Multi-Objective Optimal Tolerance Allocation of the Mechanical Systems under the Thermal Gradients

2018 ◽  
Author(s):  
S. Khodaygan ◽  
Javad Hemati-Nik
Keyword(s):  
Mechanical Systems ◽  
Tolerance Allocation ◽  
Thermal Gradients ◽  
Multi Objective

A Probabilistic Tolerance Allocation Method for Dynamic Mechanical Systems With Periodic Response and Discontinuous Forcing Functions

1995 ◽  
Author(s):  
F. Zhang ◽  
B. J. Gilmore ◽  
A. Sinha
Keyword(s):  
Combustion Engine ◽  
Equations Of Motion ◽  
Mechanical Systems ◽  
Optimization Procedure ◽  
Tolerance Allocation ◽  
Radial Clearance ◽  
Time Varying ◽  
Link Length ◽  
Design Variables ◽  
Forcing Functions

Abstract Tolerance allocation standards do not exist for mechanical systems whose response are time varying and are subjected to discontinuous forcing functions. Previous approaches based on optimization and numerical integration of the dynamic equations of motion encounter difficulty with determining sensitivities around the force discontinuity. The Alternating Frequency/Time approach is applied here to capture the effect of the discontinuity. The effective link length model is used to model the system and to account for the uncertainties in the link length, radial clearance and pin location. Since the effective link length model is applied, the equations of motion for the nominal system can be applied for the entire analysis. Optimization procedure is applied to the problem where the objective is to minimize the manufacturing costs and satisfy the constraints imposed on mechanical errors and design variables. Examples of tolerance allocation are presented for a single cylinder internal combustion engine.

Dimensional Tolerance Allocation of Stochastic Dynamic Mechanical Systems Through Performance and Sensitivity Analysis

1990 ◽  
Author(s):  
S. J. Lee ◽  
B. J. Gilmore ◽  
M. M. Ogot
Keyword(s):  
Sensitivity Analysis ◽  
Probabilistic Models ◽  
General Procedure ◽  
Equations Of Motion ◽  
Mechanical Systems ◽  
Tolerance Allocation ◽  
Stochastic Dynamic ◽  
Link Length ◽  
Analysis And Design ◽  
Dynamic Mechanical

Abstract Uncertainties due to random dimensional tolerances within stochastic dynamic mechanical systems lead to mechanical errors and thus, performance degradation. Since design standards do not exist for these systems, analysis and design tools are needed to properly allocate tolerances. This paper presents probabilistic models and methods to allocate tolerances on the link lengths and radial clearances such that the system meets a probabilistic and time dependent performance criterion. The method includes a general procedure for sensitivity analysis, using the effective link length model and nominal equations of motion. Since the sensitivity analysis requires only the nominal equations of motion and statistical information as input, it is straight forward to implement. An optimal design problem is formulated to allocate random tolerances. Examples are presented to illustrate the approach and its generality. This paper provides a solution to the tolerance allocation problem for stochastic dynamically driven mechanical systems.

Optimal Tolerance Allocation of Automotive Pneumatic Control Valves Based on Product and Process Simulations

2006 ◽  
Author(s):  
Naesung Lyu ◽  
Amane Shimura ◽  
Kazuhiro Saitou
Keyword(s):  
Product Quality ◽  
Production Cost ◽  
Radial Basis Function Network ◽  
Discrete Event ◽  
Computational Method ◽  
Tolerance Allocation ◽  
Production Volume ◽  
Pneumatic Control ◽  
Multi Objective ◽  
Trade Offs

This paper discusses a computational method for optimally allocating dimensional tolerances for an automotive pneumatic control valve. Due to the large production volume, costly tight tolerances should be allocated only to the dimensions that have high influence to the quality. Given a parametric geometry of a valve, the problem is posed as a multi-objective optimization with respect to product quality and production cost. The product quality is defined as 1) the deviation from the nominal valve design in the linearity of valve stroke and fluidic force, and 2) the difference in fluidic force with and without cavitation. These quality measures are estimated by using Monte Carlo simulation on a Radial-Basis Function Network (RBFN) trained with computational fluid dynamics (CFD) simulation of the valve operation. The production cost is estimated by the tolerance-cost relationship obtained from the discrete event simulations of valve production process. A multi-objective genetic algorithm is utilized to generate Pareto optimal tolerance allocations with respect to these objectives, and alternative tolerance allocations are proposed considering the trade-offs among multiple objectives.

