Robust Design for Fixture Layout in Multistation Assembly Systems Using Sequential Space Filling Methods

2010 ◽  
Vol 10 (4) ◽  
Author(s):  
Wenzhen Huang ◽  
Zhenyu Kong ◽  
Abishek Chennamaraju
Keyword(s):  
Optimal Design ◽  
Robust Design ◽  
High Dimension ◽  
Optimization Problem ◽  
System Level ◽  
Design Parameters ◽  
Space Filling ◽  
Sequential Space ◽  
Fixture Layout ◽  
Computation Efficiency

Fixture layout robust design of multistation manufacturing systems aims for an optimal design that enables the dimensional variation of a product insensitive to the variations of process variables in the manufacturing process. The robust design involves a high dimension and complex global optimization problem. Recent advances in stream of variation modeling techniques enable effective formulation of the optimization problem at the system level. However, there is a challenge of computation complexity in terms of searching optimal design parameters in a high dimension, nonconvex, and discontinuous design space. This makes many available algorithms ineffective or even invalid. In this paper, an alternative sequential space filling strategy is proposed, which adopts sampling approaches to search optimal designs. To improve computation efficiency, the search space is sequentially reduced to generate a series of subspaces, and a method is designed to ensure a complete coverage of these subspaces in the original feasible space. In order to validate the proposed method, a floor pan assembly from an automotive body assembly process is modeled, and then the fixture robust design is conducted with the developed methods. To show the effectiveness of the proposed method, genetic algorithm and sequential quadratic programming are also applied in the case study for comparison.

Configuration Robustness Analysis of the Optimal Design of Cable-Driven Manipulators

2016 ◽  
Vol 8 (6) ◽  
Author(s):  
Joshua T. Bryson ◽  
Xin Jin ◽  
Sunil K. Agrawal
Keyword(s):  
Optimal Design ◽  
Stochastic Optimization ◽  
High Dimension ◽  
Degrees Of Freedom ◽  
Robustness Analysis ◽  
Optimal Solution ◽  
Design Parameters ◽  
Robot Leg ◽  
Robot Performance

Designing an effective cable architecture for a cable-driven robot becomes challenging as the number of cables and degrees of freedom of the robot increase. A methodology has been previously developed to identify the optimal design of a cable-driven robot for a given task using stochastic optimization. This approach is effective in providing an optimal solution for robots with high-dimension design spaces, but does not provide insights into the robustness of the optimal solution to errors in the configuration parameters that arise in the implementation of a design. In this work, a methodology is developed to analyze the robustness of the performance of an optimal design to changes in the configuration parameters. This robustness analysis can be used to inform the implementation of the optimal design into a robot while taking into account the precision and tolerances of the implementation. An optimized cable-driven robot leg is used as a motivating example to illustrate the application of the configuration robustness analysis. Following the methodology, the effect on robot performance due to design variations is analyzed, and a modified design is developed which minimizes the potential performance degradations due to implementation errors in the design parameters. A robot leg is constructed and is used to validate the robustness analysis by demonstrating the predicted effects of variations in the design parameters on the performance of the robot.

scholarly journals Optimal Design of Shape Memory Alloy Composite under Deflection Constraint

Materials ◽  
2019 ◽  
Vol 12 (11) ◽  
pp. 1733 ◽  
Author(s):  
Yogesh Gandhi ◽  
Alessandro Pirondi ◽  
Luca Collini
Keyword(s):  
Optimal Design ◽  
Shape Memory Alloy ◽  
Shape Memory ◽  
Optimization Problem ◽  
Edge Length ◽  
Design Parameters ◽  
Stable Configuration ◽  
Alloy Composite ◽  
Bistable Behavior ◽  
Design Variables

