Sensitivity Analysis in Quantified Interval Constraint Satisfaction Problems

2015 ◽  
Vol 137 (4) ◽  
Author(s):  
Jie Hu ◽  
Yan Wang ◽  
Aiguo Cheng ◽  
Zhihua Zhong
Keyword(s):  
Sensitivity Analysis ◽  
Constraint Satisfaction ◽  
Information Gain ◽  
Constraint Satisfaction Problems ◽  
Design Parameters ◽  
Design Variables ◽  
Parameter Variations ◽  
Analytical Relations ◽  
Quantifying Uncertainty ◽  
Interval Valued

Interval is an alternative to probability distribution in quantifying uncertainty for sensitivity analysis (SA) when there is a lack of data to fit a distribution with good confidence. It only requires the information of lower and upper bounds. Analytical relations among design parameters, design variables, and target performances under uncertainty can be modeled as interval-valued constraints. By incorporating logic quantifiers, quantified constraint satisfaction problems (QCSPs) can integrate semantics and engineering intent in mathematical relations for engineering design. In this paper, a global sensitivity analysis (GSA) method is developed for feasible design space searching problems that are formulated as QCSPs, where the effects of value variations and quantifier changes for design parameters on target performances are analyzed based on several proposed metrics, including the indeterminacy of target performances, information gain of parameter variations, and infeasibility of constraints. Three examples are used to demonstrate the proposed approach.

Sensitivity Analysis in Quantified Interval Constraint Satisfaction Problems

2013 ◽  
Author(s):  
Jie Hu ◽  
Yan Wang
Keyword(s):  
Sensitivity Analysis ◽  
Constraint Satisfaction ◽  
Epistemic Uncertainty ◽  
Constraint Satisfaction Problems ◽  
Vehicle Design ◽  
Design Problems ◽  
Propagation Of Uncertainty ◽  
Interval Constraints ◽  
Interval Constraint ◽  
Interval Valued

Interval is an alternative to probability distribution in quantifying epistemic uncertainty for reliability analysis when there is a lack of data to fit a distribution with good confidence. It only requires the information of lower and upper bounds. The propagation of uncertainty is analyzed by solving interval-valued constraint satisfaction problems (CSPs). By introducing logic quantifiers, quantified constraint satisfaction problems (QCSPs) can capture more semantics and engineering intent than CSPs. Sensitivity analysis (SA) takes into account of variations associated with the structure and parameters of interval constraints to study to which extent they affect the output. In this paper, a global SA method is developed for QCSPs, where the effects of quantifiers and interval ranges on the constraints are analyzed based on several proposed metrics, which indicate the levels of indeterminacy for inputs and outputs as well as unsatisfiability of constraints. Two vehicle design problems are used to demonstrate the proposed approach.

Design Sensitivity Analysis of Nonlinear Multidisciplinary Multibody Systems in the MIXEDMODELS Platform

2007 ◽  
Author(s):  
Shilpa A. Vaze ◽  
Prakash Krishnaswami ◽  
James DeVault
Keyword(s):  
Sensitivity Analysis ◽  
Multibody Systems ◽  
Design Sensitivity ◽  
Differential Algebraic Equations ◽  
The State ◽  
Design Sensitivity Analysis ◽  
Design Parameters ◽  
State Variables ◽  
Sensitivity Coefficients ◽  
Design Variables

