From User Requirements to Commonality Specifications: An Integrated Approach to Product Family Design

Simpson, Timothy W.; Bobuk, Aaron; Slingerland, Laura A.; Brennan, Sean; Logan, Drew G.; Reichard, Karl

doi:10.2514/6.2010-9173

Cited by 8 publications

(12 citation statements)

References 37 publications

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“…As a result, genetic algorithms are often used to solve the product family optimization due to its flexibility in their problem formulation, capability to handle multiple objectives, and their ability to run in parallel computing environments [6], [9]. We implement NSGA-II [10] to solve a combinatorial multi-objective optimization problem.…”

Section: Resultsmentioning

confidence: 99%

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Module Family Design for Modular Product

Adhitama

2015

Advances in Intelligent Systems and Computing

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Abstract. Modular structure based products have been chosen by industries to provide sufficient variety of their products to the market. In this work, a multiobjective product family design that aims to develop a module family for a modular product is discussed. Enterprise considerations such as market share and cost-savings benefits are integrated with the product family design. A representation scheme is introduced to enable us to integrate the qualitative market segmentation grid (MSG) with the scalability evaluation which plays a significant role in determining the appropriate configuration of the module product as well as the final product in different market niches. The combinatorial problem with a large number of module configurations is solved through the implementation of genetic algorithm of NSGA-II. The design of a family of applicationspecific integrated circuits (ASIC) for a modular structure based electronic control unit (ECU) is used to demonstrate the proposed approach.

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Section: Resultsmentioning

confidence: 99%

“…the set of features, components or subsystems that remain constant from product to product, within a given product family) [6]. The variants or derivatives are derived from the product platform through addition, removal, or substitution of one or more modules (i.e.…”

Section: Introductionmentioning

confidence: 99%

Module Family Design for Modular Product

Adhitama

2015

Advances in Intelligent Systems and Computing

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“…This tool requires the development of QFD, which is a series of interrelated matrices that map first "customer requirements" to "engineering metrics" and then to "product sub-systems". GVI is calculated by summing up the potential redesign work as a result of changes in the product requirements [21]. GVI is an indicator of the amount of redesign required for future product designs.…”

Section: Modularisation In Constructionmentioning

confidence: 99%

“…the "functional flow block diagram" [14], [15], the "dependency structure matrix" (DSM) [15], [16]. "extended implementation structure matrix" [17], [18], the "modular identification matrix" (MIM) [11], "axiomatic design" [19], and the "modular product platform" via the "generational variance index" (GVI) [20], [21]. This paper focuses on DSM, MIM, and GVI, as these are commonly used in other engineering disciplines (e.g.…”

Section: Modularisation In Constructionmentioning

confidence: 99%

Evaluating Modularisation Tools in Construction

Wee¹,

Aurisicchio²,

Starzyk³

2017

Proceedings of the International Symposium on Automation and Robotics in Construction (IAARC)

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The construction industry is undergoing a new wave of industrialisation driven by the shift towards off-site construction and the growing interest in masscustomisation of building systems. On one side the industry is acquiring new manufacturing and automation capabilities. On the other, it has a need to understand how to develop flexible yet efficient product systems that can be more adaptable to changing situations. To address this problem the industry is starting to adopt modularisation strategies. Modularisation is useful to handle product variations and effective at reducing redesign work. Research on the application of modularisation tools in construction has been limited. There is a need to examine how modularisation tools can be used to meet construction objectives and generate efficient solutions. This paper examines the application of three modularisation tools, namely the dependency structure matrix (DSM), the modular identification matrix (MIM), and the generational variance index (GVI).A case study of a modular plant-room has been used to determine the effectiveness of the three tools at addressing fifteen modular design drivers. Each of the tools was found to address a different set of modular drivers. DSM and GVI provide rigorous solutions but they address only specific modular drivers. MIM has a more holistic approach to modularity and supports a wider set of modular drivers. However, it lacks technical rigour in determining modules. Overall, DSM and GVI, compared to MIM, are more technical tools to handle modular drivers.This research sugests that the three tools can be used in an integrated manner. MIM can be used in the early phases of modular construction management because of its ability to capture multiple and interdisciplinary modular drivers. The application of DSM and GVI should be considered for more robust solutions in respect to their individual modular drivers.

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“…Many researchers studied techniques for derivative design. These research efforts considered the whole set of design variables and designed the baseline and derivatives simultaneously [1][2][3][4][5][6][7][8][9][10]. Richard et al, Robert et al, and Deepak et al identified the important parameters for the family design by applying the market requirement analysis [1, 2, and 3]…”

Section: Introductionmentioning

confidence: 99%

Aircraft derivative design optimization considering global sensitivity and uncertainty of analysis models

Park¹,

Chung²,

Lee³

2016

International Journal of Aeronautical and Space Sciences

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Aircraft manufacturing companies have to consider multiple derivatives to satisfy various market requirements. They modify or extend an existing aircraft to meet new market demands while keeping the development time and cost to a minimum. Many researchers have studied the derivative design process, but these research efforts consider baseline and derivative designs together, while using the whole set of design variables. Therefore, an efficient process that can reduce cost and time for aircraft derivative design is needed. In this research, a more efficient design process is proposed which obtains global changes from local changes in aircraft design in order to develop aircraft derivatives efficiently. Sensitivity analysis was introduced to remove unnecessary design variables that have a low impact on the objective function. This prevented wasting computational effort and time on low priority variables for design requirements and objectives. Additionally, uncertainty from the fidelity of analysis tools was considered in design optimization to increase the probability of optimization results. The Reliability Based Design Optimization (RBDO) and Possibility Based Design Optimization (PBDO) methods were proposed to handle the uncertainty in aircraft conceptual design optimization. In this paper, Collaborative Optimization (CO) based framework with RBDO and PBDO was implemented to consider uncertainty. The proposed method was applied for civil jet aircraft derivative design that increases cruise range and the number of passengers. The proposed process provided deterministic design optimization, RBDO, and PBDO results for given requirements.

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From User Requirements to Commonality Specifications: An Integrated Approach to Product Family Design

Cited by 8 publications

References 37 publications

Module Family Design for Modular Product

Module Family Design for Modular Product

Evaluating Modularisation Tools in Construction

Aircraft derivative design optimization considering global sensitivity and uncertainty of analysis models

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