A decision support framework for flexible system design

Olewnik, Andrew; Lewis, Kemper

doi:10.1080/09544820500274019

Cited by 63 publications

(50 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Both flexibility of features to model adaptive behavior, and integration of impacts from the various physical domains are open to further development [111]. In parallel, it would be interesting to investigate opportunities to enrich capabilities of building performance simulation tools, by taking benefit from recent progress in those design methods, especially developed to aid in the design of adaptive systems [51], [112], [113].…”

Section: Design and Decision Supportmentioning

confidence: 99%

Climate adaptive building shells: State-of-the-art and future challenges

Loonen

Trcka

Cóstola

et al. 2013

Renewable and Sustainable Energy Reviews

500

270

View full text Add to dashboard Cite

Section: Design and Decision Supportmentioning

confidence: 99%

Climate adaptive building shells: State-of-the-art and future challenges

Loonen

Trcka

Cóstola

et al. 2013

Renewable and Sustainable Energy Reviews

500

270

View full text Add to dashboard Cite

“…More recently, research into flexible, reconfigurable, and evolvable systems design is also relevant to our paper (e.g., Olewnik and Lewis 2006;Ferguson et al 2007;Silver and deWeck 2007). Flexible and reconfigurable systems are capable of undergoing changes in order to meet new objectives, function effectively in varying operating environments, and deliver value in dynamic market conditions.…”

Section: Literature Reviewmentioning

confidence: 98%

Parametric design adaptation for competitive products

Yassine

2010

J Intell Manuf

View full text Add to dashboard Cite

Very often product development is seen as a process where designers iterate through several design cycles until they converge upon a design that satisfies all of the necessary requirements-design within a single generation. If one takes the view that products change (i.e. adapt and evolve), a broader view must be adopted to capture the drivers of design adaptation across multiple product generations. This paper offers a new multi-generation conceptual framework of parametric design adaptation for consumer products, called the Artisan-Patron (AP) framework, and a complementary computational model. The AP framework captures the interaction between manufacturers (the Artisan) and consumers (the Patron) by structuring the various relevant information (e.g., consumer taste, government policy, cost of raw materials, etc.). Additionally, based on this framework, a corresponding computational model is developed, which allows engineers to find optimal settings for the design variables in a dynamic multi-generation environment. The utility of the conceptual framework and the computational model is demonstrated by considering the parametric design adaptation of the automobile with respect to two design parameters-engine horsepower and weight-based on historical automotive industry data. List of symbols NTotal number of competitive products (or manufacturers) within a given productFuel economy at 0-60 mph acceleration time sfMeasure of safety which is related to the fatality rate in two-car crashes hpVehicle aggregate horsepower wVehicle weight A Set of critical-to-value attributes (CVA) in a productperformance z a,I Ideal attribute setting where the consumer is unwilling to pay for further improvement z a,C Critical setting for attributes where the consumer is unwilling to purchase the product even if all other attributes are at an ideal setting z a,0 Baseline attribute settings (i.e. for the baseline product) z f e t Estimated average fuel economy (fe) at time t z at t Estimated average acceleration time (at) at time t z s f t Estimated average safety (sf) at time t z C AF E t Sales-weighted (car & truck) adjusted fuel economy standard for the manufacturer's product mix at time t R z A i,t Reward value based on z A i,t 123 542 J Intell Manuf (2012) 23:541-559 R z A i,t Estimate of R z A i,t B Set of decision/design variables in a product design b A single decision variable, b ∈ B x B i,tVector of design or decision variables for product i at time t:t ) Upper (and lower) bounds on design variables of product i at time t x hp t Vehicle aggregate horsepower at time t x w t Vehicle aggregate weight at time t ccost (estimate) for product i at time t c weight t Estimated cost as a function of overall automobile weight at time t (average for all manufacturers) c engine t Estimated cost associated with delivering engine horsepower at time t (average for all manufacturers) c C AF E t Estimated CAFE policy penalty formula at time t (average for all manufacturers) V 0 Baseline value (i.e. at reference point) V i,t Value of product i ...

show abstract

“…Adaptable products can be evaluated by their capabilities of change in the operation stage such as adaptabilities (or flexibilities) (de Neufville and Scholtes 2011;Inkermann, Stechert, and Vietor 2013). Adaptability is used to evaluate the capability of a product to be changed in the operation stage to satisfy different requirements (Gu, Hashemina, and Nee 2004;Olewnik and Lewis 2006). For an OAP, both the specific add-on modules with specific functions and the unknown add-on modules without specified functions are considered.…”

Section: Robustness Of An Oapmentioning

confidence: 99%

Adaptable design of open architecture products with robust performance

Zhang

Xue

2015

Journal of Engineering Design

View full text Add to dashboard Cite

Adaptable design is an approach to design adaptable products whose modules/configurations and parameter values can be changed during an operation stage to satisfy different customer requirements. An open architecture product is an adaptable product with open interfaces to allow the third-party vendors to develop new add-on modules and connect these add-on modules through the open interfaces. In this work, an open architecture adaptable product is modelled by a platform, alternative add-on modules, and open interfaces to connect the add-on modules with the platform. Both the specific add-on modules that need to be designed at the product development stage and the unknown add-on modules that could be added in the future are considered. In this research, a novel robust design approach is introduced to identify the optimal design of an open architecture adaptable product whose functional performance measures are the least sensitive to variations of the product and operating parameters due to uncertainties. First, characteristics of open architecture adaptable products are discussed. Methods for modelling of platform, add-on modules, and open interfaces are then introduced. A multi-level optimisation method is subsequently explained to identify the optimal design configuration and parameters considering product performance measures and their variations.

show abstract

A decision support framework for flexible system design

Cited by 63 publications

References 22 publications

Climate adaptive building shells: State-of-the-art and future challenges

Climate adaptive building shells: State-of-the-art and future challenges

Parametric design adaptation for competitive products

Adaptable design of open architecture products with robust performance

Contact Info

Product

Resources

About