Frameworks for organising design performance metrics

Lucero, Briana; Linsey, Julie; Turner, Cameron J.

doi:10.1080/09544828.2015.1135235

Cited by 13 publications

(19 citation statements)

References 24 publications

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“…The Design-Analogy Performance Parameter System (D-APPS) is a tool that computationally identifies design analogies (Lucero, 2014;Lucero et al, 2014Lucero et al, , 2016. D-APPS, in its simplest form, is an analogy "search engine" that returns analogies to the engineer based on the specific performance parameters and critical chain models of the design problem and the analogical solutions.…”

Section: Function Modeling For Design Analogiesmentioning

confidence: 99%

Transforming functional models to critical chain models via expert knowledge and automatic parsing rules for design analogy identification

Agyemang

Linsey

Turner

2017

AIEDAM

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Critical chains composed of critical flows and functions have been demonstrated as an effective qualitative analogy retrieval approach based on performance metrics. In prior work, engineers used expert knowledge to transform functional models into critical chain models, which are abstractions of the functional model. Automating this transformation process is highly desirable so as to provide for a robust transformation method. Within this paper, two paradigms for functional modeling abstraction are compared. A series of pruning rules provide an automated transformation approach, and this is compared to the results generated previously through an expert knowledge approach. These two approaches are evaluated against a set of published functional models. The similarity of the resulting transformation of the functional models into critical chain models is evaluated using a functional chain similarity metric, developed in previous work. Once critical chain models are identified, additional model evaluation criteria are used to evaluate the utility of the critical chain models for design analogy identification. Since the functional vocabulary acts as a common language among designers and engineers to abstract and represent critical design artifact information, analogous matching can be made about the functional vocabulary. Thus, the transformation of functional models into critical chain models enables engineers to use functional abstraction as a mechanism to identify design analogies. The critical flow rule is the most effective first step when automatically transforming a functional model to a critical chain model. Further research into more complex critical chain model architectures and the interactions between criteria is merited.

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Section: Function Modeling For Design Analogiesmentioning

confidence: 99%

Transforming functional models to critical chain models via expert knowledge and automatic parsing rules for design analogy identification

Agyemang

Linsey

Turner

2017

AIEDAM

Self Cite

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“…Beyond the focus of defining function vocabulary (Szykman et al, 1999; Hirtz et al, 2002; Kurtoglu et al, 2005), researchers have explored ways to use the function models in supporting engineering design activities. For instance, researchers have employed functional representations as a basis for analogy identification, including defining critical function flows to define solution elements (Lucero et al, 2014, 2016). Their definitions of critical function flows suggest that some elements of the functional model are more significant than others, which may be interpreted as being information rich.…”

Section: Function Modeling: a Backgroundmentioning

confidence: 99%

Comparing function structures and pruned function structures for market price prediction: An approach to benchmarking representation inferencing value

Gill

Summers

Turner

2017

AIEDAM

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Benchmarking function modeling and representation approaches requires a direct comparison, including the inferencing support by the different approaches. To this end, this paper explores the value of a representation by comparing the ability of a representation to support reasoning based on varying amounts of information stored in the representational components of a function structure: vocabulary, grammar, and topology. This is done by classifying the previously developed functional pruning rules into vocabulary, grammatical, and topological classes and applying them to function structures available from an external design repository. The original and pruned function structures of electromechanical devices are then evaluated for how accurately market values can be predicted using the graph complexity connectivity method. The accuracy is found to be inversely related to the amount of information and level of detail. Applying the topological rule does not significantly impact the predictive power of the models, while applying the vocabulary rules and the grammar rules reduces the accuracy of the predictions. Finally, the least predictive model set is that which had all rules applied. In this manner, the value of a representation to predict or answer questions is quantified.

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“…The work results in intangible indicators with finegrain refinement measurements. Concerning the product performance viewpoint, Lucero et al propose performance metrics that can be classified as quantifiable quantities employed by engineers (Lucero et al, 2016) (Lucero et al, 2014). Using a functional basis (Hirtz et al, 2002), they associate critical flow (CF) and functions as a critical pair to identify relevant performance metrics.…”

Section: Introductionmentioning

confidence: 99%

Use Design Performance Based on Use Requirements

Mahdjoub

Bluntzer

Bertin

2019

Proc. Int. Conf. Eng. Des.

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Industrial companies today must operate in an increasingly competitive world and need to rethink their organization accordingly. First, industrial strategies concerning technical management need to change and develop. If we consider the specific management of the product design process, managers use indicators during the lifecycle of the product concerning quality, cost and lead-times. For example, some new indicators concerning performance metrics related to cooperation issues among the design team are set up. Secondly, managers increasingly need to integrate the user in the early phases of the design process. The main benefit of this approach is that it allows designers to innovate more rapidly and robustly. The aim of this paper is to introduce a new approach making it possible to calculate a performance indicator concerning use design. The new indicator will help management drive the design process through the integration of use in the product, helping to enhance the usability of the future product, and consequently improve innovation.

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Frameworks for organising design performance metrics

Cited by 13 publications

References 24 publications

Transforming functional models to critical chain models via expert knowledge and automatic parsing rules for design analogy identification

Transforming functional models to critical chain models via expert knowledge and automatic parsing rules for design analogy identification

Comparing function structures and pruned function structures for market price prediction: An approach to benchmarking representation inferencing value

Use Design Performance Based on Use Requirements

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