Shape-adaptive or morphing capability in both aerospace structures and wind turbine blade design is regarded as significant to increase aerodynamic performance and simplify mechanisms by reducing the number of moving parts. The underlying bistable behavior of asymmetric cross-ply composites makes them a suitable candidate for morphing applications. To date, various theoretical and experiential studies have been carried out to understand and predict the bistable behavior of asymmetric laminates and especially the curvature obtained in their stable configurations. However, when the bi-stable composite plate is integrated with shape memory alloy wires to control the curvature and to snap from a stable configuration to the other (shape memory alloy composite, SMAC), the identification of the design parameters, namely laminate edge length, ply thickness and ply orientation, is not straightforward. The aim of this article is to present the formulation of an optimization problem for the parameters of an asymmetric composite laminate integrated with pre-stressed shape memory alloys (SMA) wires under bi-stability and a minimum deflection requirement. Wires are modeled as an additional ply placed at the mid-plane of the composite host plate. The optimization problem is solved numerically in MATLAB and optimal design variables are then used to model the SMAC in ABAQUS™. Finite element results are compared against numerical results for validation.

scholarly journals Tolerance Synthesis of Mechanisms: A Robust Design Approach

2003 ◽  
Author(s):  
Ste´phane Caro ◽  
Fouad Bennis ◽  
Philippe Wenger
Keyword(s):  
Robust Design ◽  
Optimization Problem ◽  
Synthesis Method ◽  
Upper And Lower Bounds ◽  
Design Parameters ◽  
Design Problems ◽  
Tolerance Synthesis ◽  
Design Variables ◽  
Synthesis Of Mechanisms ◽  
Serial Positioning

The paper aims at dimensioning a mechanism in order to make it robust, and synthesizing its dimensional tolerances. The design of a mechanism is supposed to be robust when its performance is as little as sensitive as possible to variations. First, a distinction is made between three sets to formulate a robust design problem; (i) the set of Design Variables (DV) whose nominal values can be selected between a range of upper and lower bounds, they are controllable; (ii) the set of Design Parameters (DP) that cannot be adjusted by the designer, they are uncontrollable; (iii) the set of performance functions. DV are however under uncontrollable variations although their nominal value can be adjusted. Moreover, two methods are described to solve robust design problems. The first method is explicit and solves problems that aim at minimizing variations in performance. The second method, an optimization problem, aims at optimizing the performance and minimizing its variations, but only when the ranges of variations in DV and DP are known. Besides, we define and compare some robustness indices. From the explicit method, we develop a new tolerance synthesis method. Finally, three examples are included to illustrate these methods: a damper, a two-dof and a three-dof serial positioning manipulator.

scholarly journals Structural optimization considering the probabilistic system response

2004 ◽  
Vol 31 (3-4) ◽  
pp. 361-394 ◽  
Author(s):  
M. Papadrakakis ◽  
N.D. Lagaros ◽  
V. Plevris
Keyword(s):  
Structural Optimization ◽  
Design Optimization ◽  
Robust Design ◽  
Large Scale ◽  
Optimization Problem ◽  
Structural Parameters ◽  
Dominant Role ◽  
Robust Design Optimization ◽  
Design Parameters ◽  
System Response

In engineering problems, the randomness and uncertainties are inherent and the scatter of structural parameters from their nominal ideal values is unavoidable. In Reliability Based Design Optimization (RBDO) and Robust Design Optimization (RDO) the uncertainties play a dominant role in the formulation of the structural optimization problem. In an RBDO problem additional non deterministic constraint functions are considered while an RDO formulation leads to designs with a state of robustness, so that their performance is the least sensitive to the variability of the uncertain variables. In the first part of this study a metamodel assisted RBDO methodology is examined for large scale structural systems. In the second part an RDO structural problem is considered. The task of robust design optimization of structures is formulated as a multi-criteria optimization problem, in which the design variables of the optimization problem, together with other design parameters such as the modulus of elasticity and the yield stress are considered as random variables with a mean value equal to their nominal value. .

A Gaussian Process Modeling Approach for Fast Robust Design With Uncertain Inputs

2018 ◽  
Author(s):  
Kevin M. Ryan ◽  
Jesper Kristensen ◽  
You Ling ◽  
Sayan Ghosh ◽  
Isaac Asher ◽  
...  
Keyword(s):  
Gaussian Process ◽  
Design Optimization ◽  
Robust Design ◽  
Optimization Problem ◽  
Robust Design Optimization ◽  
Design Parameters ◽  
Input Uncertainty ◽  
Single Level ◽  
Output Uncertainty ◽  
Gp Model