Most state-of-the-art multibody systems are multidisciplinary and encompass a wide range of components from various domains such as electrical, mechanical, hydraulic, pneumatic, etc. The design considerations and design parameters of the system can come from any of these domains or from a combination of these domains. In order to perform analytical design sensitivity analysis on a multidisciplinary system (MDS), we first need a uniform modeling approach for this class of systems to obtain a unified mathematical model of the system. Based on this model, we can derive a unified formulation for design sensitivity analysis. In this paper, we present a modeling and design sensitivity formulation for MDS that has been successfully implemented in the MIXEDMODELS (Multidisciplinary Integrated eXtensible Engine for Driving Metamodeling, Optimization and DEsign of Large-scale Systems) platform. MIXEDMODELS is a unified analysis and design tool for MDS that is based on a procedural, symbolic-numeric architecture. This architecture allows any engineer to add components in his/her domain of expertise to the platform in a modular fashion. The symbolic engine in the MIXEDMODELS platform synthesizes the system governing equations as a unified set of non-linear differential-algebraic equations (DAE’s). These equations can then be differentiated with respect to design to obtain an additional set of DAE’s in the sensitivity coefficients of the system state variables with respect to the system’s design variables. This combined set of DAE’s can be solved numerically to obtain the solution for the state variables and state sensitivity coefficients of the system. Finally, knowing the system performance functions, we can calculate the design sensitivity coefficients of these performance functions by using the values of the state variables and state sensitivity coefficients obtained from the DAE’s. In this work we use the direct differentiation approach for sensitivity analysis, as opposed to the adjoint variable approach, for ease in error control and software implementation. The capabilities and performance of the proposed design sensitivity analysis formulation are demonstrated through a numerical example consisting of an AC rectified DC power supply driving a slider crank mechanism. In this case, the performance functions and design variables come from both electrical and mechanical domains. The results obtained were verified by perturbation analysis, and the method was shown to be very accurate and computationally viable.

Optimal design of a parallel robotic gripper using enhanced multi-objective ant lion optimizer with a sensitivity analysis approach

2020 ◽  
Vol 40 (5) ◽  
pp. 703-721
Author(s):  
Golak Bihari Mahanta ◽  
Deepak BBVL ◽  
Bibhuti B. Biswal ◽  
Amruta Rout
Keyword(s):  
Sensitivity Analysis ◽  
Distribution Function ◽  
Design Parameters ◽  
Objective Functions ◽  
Content Type ◽  
Multi Objective ◽  
The Past ◽  
Design Variables ◽  
Pick And Place ◽  
Ant Lion

Purpose From the past few decades, parallel grippers are used successfully in the automation industries for performing various pick and place jobs due to their simple design, reliable nature and its economic feasibility. So, the purpose of this paperis to design a suitable gripper with appropriate design parameters for better performance in the robotic production systems. Design/methodology/approach In this paper, an enhanced multi-objective ant lion algorithm is introduced to find the optimal geometric and design variables of a parallel gripper. The considered robotic gripper systems are evaluated by considering three objective functions while satisfying eight constraint equations. The beta distribution function is introduced for generating the initial random number at the initialization phase of the proposed algorithm as a replacement of uniform distribution function. A local search algorithm, namely, achievement scalarizing function with multi-criteria decision-making technique and beta distribution are used to enhance the existing optimizer to evaluate the optimal gripper design problem. In this study, the newly proposed enhanced optimizer to obtain the optimum design condition of the design variables is called enhanced multi-objective ant lion optimizer. Findings This study aims to obtain optimal design parameters of the parallel gripper with the help of the developed algorithms. The acquired results are investigated with the past research paper conducted in that field for comparison. It is observed that the suggested method to get the best gripper arrangement and variables of the parallel gripper mechanism outperform its counterparts. The effects of the design variables are needed to be studied for a better design approach concerning the objective functions, which is achieved by sensitivity analysis. Practical implications The developed gripper is feasible to use in the assembly operation, as well as in other pick and place operations in different industries. Originality/value In this study, the problem to find the optimum design parameter (i.e. geometric parameters such as length of the link and parallel gripper joint angles) is addressed as a multi-objective optimization. The obtained results from the execution of the algorithm are evaluated using the performance indicator algorithm and a sensitivity analysis is introduced to validate the effects of the design variables. The obtained optimal parameters are used to develop a gripper prototype, which will be used for the assembly process.

