Target Cascading in Optimal System Design

2000 ◽  
Author(s):  
Hyung Min Kim ◽  
Nestor F. Michelena ◽  
Panos Y. Papalambros ◽  
Tao Jiang
Keyword(s):  
Design Problem ◽  
Optimization Problem ◽  
Original Problem ◽  
Efficient Manner ◽  
Performance Targets ◽  
Coordination Strategy ◽  
Design Specifications ◽  
Target Cascading ◽  
Optimal System Design ◽  
Problem Design

Abstract Target cascading is a key challenge in the early product development stages of large complex artifacts: How to propagate the desirable top level design specifications (or targets) to appropriate specifications for the various subsystems and components in a consistent and efficient manner. Consistency means that all parts of the designed system should end up working well together, while efficiency means that the process itself should avoid iterations at later stages, which are costly in time and resources. In the present article target cascading is formalized in a process modeled as a multilevel optimal design problem. Design targets are cascaded down to lower levels using partitioning of the original problem into a hierarchical set of sub-problems. For each design problem at a given level, an optimization problem is formulated to minimize deviations from the propagated targets and thus achieve intersystem compatibility. A coordination strategy links all subproblem decisions so that the overall system performance targets are met. The process is illustrated with an explicit analytical problem and a simple chassis design model that demonstrates how the process can be applied in practice.

Target Cascading in Optimal System Design

2003 ◽  
Vol 125 (3) ◽  
pp. 474-480 ◽  
Author(s):  
Hyung Min Kim ◽  
Nestor F. Michelena ◽  
Panos Y. Papalambros ◽  
Tao Jiang
Keyword(s):  
Design Problem ◽  
Optimization Problem ◽  
Original Problem ◽  
Efficient Manner ◽  
Performance Targets ◽  
Coordination Strategy ◽  
Design Specifications ◽  
Target Cascading ◽  
Optimal System Design ◽  
Problem Design

Target cascading is a key challenge in the early product development stages of large complex artifacts: how to propagate the desirable top level design specifications (or targets) to appropriate specifications for the various subsystems and components in a consistent and efficient manner. Consistency means that all parts of the designed system should work well together, while efficiency means that the process itself should avoid iterations at later stages, which are costly in time and resources. In the present article target cascading is formalized by a process modeled as a multilevel optimal design problem. Design targets are cascaded down to lower levels using partitioning of the original problem into a hierarchical set of subproblems. For each design problem at a given level, an optimization problem is formulated to minimize deviations from the propagated targets and thus achieve intersystem compatibility. A coordination strategy links all subproblem decisions so that the overall system performance targets are met. The process is illustrated with an explicit analytical problem and a simple automotive chassis design model that demonstrates how the process can be applied in practice.

Solving a Two-stage Supply Chain Network Design Problem with Fixed Costs by a Hybrid Genetic Algorithm

2021 ◽  
Author(s):  
Ovidiu Cosma ◽  
Petrică C Pop ◽  
Cosmin Sabo
Keyword(s):  
Genetic Algorithm ◽  
Supply Chain ◽  
Network Design ◽  
Design Problem ◽  
Optimization Problem ◽  
Hybrid Genetic Algorithm ◽  
Network Design Problem ◽  
Supply Chain Network Design ◽  
Supply Chain Network ◽  
Fixed Costs

Abstract In this paper we investigate a particular two-stage supply chain network design problem with fixed costs. In order to solve this complex optimization problem, we propose an efficient hybrid algorithm, which was obtained by incorporating a linear programming optimization problem within the framework of a genetic algorithm. In addition, we integrated within our proposed algorithm a powerful local search procedure able to perform a fine tuning of the global search. We evaluate our proposed solution approach on a set of large size instances. The achieved computational results prove the efficiency of our hybrid genetic algorithm in providing high-quality solutions within reasonable running-times and its superiority against other existing methods from the literature.

scholarly journals An Enhanced Analytical Target Cascading and Kriging Model Combined Approach for Multidisciplinary Design Optimization

