Set-based design of mechanical systems with design robustness integrated

Qureshi, Ahmed Jawad; Dantan, Jean‐Yves; Bruyère, Jérôme; Bigot, Régis

doi:10.1504/ijpd.2014.060037

Cited by 4 publications

(2 citation statements)

References 33 publications

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“…developed a robust design approach to SBD by integrating existential and universal quantifiers from the quantifier CSP (QCSP) 75 with interval arithmetic to explore and separate the robust solutions from the initial design space. They later revised and expanded upon their method in 2014 76 . Their updated QCSP model is defined as a tuple 〈QV, QN, D, C〉:

Q V = {q_{1} v_{1}, \dots, q_{n} v_{n}}

is the set of quantified design variables,

Q N = {q_{1} n_{1}, \dots, q_{n} n_{n}}

is the set of quantified uncertainty variables,

D = {d_{1}, \dots, d_{n}}

is a set of domains,

C = {c_{1}, \dots, c_{n}}

is a set of constraints.…”

Section: Quantitative Methodsmentioning

confidence: 99%

“…Publication distribution per year expanded upon their method in 2014. 76 Their updated QCSP model is defined as a tuple 〈QV, QN, D, C〉: In 2013, Yannou et al 62 developed a SBD approach for designing a single product or a family of products that combines CSP with market research. Their approach used CSP methods with several usage coverage indices which assesses the feasibility of a given product or product family in achieving the expected set of usage scenarios.…”

Section: Constraint Satisfaction Problems (Csp)mentioning

confidence: 99%

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Survey on set‐based design (SBD) quantitative methods

Dullen

Verma

Blackburn

et al. 2021

Systems Engineering

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Product development efforts now more than ever are in need of methodologies that can address the challenges of increased system complexities, shortening time to market, increased demands in mass customization, market instabilities, geographical barriers, improved innovation, and adaptability to emerging technologies. To address these challenges most companies will need to make key decisions early in the product development life-cycle. In this early phase there are high levels of information uncertainty and information ambiguity. Under these circumstances many companies will converge too early to a point design (Point Based Design-PBD) which will lead to increased cost and schedule delays due to reworking the design later in the product development life cycle. To overcome these challenges many researchers have proposed the Set-Based Design (SBD) methodology. However, there has been limited guidance on how to define, reason, and narrow sets while improving the level of abstraction of the design.To address such concerns, a literature review was conducted. The contributions of this research include: (1) aggregated literature from over 100 sources on quantitative methods (QM) that has not been considered SBD but does support set-based thinking,(2) consolidated body of knowledge on QM to help industrial practitioners implement SBD, (3) defined gaps and opportunities for future research, and (4) defined strengths and limitations of QM and techniques to define, reason and narrow sets.

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Q V = {q_{1} v_{1}, \dots, q_{n} v_{n}}

is the set of quantified design variables,

Q N = {q_{1} n_{1}, \dots, q_{n} n_{n}}

is the set of quantified uncertainty variables,

D = {d_{1}, \dots, d_{n}}

is a set of domains,

C = {c_{1}, \dots, c_{n}}

is a set of constraints.…”

Section: Quantitative Methodsmentioning

confidence: 99%

Section: Constraint Satisfaction Problems (Csp)mentioning

confidence: 99%

Survey on set‐based design (SBD) quantitative methods

Dullen

Verma

Blackburn

et al. 2021

Systems Engineering

View full text Add to dashboard Cite

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Set-based design: a review and new directions

2020

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Set-based design (SBD), sometimes referred to as set-based concurrent engineering (SBCE), has emerged as an important component of lean product development (LPD) with all researchers describing it as a core enabler of LPD. Research has explored the principles underlying LPD and SBCE, but methodologies for the practical implementation need to be better understood. A review of SBD is performed in this article in order to discover and analyse the key aspects to consider when developing a model and methodology to transition to SBCE. The publications are classified according to a new framework, which allows us to map the topology of the relevant SBD literature from two perspectives: the research paradigms and the coverage of the generic creative design process (Formulation–Synthesis–Analysis–Evaluation–Documentation–Reformulation). It is found that SBD has a relatively low theoretical development, but there is a steady increase in the diversity of contributions. The literature abounds with methods, guidelines and tools to implement SBCE, but they rarely rely on a model that is in the continuum of a design process model, product model or knowledge-based model with the aim of federating the three Ps (People–Product–Process) towards SBCE and LPD in traditional industrial contexts.

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Scalable Set-Based Design Optimization and Remanufacturing for Meeting Changing Requirements

Handawi

Andersson

Panarotto

et al. 2020

Journal of Mechanical Design

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Design requirements are often uncertain in the early stages of product development. Set-based design (SBD) is a paradigm for exploring, and keeping under consideration, several alternatives so that commitment to a single design can be delayed until requirements are settled. In addition, requirements may change over the lifetime of a component or a system. Novel manufacturing technologies may enable designs to be remanufactured to meet changed requirements. By considering this capability during the (SBD) optimization process, solutions can be scaled to meet evolving requirements and customer specifications even after commitment. Such an ability can also support a circular economy paradigm based on the return of used or discarded components and systems to working condition. We propose a (SBD) methodology to obtain scalable optimal solutions that can satisfy changing requirements through remanufacturing. We first use design optimization and surrogate modeling to obtain parametric optimal designs. This set of parametric optimal designs is then reduced to scalable optimal designs by observing a set of transition rules for the manufacturing process used (additive or subtractive). The methodology is demonstrated by means of a structural aeroengine component that is remanufactured by direct energy deposition of a stiffener to meet higher loading requirements

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Set-based design of mechanical systems with design robustness integrated

Cited by 4 publications

References 33 publications

Survey on set‐based design (SBD) quantitative methods

Survey on set‐based design (SBD) quantitative methods

Set-based design: a review and new directions

Scalable Set-Based Design Optimization and Remanufacturing for Meeting Changing Requirements

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