Many engineering design and industrial manufacturing applications are tasked with finding optimum designs while dealing with uncertainty in the design parameters. The performance or quality of the design may be sensitive to the input variation, making it difficult to optimize. Probabilistic and robust design optimization methods are used in these scenarios to find the designs that will perform best under the presence of known input uncertainty. Robust design optimization algorithms often require a two-level optimization problem (double-loop) to find a solution. The design optimization outer-loop repeatedly calls a series of inner loops that calculate uncertainty measures of the outputs. This nested optimization problem is computationally expensive and can sometimes render the task infeasible for practical engineering robust design problems. This paper details a single-level metamodel-assisted approach for probabilistic and robust design. An enhanced Gaussian Process (GP) metamodel formulation is used to provide exact values of output uncertainty in the presence of uncertain inputs. The GP model utilizes a squared-exponential kernel function and assumes normally distributed input uncertainty. These two factors together allow for an exact calculation of the first and second moments of the marginal predictive distribution. Predictions of output uncertainty are directly calculated, creating an efficient single-level robust optimization problem. We demonstrate the effectiveness of the single-level GP-assisted robust design approach on multiple engineering example problems, including a beam vibration problem, a cantilevered beam with multiple constraints, and a robust autonomous aircraft flight controller design problem. For the optimization problems investigated in this study, the single-level framework found the robust optimum with a 99.9% savings in function evaluations over the standard two-level approach.

scholarly journals Robust Design Optimization in Computational Mechanics

2008 ◽  
Vol 75 (2) ◽  
Author(s):  
E. Capiez-Lernout ◽  
C. Soize
Keyword(s):  
Cost Function ◽  
Design Optimization ◽  
Robust Design ◽  
Stochastic System ◽  
Optimization Problem ◽  
Probabilistic Approach ◽  
Robust Design Optimization ◽  
Design Parameters ◽  
Random Response ◽  
Numerical Application

The motivation of this paper is to propose a methodology for analyzing the robust design optimization problem of complex dynamical systems excited by deterministic loads but taking into account model uncertainties and data uncertainties with an adapted nonparametric probabilistic approach, whereas only data uncertainties are generally considered in the literature by using a parametric probabilistic approach. The possible designs are represented by a numerical finite element model whose design parameters are deterministic and belong to an admissible set. The optimization problem is formulated for the stochastic system as the minimization of a cost function associated with the random response of the stochastic system including the variability of the stochastic system induced by uncertainties and the bias corresponding to the distance of the mean random response to a given target. The gradient and the Hessian of the cost function with respect to the design parameters are explicitly calculated. The complete theory and a numerical application are presented.

scholarly journals Optimal design of fixture layouts for compliant sheet metal assemblies

2020 ◽  
Vol 110 (7-8) ◽  
pp. 2181-2201
Author(s):  
Abolfazl Rezaei Aderiani ◽  
Kristina Wärmefjord ◽  
Rikard Söderberg ◽  
Lars Lindkvist ◽  
Björn Lindau
Keyword(s):  
Optimal Design ◽  
Sheet Metal ◽  
Design Procedure ◽  
Optimization Method ◽  
Design Parameters ◽  
Fixture Layout ◽  
Geometrical Quality ◽  
Evolutionary Optimization Algorithms ◽  
Assembly Procedure

Abstract A preeminent factor in the geometrical quality of a compliant sheet metal assembly is the fixture layout that is utilized to perform the assembly procedure. Despite the presence of a great number of studies about the optimization of assembly fixture layouts, there is not a comprehensive algorithm to optimize all design parameters of fixture layouts for compliant sheet metal assemblies. These parameters are the location and type of hole and slot in each part, the slot orientation, and the number and location of additional clamps. This paper presents a novel optimization method that optimizes all these parameters simultaneously to maximize the geometrical quality of the assemblies. To attain this goal, compliant variation simulations of the assemblies are utilized along with evolutionary optimization algorithms. The assembly springback and contacts between parts are considered in the simulations. After determining the optimal design parameters, the optimal positions of locators are fine-tuned in another stage of optimization. Besides, a top-down design procedure is proposed for applying this method to multi-station compliant assemblies. The presented method is applied to two industrial sample cases from the automotive industry. The results evidence a significant improvement of geometrical quality by utilizing the determined fixture layout from the presented method compared with the original fixture layouts of the sample cases.

scholarly journals Fundamental framework toward optimal design of product platform for industrial three-axis linear-type robots