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Ping Jiang ◽  
Jianzhuang Wang ◽  
Qi Zhou ◽  
Xiaolin Zhang
Keyword(s):  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Kriging Model ◽  
Multidisciplinary Design ◽  
High Approximation ◽  
Engineering Systems ◽  
Analytical Target Cascading ◽  
Combined Approach ◽  
Coordination Strategy ◽  
Target Cascading

Multidisciplinary design optimization (MDO) has been applied widely in the design of complex engineering systems. To ease MDO problems, analytical target cascading (ATC) organizes MDO process into multilevels according to the components of engineering systems, which provides a promising way to deal with MDO problems. ATC adopts a coordination strategy to coordinate the couplings between two adjacent levels in the design optimization process; however, existing coordination strategies in ATC face the obstacles of complicated coordination process and heavy computation cost. In order to conquer this problem, a quadratic exterior penalty function (QEPF) based ATC (QEPF-ATC) approach is proposed, where QEPF is adopted as the coordination strategy. Moreover, approximate models are adopted widely to replace the expensive simulation models in MDO; a QEPF-ATC and Kriging model combined approach is further proposed to deal with MDO problems, owing to the comprehensive performance, high approximation accuracy, and robustness of Kriging model. Finally, the geometric programming and reducer design cases are given to validate the applicability and efficiency of the proposed approach.

scholarly journals Optimal design of a DC MHD pump by simulated annealing method

2014 ◽  
Vol 11 (2) ◽  
pp. 339-350
Author(s):  
Khadidja Bouali ◽  
Fatima Kadid ◽  
Rachid Abdessemed
Keyword(s):  
Simulated Annealing ◽  
Optimal Design ◽  
Objective Function ◽  
Design Problem ◽  
Design Methodology ◽  
Optimization Problem ◽  
Optimization Procedure ◽  
Simulated Annealing Method ◽  
Direct Interpretation ◽  
Annealing Method

In this paper a design methodology of a magnetohydrodynamic pump is proposed. The methodology is based on direct interpretation of the design problem as an optimization problem. The simulated annealing method is used for an optimal design of a DC MHD pump. The optimization procedure uses an objective function which can be the minimum of the mass. The constraints are both of geometrics and electromagnetic in type. The obtained results are reported.

A Formal Approach to Design Specifications

1990 ◽  
Author(s):  
Andrew Kusiak ◽  
Edward Szczerbicki
Keyword(s):  
Problem Solving ◽  
Conceptual Design ◽  
Design Problem ◽  
Functional Space ◽  
Requirements Specification ◽  
Synthesis Process ◽  
Formal Approach ◽  
Design Specifications ◽  
Level Of Abstraction ◽  
Active Interaction

Abstract In this paper a methodology for the specification stage in conceptual design is presented. It allows for problem solving in an active interaction with the designer. An important part of the proposed methodology is the requiremental and functional tree representing the overall logic and structure of the design problem. The specification stage aims at providing requirements and transforming them into functions of the designed object. It occurs at the highest level of abstraction and it must provide enough information to begin the synthesis process where functions are transformed into design components that are further synthesized into the designed object. The proposed approach was motivated by the following problems: specification of requirements, specification of functions, incorporation of logic into functional and requiremental trees, representation of requirements-functions interaction, and optimization in the functional space. The methodology presented is illustrated with examples.

Target Cascading: A Design Process for Achieving Vehicle Ride and Handling Targets

2001 ◽  
Author(s):  
D. Geoff Rideout ◽  
Jeffrey L. Stein ◽  
John B. Ferris
Keyword(s):  
Design Process ◽  
Design Methodology ◽  
Vehicle Design ◽  
Design Strategies ◽  
Tire Pressure ◽  
Simulation Tools ◽  
Performance Targets ◽  
Overall Design ◽  
Target Cascading ◽  
Ride And Handling