Dimensional Tolerance Allocation of Stochastic Dynamic Mechanical Systems Through Performance and Sensitivity Analysis

1993 ◽  
Vol 115 (3) ◽  
pp. 392-402 ◽  
Author(s):  
S. J. Lee ◽  
B. J. Gilmore ◽  
M. M. Ogot
Keyword(s):  
Sensitivity Analysis ◽  
Probabilistic Models ◽  
General Procedure ◽  
Equations Of Motion ◽  
Mechanical Systems ◽  
Tolerance Allocation ◽  
Stochastic Dynamic ◽  
Link Length ◽  
Analysis And Design ◽  
Dynamic Mechanical

Uncertainties due to random dimensional tolerances within stochastic dynamic mechanical systems lead to mechanical errors and thus, performance degradation. Since design standards do not exist for these systems, analysis and design tools are needed to properly allocate tolerances. This paper presents probabilistic models and methods to allocate tolerances on the link lengths and radial clearances such that the system meets a probabilistic and time dependent performance criterion. The method includes a general procedure for sensitivity analysis, using the effective link length model and nominal equations of motion. Since the sensitivity analysis requires only the nominal equations of motion and statistical information as input, it is straight forward to implement. An optimal design problem is formulated to allocate random tolerances. Examples are presented to illustrate the approach and its generality. This paper provides a solution to the tolerance allocation problem for stochastic dynamically driven mechanical systems.

A framework for tolerance design considering systematic and random uncertainties due to operating conditions

2019 ◽  
Vol 39 (5) ◽  
pp. 854-871
Author(s):  
S. Khodaygan
Keyword(s):  
Operating Conditions ◽  
Tolerance Allocation ◽  
Manufacturing Cost ◽  
Tolerance Design ◽  
Element Analysis ◽  
Content Type ◽  
Multi Objective ◽  
Mechanical Assemblies ◽  
Conflicting Objectives ◽  
Random Uncertainties

Purpose The purpose of this paper is to present a novel Kriging meta-model assisted method for multi-objective optimal tolerance design of the mechanical assemblies based on the operating conditions under both systematic and random uncertainties. Design/methodology/approach In the proposed method, the performance, the quality loss and the manufacturing cost issues are formulated as the main criteria in terms of systematic and random uncertainties. To investigate the mechanical assembly under the operating conditions, the behavior of the assembly can be simulated based on the finite element analysis (FEA). The objective functions in terms of uncertainties at the operating conditions can be modeled through the Kriging-based metamodeling based on the obtained results from the FEA simulations. Then, the optimal tolerance allocation procedure is formulated as a multi-objective optimization framework. For solving the multi conflicting objectives optimization problem, the multi-objective particle swarm optimization method is used. Then, a Shannon’s entropy-based TOPSIS is used for selection of the best tolerances from the optimal Pareto solutions. Findings The proposed method can be used for optimal tolerance design of mechanical assemblies in the operating conditions with including both random and systematic uncertainties. To reach an accurate model of the design function at the operating conditions, the Kriging meta-modeling is used. The efficiency of the proposed method by considering a case study is illustrated and the method is verified by comparison to a conventional tolerance allocation method. The obtained results show that using the proposed method can lead to the product with a more robust efficiency in the performance and a higher quality in comparing to the conventional results. Research limitations/implications The proposed method is limited to the dimensional tolerances of components with the normal distribution. Practical implications The proposed method is practically easy to be automated for computer-aided tolerance design in industrial applications. Originality/value In conventional approaches, regardless of systematic and random uncertainties due to operating conditions, tolerances are allocated based on the assembly conditions. As uncertainties can significantly affect the system’s performance at operating conditions, tolerance allocation without including these effects may be inefficient. This paper aims to fill this gap in the literature by considering both systematic and random uncertainties for multi-objective optimal tolerance design of mechanical assemblies under operating conditions.

Multi-objective optimization by a new hybridized method: applications to random mechanical systems

2013 ◽  
Vol 45 (8) ◽  
pp. 917-939 ◽  
Author(s):  
H. Zidani ◽  
E. Pagnacco ◽  
R. Sampaio ◽  
R. Ellaia ◽  
J. E. Souza de Cursi
Keyword(s):  
Mechanical Systems ◽  
Multi Objective Optimization ◽  
Multi Objective
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