Generation and Mapping of Minimally-Restrictive Manufacturability Constraints for Mechanical Design Problems

Traditional design-for-manufacturing (DFM) strategies focus on efficiency and design simplification and tend to be too restrictive for optimization-based design methods; recent advances in manufacturing technologies have opened up many new and exciting design options, but it is necessary to have a wide design space in order to take advantage of these benefits. What is needed is a simple but effective approach for restricting the design space to designs which are guaranteed to be manufacturable, but which leave intact as much of the design space as possible. Work has been done in this area for some specific domains, but a general method for accomplishing this has not yet been refined. This article presents an exploration of this problem and developed a framework for mapping practical manufacturing knowledge into mathematical manufacturability constraints in mechanical design problem formulations. The steps for completing this mapping and the enforcing the constraints are discussed and demonstrated. Three case studies (a milled heat exchanger fin, a 3-D printed topologically-optimized beam, and a pulley requiring a hybrid additive-subtractive process for production) were completed to demonstrate the concepts; these concepts include problem formulation, the generation and enforcement of the manufacturability constraints, and fabrication of the resulting designs with and without constraints.

Identification of Roughness with Optimal Contact Response with respect to Real Contact Area and Normal Stiffness

Additive manufacturing technologies are a key point of the current era of Industry 4.0, promoting the production of mechanical components via the addition of subsequent layers of material. Then, they may be also used to produce surfaces tailored to achieve a desired mechanical contact response. In this work, we develop a method to prototype profiles optimizing a suitable trade-off between two different target mechanical responses. The mechanical design problem is solved relying on both physical assumptions and optimization methods. An algorithm is proposed, exploiting an analogy between genetics and the multiscale characterization of roughness, where various length-scales are described in terms of rough profiles, named chromosomes. Finally, the proposed algorithm is tested on a representative example, and the topological and spectral features of roughness of the optimized profiles are discussed.

Progressive-Stepping-Based Non-Dominated Sorting Genetic Algorithm for Multi-Objective Optimization

This paper demonstrates two approaches to achieve faster convergence and a better spread of Pareto solutions in fewer numbers of generations, compared to a few existing algorithms, including NSGA-II and SPEA2 to solve multi-objective optimization problems (MOP's). Two algorithms are proposed based on progressive stepping mechanism, which is obtained by the hybridization of existing Non-dominated Sorting Genetic Algorithm II (NSGA-II) with novel guided search schemes, and modified chromosome selection and replacement mechanisms. Progressive Stepping Non-dominated Sorting based on Local search (PSNS-L) controls the step size, and Progressive Stepping Non-dominated Sorting based on Utopia point (PSNS-U) method controls the number of divisions to generate better chromosomes in each generation to achieve faster convergence. Four multi-objective evolutionary algorithms (EA's) are compared for different benchmark functions and PSNS outperforms them in most cases based on various performance metric values. Finally a mechanical design problem has been solved with PSNS algorithms.

Lifecycle-Based Swarm Optimization Method for Numerical Optimization

Bioinspired optimization algorithms have been widely used to solve various scientific and engineering problems. Inspired by biological lifecycle, this paper presents a novel optimization algorithm called lifecycle-based swarm optimization (LSO). Biological lifecycle includes four stages: birth, growth, reproduction, and death. With this process, even though individual organism died, the species will not perish. Furthermore, species will have stronger ability of adaptation to the environment and achieve perfect evolution. LSO simulates Biological lifecycle process through six optimization operators: chemotactic, assimilation, transposition, crossover, selection, and mutation. In addition, the spatial distribution of initialization population meets clumped distribution. Experiments were conducted on unconstrained benchmark optimization problems and mechanical design optimization problems. Unconstrained benchmark problems include both unimodal and multimodal cases the demonstration of the optimal performance and stability, and the mechanical design problem was tested for algorithm practicability. The results demonstrate remarkable performance of the LSO algorithm on all chosen benchmark functions when compared to several successful optimization techniques.

Mechanical Design and Study on Showing Platform of Rotation and Vertical Reciprocation

In view of well- designed showing platform is advantageous to promoting exhibition effect, the author analyzes the developing course of showing platform, and combining the mechanical design problem of existing showing platform which exists in using function, art function and material technique function and others, discusses the mechanical design requirement, the fundamental structure and working principle, the shape design and the color design of showing platform of rotation and vertical reciprocation. Among them the fundamental structure and working principle mainly elaborate the constituent parts of showing platform, the structure characteristics and working manner. Then the possibility is analyzed. On this foundation, the practical application of showing platform of rotation and vertical reciprocation is analyzed.

An Evolutionary Lagrange Method for Mechanical Design

A novel application to mechanical optimal design is presented in this paper. Here, an evolutionary algorithm, called mixed-integer differential evolution (MIHDE), is used to solve general mixed-integer optimization problems. However, most of real-world mixed-integer optimization problems frequently consist of equality and/or inequality constraints. In order to effectively handle constraints, an evolutionary Lagrange method based on MIHDE is implemented to solve the mixed-integer constrained optimization problems. Finally, the evolutionary Lagrange method is applied to a mechanical design problem. The satisfactory results are achieved, and demonstrate that the evolutionary Lagrange method can effectively solve the optimal mechanical design problem.

Haptic Wrists: An Alternative Design Strategy Based on User Perception

A new three degree-of-freedom (3DOF) torque feedback wrist is being developed to be added to an existing 3DOF force feedback haptic device. It is difficult to find a satisfactory solution to the mechanical design problem, mainly because of the required large rotational workspace and severe weight constraints. This work proposes an alternative design strategy based on user perception, which allows simplification of the mechanics. The proposed approach consists of substituting the last rotational DOF of the wrist with a pseudohaptic DOF. Thanks to specially designed visuotactile cues, the pseudohaptic DOF is integrated with the active DOF into the same device, being able to generate free motion and collision detection perception to the user. This approach provides for simpler kinematics, lightweight designs, lower inertias, and less friction, which are key advantages for the inclusion of torque feedback into force feedback devices.

Abstractions, Design Views and Focusing

Abstractions serve to reduce the complexity of the design process by providing a simple yet still useful representation of the design. Abstractions change one or all of the focus, resolution and accuracy of the design representation. Focusing abstractions direct the designer’s attention to fundamental relationships amongst design variables and requirements. The process of forming focusing abstractions incorporates the design relations and variables that are of concern to the designer, while mitigating the complexity of the resulting design view for the designer. The complexity is minimized by reducing the number of variables and relations considered simultaneously. This is done in a manner which allows the designer to determine the need for further refinements in configuration, to make parametric decisions, and to identify critical design relationships. The appropriate use of focusing abstractions can improve both the design process and the final design. Several basic approaches to creating focusing abstractions are described and one method, based upon Gröbner Bases, is developed in detail. This method is appropriate for a design object representation consisting of parametric constraints represented as sets of polynomial equations. This approach is demonstrated within the context of a sample electro-mechanical design problem, a cordless screwdriver.

Motion Interpolation and Mechanism Synthesis

This paper studies planar motion approximation problems from a computational geometric perspective and develop a computational geometric structure that can be used for mechanical motion synthesis. This allows for development of computational algorithms and software systems to support the mechanical design activity. The approach uses an orientable kinematic mapping to transform the mechanical design problem into a curve design problem in the space of the mapping. The curve design problem for synthesis of an analytic motion is carried out by Hermite interpolation. In case of a mechanical linkage, however, the Hermite interpolation is combined with a first-order curve fitting procedure for synthesizing the motion.