Sensitivity Analysis in Yield Optimization of MEMS Tunable Capacitors

2006 ◽  
Author(s):  
Mohammad Shavezipur ◽  
Kumaraswamy Ponnambalam ◽  
Amir Khajepour ◽  
Seyed Mohammad Hashemi
Keyword(s):  
Sensitivity Analysis ◽  
Design Parameters ◽  
Arbitrary Distribution ◽  
Voltage Response ◽  
Effective Parameters ◽  
Yield Optimization ◽  
Tunable Capacitor ◽  
Tunable Capacitors ◽  
Design Variables ◽  
Final Yield

The fabrication of MEMS tunable capacitors faces many uncertainties in which the fabricated dimensions differ from nominal values. This deviation in a tunable capacitor may cause significant variation in the capacitance-voltage response. In this paper, the effect of uncertainty in parallel-plate tunable capacitors is studied to maximize the yield under given criteria. A new method for yield optimization of tunable MEMS capacitors is developed. The method can take into account any arbitrary distribution and is not restricted to normality assumptions. The optimal designs verified by Monte-Carlo simulation exhibits considerable improvement in the yield. A sensitivity analysis is then performed to refine the design variables and maximize the yield based on the most effective parameters. When the fabrication process is already established and cannot be changed, the method can be employed to estimate the final yield for the process. The advantage of this method is demonstrated by numerical examples where the yield using initial design parameters is compared to the yield of the device with optimum parameters.

scholarly journals Enhance Derivative Design Considering Global Sensitivity of Design Parameters

2013 ◽  
Author(s):  
Hyeong-UK Park ◽  
Kamran Behdinan ◽  
Joon Chung ◽  
Jae-Woo Lee
Keyword(s):  
Sensitivity Analysis ◽  
Design Process ◽  
Life Cycle Cost ◽  
Global Sensitivity Analysis ◽  
Collaborative Optimization ◽  
Design Parameters ◽  
Fast Method ◽  
Engineering Product ◽  
Global Sensitivity ◽  
Design Variables

An engineering product design considers derivatives to reduce the life cycle cost and to increase the efficiency on operation when it has new demands. The proposed design process in this study obtains derivative designs based on sensitivity of design variable. The efficiency and accuracy of the derivative design process can be enhanced by implementing global sensitivity analysis. Sensitivity analysis sensors the design variables accordingly and variables with low sensitivity for objective function can be neglected, since computational effort and time is not necessary for a design with less priority. In this research, e-FAST method code for global sensitivity analysis module was developed and implemented on Multidisciplinary Design Optimization (MDO) problem. The wing design was considered for MDO problem that used aerodynamics and structural disciplines. The global sensitivity analysis method was applied to reduce the number of design variables and Collaborative Optimization (CO) was used as MDO method. This research shows the efficiency of reduction of dimensionality of complex MDO problem by using global sensitivity analysis. In addition, this result shows important design variables for design requirement to student when they solving design problem.

scholarly journals CONCEPTUAL DESIGN FOR ASSEMBLY IN AEROSPACE INDUSTRY: SENSITIVITY ANALYSIS OF MATHEMATICAL FRAMEWORK AND DESIGN PARAMETERS

2021 ◽  
Vol 1 ◽  
pp. 731-740
Author(s):  
Giovanni Formentini ◽  
Claudio Favi ◽  
Claude Cuiller ◽  
Pierre-Eric Dereux ◽  
Francois Bouissiere ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Conceptual Design ◽  
Design Parameters ◽  
Design For Assembly ◽  
Mathematical Framework ◽  
Commercial Aircraft ◽  
System Architectures ◽  
Complex Engineering ◽  
Aircraft System ◽  
Definition Of

AbstractOne of the most challenging activity in the engineering design process is the definition of a framework (model and parameters) for the characterization of specific processes such as installation and assembly. Aircraft system architectures are complex structures used to understand relation among elements (modules) inside an aircraft and its evaluation is one of the first activity since the conceptual design. The assessment of aircraft architectures, from the assembly perspective, requires parameter identification as well as the definition of the overall analysis framework (i.e., mathematical models, equations).The paper aims at the analysis of a mathematical framework (structure, equations and parameters) developed to assess the fit for assembly performances of aircraft system architectures by the mean of sensitivity analysis (One-Factor-At-Time method). The sensitivity analysis was performed on a complex engineering framework, i.e. the Conceptual Design for Assembly (CDfA) methodology, which is characterized by level, domains and attributes (parameters). A commercial aircraft cabin system was used as a case study to understand the use of different mathematical operators as well as the way to cluster attributes.

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