2015 ◽  
Vol 2 (3) ◽  
pp. 157-164 ◽  
Author(s):  
Kana Sawai ◽  
Yutaka Nomaguchi ◽  
Kikuo Fujita
Keyword(s):  
Optimal Design ◽  
Optimization Problem ◽  
Performance Metrics ◽  
Beam Theory ◽  
Design Parameters ◽  
Product Platform ◽  
Linear Type ◽  
Operation Speed ◽  
Trade Offs ◽  
Wide Range

Abstract This paper discusses an optimization-based approach for the design of a product platform for industrial three-axis linear-type robots, which are widely used for handling objects in manufacturing lines. Since the operational specifications of these robots, such as operation speed, working distance and orientation, weight and shape of loads, etc., will vary for different applications, robotic system vendors must provide various types of robots efficiently and effectively to meet a range of market needs. A promising step toward this goal is the concept of a product platform, in which several key elements are commonly used across a series of products, which can then be customized for individual requirements. However the design of a product platform is more complicated than that of each product, due to the need to optimize the design across many products. This paper proposes an optimization-based fundamental framework toward the design of a product platform for industrial three-axis linear-type robots; this framework allows the solution of a complicated design problem and builds an optimal design method of fundamental features of robot frames that are commonly used for a wide range of robots. In this formulation, some key performance metrics of the robot are estimated by a reduced-order model which is configured with beam theory. A multi-objective optimization problem is formulated to represent the trade-offs among key design parameters using a weighted-sum form for a single product. This formulation is integrated into a mini–max type optimization problem across a series of robots as an optimal design formulation for the product platform. Some case studies of optimal platform design for industrial three-axis linear-type robots are presented to demonstrate the applications of a genetic algorithm to such mathematical models.

Kinematic Analysis on Running Clearance in a Trochoidal-Type Machine

1995 ◽  
Author(s):  
John B. Shung ◽  
Yi Zhang
Keyword(s):  
Mathematical Model ◽  
Optimal Design ◽  
Robust Design ◽  
Upper Bound ◽  
Kinematic Analysis ◽  
Design Parameters ◽  
Mean Values ◽  
Type Machine ◽  
The Mean ◽  
Design Optimum

Abstract A methodology to design tight running clearance between rotor and chamber in a trochoidal-type machine is presented. A mathematical model to describe the running clearance is developed. Only kinematic design parameters are considered. The effect of the mean values and tolerances of the design parameters on the running clearance is studied by applying robust design. Mean values of design parameters which provide running clearance to be less sensitive to the tolerances are obtained. The effect of the upper bound of the running clearance on the tolerance is also studied by applying the probabilistic optimal design. Optimum tolerances which minimize a cost function are obtained. Therefore, one can apply this methodology to design running clearance by choosing appropriate mean values and tolerances of the design parameters.

Justification of design parameters of the fractional reaping conveyor and its devices for removal of beveled stems from under the wheels of the vehicle

2019 ◽  
Vol 1 (3) ◽  
pp. 1-10
Author(s):  
Mikhail M. Konstantinov ◽  
Ivan N. Glushkov ◽  
Sergey S. Pashinin ◽  
Igor I. Ognev ◽  
Tatyana V. Bedych
Keyword(s):  
Optimal Design ◽  
Technological Process ◽  
Design Parameters ◽  
Theoretical Studies ◽  
Optimal Parameters ◽  
Belt Conveyor ◽  
Grain Crops ◽  
Mode Of Operation ◽  
Optimal Values ◽  
Main Component

In this paper we consider the structural and technological process of the combine used in the process of separate harvesting of grain crops, as well as a number of its parameters. Among the main units of the combine, we allocate a conveyor and devices for removing beveled stems from under the wheels of the vehicle. The principle of operation of the conveyor at different phases of the Reaper and especially the removal of cut stems from under the wheels of the vehicle during operation of the Reaper. The results of theoretical studies on the establishment of the optimal design of the parameters of the belt conveyor are presented, the ranges of their optimal values are considered and determined. Studies on the establishment of optimal parameters of the screw divider in the Reaper, which is the main component of the device for removal of beveled stems, are presented. Taking into account the optimal design and mode of operation of the screw divider, the correct work is provided to remove the cut stems from under the wheels of the harvester.

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