Abstract Vehicle dynamics are well understood by both academic researchers and automotive industries. And while modeling and simulation tools are still underutilized, they are becoming more frequently used in the vehicle design process. However, there is still lacking an overall design methodology that can link and integrate in a systematic fashion the design tasks of individual components or systems such that the vehicle performs as intended with a minimal number of design iterations. A process called Target Cascading, applied in the early stages of vehicle design, might serve as this systematic design methodology. In this paper, Target Cascading is evaluated for its ability to propagate top-level design specifications down to specifications for various subsystems and components in a vehicle design problem. More specifically, general ride and handling targets are set for a vehicle and these are cascaded down through the suspension, tire pressure and spring design levels by partitioning the original problem into a hierarchical set of subproblems. At a given level, an optimization problem is formulated to minimize deviations from the proposed targets and thus achieve intersystem compatibility. A coordination strategy links all subproblem decisions so that the overall supersystem performance targets are met. Results are presented that demonstrate Target Cascading’s utility in unearthing tradeoffs and incompatibilities among initial targets early in the vehicle development cycle. Throughout the paper, the Target Cascading process is compared to traditional vehicle design strategies for achieving ride and handling targets. Target Cascading appears to be a promising systematic technique for the design of vehicles to meet ride and handling specifications.

Quantifying the Impact of Domain Knowledge and Problem Framing on Sequential Decisions in Engineering Design

2018 ◽  
Vol 140 (10) ◽  
Author(s):  
Murtuza Shergadwala ◽  
Ilias Bilionis ◽  
Karthik N. Kannan ◽  
Jitesh H. Panchal
Keyword(s):  
Engineering Design ◽  
Information Acquisition ◽  
Design Problem ◽  
Domain Knowledge ◽  
Optimization Problem ◽  
Domain Specific ◽  
Problem Framing ◽  
Design Solutions ◽  
The Impact ◽  
Domain Independent

Many decisions within engineering systems design are typically made by humans. These decisions significantly affect the design outcomes and the resources used within design processes. While decision theory is increasingly being used from a normative standpoint to develop computational methods for engineering design, there is still a significant gap in our understanding of how humans make decisions within the design process. Particularly, there is lack of knowledge about how an individual's domain knowledge and framing of the design problem affect information acquisition decisions. To address this gap, the objective of this paper is to quantify the impact of a designer's domain knowledge and problem framing on their information acquisition decisions and the corresponding design outcomes. The objective is achieved by (i) developing a descriptive model of information acquisition decisions, based on an optimal one-step look ahead sequential strategy, utilizing expected improvement maximization, and (ii) using the model in conjunction with a controlled behavioral experiment. The domain knowledge of an individual is measured in the experiment using a concept inventory, whereas the problem framing is controlled as a treatment variable in the experiment. A design optimization problem is framed in two different ways: a domain-specific track design problem and a domain-independent function optimization problem (FOP). The results indicate that when the problem is framed as a domain-specific design task, the design solutions are better and individuals have a better state of knowledge about the problem, as compared to the domain-independent task. The design solutions are found to be better when individuals have a higher knowledge of the domain and they follow the modeled strategy closely.

Hierarchical Arrangement of Characteristics in Product Design Optimization Problems for Deeper Insight Into Optimized Results

2004 ◽  
Author(s):  
Masataka Yoshimura ◽  
Masahiko Taniguchi ◽  
Kazuhiro Izui ◽  
Shinji Nishiwaki
Keyword(s):  
Design Optimization ◽  
Product Design ◽  
Optimum Design ◽  
Design Problem ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Optimization Method ◽  
Hierarchical Level ◽  
Hierarchical Arrangement ◽  
Insight Into

This paper proposes a design optimization method for machine products that is based on the decomposition of performance characteristics, or alternatively, extraction of simpler characteristics, to accommodate the specific features or difficulties of a particular design problem. The optimization problem is expressed using hierarchical constructions of the decomposed and extracted characteristics and the optimizations are sequentially repeated, starting with groups of characteristics having conflicting characteristics at the lowest hierarchical level and proceeding to higher levels. The proposed method not only effectively enables achieving optimum design solutions, but also facilitates deeper insight into the design optimization results, and aids obtaining ideas for breakthroughs in the optimum solutions. An applied example is given to demonstrate the effectiveness of the proposed method.

