Integrating Target Costing Into Perception-Based Concept Evaluation of Complex and Large-Scale Systems Using Simultaneously Decomposed QFD

In the conceptual design phase, engineers may need to perceptually screen and prioritize feasible design concepts by their potential to fulfill both customer and financial requirements. This paper presents a system design methodology that integrates perception-based concept evaluation and target costing of complex and large-scale systems. The methodology decomposes a system into modules and evaluates each module concept with its target requirements and cost. This method proposes the decomposition of quality function deployment matrices simultaneously for both requirements and structure in order to allocate the worth and target cost of the modules in a system. Developed from module concepts that satisfy their target requirements and cost, this new system should better satisfy both customer and financial requirements.

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Decentralized control for large scale systems with inherently coupled subsystems

Journal of Vibration and Control ◽

10.1177/10775463211034953 ◽

2021 ◽

pp. 107754632110349

Author(s):

Filip Svoboda ◽

Kristian Hengster-Movric ◽

Martin Hromčík

Keyword(s):

Design Methodology ◽

Large Scale ◽

Single Agent ◽

Control Design ◽

Linear Matrix ◽

Multi Agent Systems ◽

Large Scale Systems ◽

Coupled Subsystems ◽

Multi Agent ◽

Interaction Topology

This paper brings a novel scalable control design methodology for Large-Scale Systems. Such systems are considered as multi-agent systems with inherent interactions between neighboring agents. The presented design methodology uses single-agent dynamics and their interaction topology, rather than relying on the model of the entire system. The dimension of the design problem therefore remains the same with growing number of agents. This allows a feasible control design even for large systems. Moreover, the proposed design is based on simple Linear Matrix Inequalities, efficiently solvable using standard computational tools. Numerical results validate the proposed approach.

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Sensitivity Analysis of the Rating Scales and Worth Calculation Schemes Used in QFD Matrices

Design Engineering ◽

10.1115/imece2004-61500 ◽

2004 ◽

Author(s):

Shun Takai ◽

Kosuke Ishii

Keyword(s):

Sensitivity Analysis ◽

Quality Function Deployment ◽

Rating Scales ◽

Rating Scale ◽

Upper Bounds ◽

Specific Pattern ◽

House Of Quality ◽

Customer Requirements ◽

Design Concepts ◽

Concept Evaluation

Quality Function Deployment (QFD) is matrix method that identifies relative worth of product requirements from the customer requirements and their importance. Understanding the relative worth enables engineers to evaluate the potential of design concepts to achieve important requirements. In a QFD matrix called “House of Quality” or QFD I, engineers assess correlations between product requirements and customer requirements using a linear (e.g., 1–3–5) or an exponential (e.g., 1–3–9) rating scale. The exponential scale assigns product requirements that have large correlations with customer requirements a higher ratings of 9 instead of 5, and therefore, gives them larger relative worth. This paper studies how the choice of linear 1–3–5 and exponential 1–3–9 rating scales changes the relative worth of product requirements. To avoid being restricted to any specific pattern of a QFD matrix, this paper uses simulations and analytic approaches to obtain distributions of changes of relative worth, and to calculate the upper bounds of these changes. Finally, in an illustrative example, the authors integrate QFD and concept evaluation activities and provide a case in which the choice of rating scale in a QFD I matrix changes the optimal concept.

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Adaptive unscented transform for uncertainty quantification in EMC large-scale systems

COMPEL The International Journal for Computation and Mathematics in Electrical and Electronic Engineering ◽

10.1108/compel-10-2012-0212 ◽

2014 ◽

Vol 33 (3) ◽

pp. 914-926 ◽

Cited By ~ 4

Author(s):

Moises Ferber ◽

Christian Vollaire ◽

Laurent Krähenbühl ◽

João Antônio Vasconcelos

Keyword(s):

Uncertainty Quantification ◽

Design Methodology ◽

Large Scale ◽

Uncertainty Propagation ◽

Stochastic Collocation ◽

Content Type ◽

Large Scale Systems ◽

Unscented Transform ◽

Efficient Alternative ◽

Input Variables

Purpose – The purpose of this paper is to introduce a novel methodology for uncertainty quantification in large-scale systems. It is a non-intrusive approach based on the unscented transform (UT) but it requires far less simulations from a EM solver for certain models. Design/methodology/approach – The methodology of uncertainty propagation is carried out adaptively instead of considering all input variables. First, a ranking of input variables is determined and after a classical UT is applied successively considering each time one more input variable. The convergence is reached once the most important variables were considered. Findings – The adaptive UT can be an efficient alternative of uncertainty propagation for large dimensional systems. Originality/value – The classical UT is unfeasible for large-scale systems. This paper presents one new possibility to use this stochastic collocation method for systems with large number of input dimensions.

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