Smart Optimization of Machine Systems Using Hierarchical Genotype Representations

Design problems for machine products are generally hierarchically expressed. With conventional product optimization methods, it is difficult to concurrently optimize all design variables of portions within the hierarchical structure. This paper proposes a design optimization method using genetic algorithms containing hierarchical genotype representations, so that the hierarchical structures of machine system designs are exactly expressed through genotype coding, and optimization can be concurrently conducted for all of the hierarchical structures. Crossover and mutation operations for manipulating the hierarchical genotype representations are also developed. The proposed method is applied to a machine-tool structural design to demonstrate its effectiveness.

A Distributed Approach for Accessibility and Maintainability Check With a Manikin

The validation of the accessibility, maintainability, mounting/dismantle simulation in a cluttered environment is a key problem during the design process of a mechanical system. On the one hand research in path planning lead to automatic trajectory definition. These systems are really efficient for simple problems. On the other hand direct manipulation is possible thanks to robotic CAD systems. Another direct manipulation is possible with common virtual reality tools that allow the designer immersion in a whole mechanical environment. In such an environment the designer can handle an object in order to check its accessibility. Thanks to the use of a multi-agent architecture we greatly improve the effectiveness of virtual reality tools while coupling algorithmic approaches and direct manipulation. This original method is a solution of a multi-criteria constrained optimisation problem. Theoretical and practical aspects are presented.

Fictitious Domain Solution of Frequency Response Problems

This paper discusses an alternative solution strategy for frequency response problems in elasticity. This strategy uses a meshless method, derived in a periodic domain setting, extended to allow the analysis of arbitrary geometries with the use of a fictitious domain. This solution technique is designed to solve problems with a large number of degrees of freedom and it requires the use of iterative solvers where preconditioning is necessary for reasonable convergence rates. Two dimensional examples illustrating this approach are provided.

A Model for the Prediction of Form Errors in Face Milling and Turning

A method is proposed for predicting form errors due to both clamping and cutting forces in face milling and turning. It allows complex tool trajectories and workpiece geometries. Error computation is performed by the finite element method. An experimental validation of the model for face milling is presented. Two industrial applications are produced in order to demonstrate the capabilities of the method.

Topology Synthesis of Large-Displacement Compliant Mechanisms

This paper describes the use of topology optimization as a synthesis tool for the design of large-displacement compliant mechanisms. An objective function for the synthesis of large-displacement mechanisms is proposed together with a formulation for synthesis of path-generating compliant mechanisms. The responses of the compliant mechanisms are modelled using a Total Lagrangian finite element formulation, the sensitivity analysis is performed using the adjoint method and the optimization problem is solved using the Method of Moving Asymptotes. Procedures to circumvent some numerical problems are discussed.

Comparison of Two Multiobjective Optimization Techniques With and Within Genetic Algorithms

Engineering decision making involving multiple competing objectives relies on choosing a design solution from an optimal set of solutions. This optimal set of solutions, referred to as the Pareto set, represents the tradeoffs that exist between the competing objectives for different design solutions. Generation of this Pareto set is the main focus of multiple objective optimization. There are many methods to solve this type of problem. Some of these methods generate solutions that cannot be applied to problems with a combination of discrete and continuous variables. Often such solutions are obtained by an optimization technique that can only guarantee local Pareto solutions or is applied to convex problems. The main focus of this paper is to demonstrate two methods of using genetic algorithms to overcome these problems. The first method uses a genetic algorithm with some external modifications to handle multiple objective optimization, while the second method operates within the genetic algorithm with some significant internal modifications. The fact that the first method operates with the genetic algorithm and the second method within the genetic algorithm is the main difference between these two techniques. Each method has its strengths and weaknesses, and it is the objective of this paper to compare and contrast the two methods quantitatively as well as qualitatively. Two multiobjective design optimization examples are used for the purpose of this comparison.

Design and Experimental Verification of a New Direct Cold Drawing Die for Section Rod From Round Bar

This paper presents the design and verification of a new direct cold drawing die used for drawing of hexagon/square section rods from round bars. Advanced computer-aided design and analysis tools are utilized to assist in the design of die profile and manufacturing parameters. The strain gage method is adopted to measure the mean drawing force and verify the die design and machining process.

A Fuzzy Adaptive Simplex Search Optimization Algorithm

Optimization algorithms usually use fixed parameters that are empirically chosen to reach the minimum for various objective functions. This paper shows how to incorporate fuzzy logic in optimization algorithms to make the search adaptive to various objective functions. This idea is applied to produce a new algorithm for minimization of a function of n variables using an adaptive form of the simplex method. The search starts by generating a simplex with n+1 vertices. The algorithm replaces the point with the highest function value by a new point. This process comprises reflecting the point with the highest function value in addition to expanding or contracting the simplex using fuzzy logic controllers whose inputs incorporate the relative weights of the function values at the simplex points. The efficiency of the algorithm is studied using a set of standard minimization test problems. This algorithm generally results in a faster convergence toward the minimum. The algorithm is also applied successfully to two engineering design problems.

Smooth Surface Interpolation With Multiple Patches

This paper addresses the problem of interpolating point data with multiple patches. The specific issue addressed in this paper is the continuity between the patches used for interpolation. The procedure described in this paper maintains continuity by introducing an intermediate patch between the two patches used for interpolating the point data. This patch is formed by several Bezier patches that maintain continuity with the corresponding Bezier patches obtained by repeated knot insertion in the two interpolating patches. The blending Bezier patches are then converted to a blending B-spline patch by knot removal. It is shown that C1 continuity is obtained across the junction between each interpolating patch and the blending patch. The continuity, across each blending patch and the interpolation performance in the blending patch is also discussed. The paper presents results, of implementation on some typical surfaces.

Generation of Design Data Through Numerical Modeling of a Post and Dome Feature

This paper focuses on developing improved design equations to estimate the retention strength, insertion force, and insertion strain of a particular snap-fit, the post and dome feature. Finite element methods and multiple regression techniques were used in lieu of beam equations to develop the improved design equations. Sensitivity data is plotted for both the main effects and selected variable interactions. A study of detailed catch geometry was done in order to identify an optimal catch geometry. Typical design parameters were varied in order to develop design equations for users of this feature. The post and dome feature was selected for analysis because it is a high performance snap-fit that is self-datuming and can take some shear loading in addition to retention. The post and dome provide a higher ratio of retention force to insertion force than traditional cantilever snap-fits, and retention is less dependent on friction.