety of domains, the performances of these in terms of knowledge retrieval are expected to be low due to the level of abstraction.…”

Section: Ontology Constructionmentioning

confidence: 99%

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Natural language processing in-and-for design research

2022

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We review the scholarly contributions that utilise natural language processing (NLP) techniques to support the design process. Using a heuristic approach, we gathered 223 articles that are published in 32 journals within the period 1991–present. We present state-of-the-art NLP in-and-for design research by reviewing these articles according to the type of natural language text sources: internal reports, design concepts, discourse transcripts, technical publications, consumer opinions and others. Upon summarising and identifying the gaps in these contributions, we utilise an existing design innovation framework to identify the applications that are currently being supported by NLP. We then propose a few methodological and theoretical directions for future NLP in-and-for design research.

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Section: Requirement Extractionmentioning

confidence: 99%

Section: Ontology Constructionmentioning

confidence: 99%

Natural language processing in-and-for design research

2022

Self Cite

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“…Often information about the prototype and product development process is sparse, or known only to the team or individuals working on the project, as there is little to no expectation that it will be communicated to others (McAlpine et al, 2006). However, the information relating to the process of product development, rather than the information pertaining to the individual prototypes can yield interesting insights and learnings to improve future development activities (Barhoush et al, 2019;Bracewell et al, 2009;Siddharth et al, 2020). Soomro et al (2021) analysed six technologies aimed at supporting the capture of prototyping activities, categorising them into three groups: software, hardware and hybrid approaches.…”

Section: Prototypesmentioning

confidence: 99%

Pro2Booth: Towards an Improved Tool for Capturing Prototypes and the Prototyping Process

et al. 2022

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The act of prototyping is a key element of the design process. However, capturing information on how prototypes evolve and influence one another is a complex problem. This paper presents an iterative evolution to a prototyping capture platform, termed Pro2Booth, designed to address the shortcomings encountered in previous systems. The Pro2Booth hardware and online software described in this paper provide a new baseline for future innovation and exploration of the prototype capture process.

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A system concept representation framework and its testing on patents, urban architectural patterns, and software patterns

Menshenin

Crawley

2020

Systems Engineering

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The development of a concept for a system is a key step toward creating the system's architecture. Most previous concept development approaches focus on the procedures for the conceptual design activity—the sequence of activities and tasks. Our work is motivated by the desire to elaborate in details the notional content of a system concept and to provide the means of encoding and analyzing it in a digital environment. The objective of this work is to develop a system concept representation framework that can systematically represent the concept's constituents, their definitions, and interconnections. In order to demonstrate the utility of this framework, we have conducted three studies: mapped eight selected US patents, nine selected urban architectural patterns, and three selected software patterns to the framework. Patents, urban architectural patterns, and software patterns each contain a rich body of knowledge about the system they describe, and therefore they must logically contain a description of the concepts underlying them. We show that the main features of proposed framework can be found in patents, urban architectural patterns, and software patterns. The major utility of the framework is that it provides the means to encode existing system concepts and to inform the conceptual design of new systems, contributing to the INCOSE Model‐Based Conceptual Design initiative.

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Modeling and structuring design rationale to enable knowledge reuse

Cited by 6 publications

References 32 publications

Natural language processing in-and-for design research

Natural language processing in-and-for design research

Pro2Booth: Towards an Improved Tool for Capturing Prototypes and the Prototyping Process

A system concept representation framework and its testing on patents, urban architectural patterns, and software patterns

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