Accelerated Geometry Accuracy Optimization of Additive Manufacturing Parts

2017 ◽  
Author(s):  
Amir M. Aboutaleb ◽  
Linkan Bian ◽  
Prahalad K. Rao ◽  
Mark A. Tschopp
Keyword(s):  
Additive Manufacturing ◽  
Optimization Problem ◽  
Principal Component ◽  
Geometric Features ◽  
Simulation Studies ◽  
Fused Filament Fabrication ◽  
Efficient Manner ◽  
Geometric Dimensioning And Tolerancing ◽  
Novel Approach

Despite recent advances in improving mechanical properties of parts fabricated by Additive Manufacturing (AM) systems, optimizing geometry accuracy of AM parts is still a major challenge for pushing this cutting-edge technology into the mainstream. This work proposes a novel approach for improving geometry accuracy of AM parts in a systematic and efficient manner. Initial experimental data show that different part geometric features are not necessary positively correlated. Hence, it may not be possible to optimize them simultaneously. The proposed methodology formulates the geometry accuracy optimization problem as a multi-objective optimization problem. The developed method targeted minimizing deviations within part’s major Geometric Dimensioning and Tolerancing (GD&T) features (i.e., Flatness, Circularity, Cylindricity, Concentricity and Thickness). First, principal component analysis (PCA) is applied to extract key components within multi-geometric features of parts. Then, experiments are sequentially designed in an accelerated and integrated framework to achieve sets of process parameters resulting in acceptable level of deviations within principal components of multi-geometric features of parts. The efficiency of proposed method is validated using simulation studies coupled with a real world case study for geometry accuracy optimization of parts fabricated by fused filament fabrication (FFF) system. The results show that optimal designs are achieved by fewer numbers of experiments compared with existing methods.

Vehicle Handling Dynamics Optimization Based in Passive Suspension Settings in Target Cascading Framework

2014 ◽  
Author(s):  
Juan C. Blanco ◽  
Luis E. Muñoz
Keyword(s):  
Optimal Design ◽  
Optimization Problem ◽  
Suspension System ◽  
Dynamics Simulation ◽  
Design Stage ◽  
Partial Geometry ◽  
Embodiment Design ◽  
Design Variables ◽  
Target Cascading

The vehicle optimal design is a multi-objective multi-domain optimization problem. Each design aspect must be analyzed by taking into account the interactions present with other design aspects. Given the size and complexity of the problem, the application of global optimization methodologies is not suitable; hierarchical problem decomposition is beneficial for the problem analysis. This paper studies the handling dynamics optimization problem as a sub-problem of the vehicle optimal design. This sub-problem is an important part of the overall vehicle design decomposition. It is proposed that the embodiment design stage can be performed in an optimal viewpoint with the application of the analytical target cascading (ATC) optimization strategy. It is also proposed that the design variables should have sufficient physical significance, but also give the overall design enough design degrees of freedom. In this way, other optimization sub-problems can be managed with a reduced variable redundancy and sub-problem couplings. Given that the ATC strategy is an objective-driven methodology, it is proposed that the objectives of the handling dynamics, which is a sub-problem in the general ATC problem, can be defined from a Pareto optimal set at a higher optimization level. This optimal generation of objectives would lead to an optimal solution as seen at the upper-level hierarchy. The use of a lumped mass handling dynamics model is proposed in order to manage an efficient optimization process based in handling dynamics simulations. This model contains detailed information of the tire properties modeled by the Pacejka tire model, as well as linear characteristics of the suspension system. The performance of this model is verified with a complete multi-body simulation program such as ADAMS/car. The handling optimization problem is presented including the proposed design variables, the handling dynamics simulation model and a case study in which a double wishbone suspension system of an off-road vehicle is analyzed. In the case study, the handling optimization problem is solved by taking into account couplings with the suspension kinematics optimization problem. The solution of this coupled problem leads to the partial geometry definition of the suspension system mechanism.

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