Optimal Tolerancing: The Link Between Design and Manufacturing Productivity

1994 ◽  
Author(s):  
Mark Iannuzzi ◽  
Eric Sandgren
Keyword(s):  
Optimal Allocation ◽  
Mechanical Design ◽  
Computational Design ◽  
Optimization Method ◽  
Design Tool ◽  
Superior Performance ◽  
Test Problems ◽  
Tolerance Range ◽  
Manufacturing Productivity ◽  
Combined Algorithm

Abstract A computational design tool is presented which permits the optimal allocation of tolerances for mechanical and electrical components and assemblies. The basic approach involves the coupling of a nontraditional optimization method with a Monte Carlo based tolerance analysis. The objective is to determine the tolerance range value to assign to each nominal dimension which minimizes the production cost of the component or assembly while simultaneously meeting all critical dimensional and functional constraints imposed upon the design. A discretization of possible tolerance range values is performed and a global search is conducted by a genetic algorithm. Both the fine and course grain performance of the combined algorithm is demonstrated on a series of test problems ranging from a simple assembly of blocks to several real mechanical design problems. Solutions generated on problems taken from the literature indicate superior performance to existing techniques. Extensions which would allow for a complete optimal dimensional management environment are examined.

scholarly journals Elite Exploitation: A Combination of Mathematical Concept and EMO Approach for Multi-Objective Decision Making

Symmetry ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 136
Author(s):  
Wenxiao Li ◽  
Yushui Geng ◽  
Jing Zhao ◽  
Kang Zhang ◽  
Jianxin Liu
Keyword(s):  
Decision Making ◽  
Optimization Problems ◽  
Hybrid Genetic Algorithm ◽  
Decision Makers ◽  
Superior Performance ◽  
Test Problems ◽  
Mathematical Function ◽  
Hyperbolic Tangent ◽  
Nsga Ii ◽  
Multi Objective

This paper explores the combination of a classic mathematical function named “hyperbolic tangent” with a metaheuristic algorithm, and proposes a novel hybrid genetic algorithm called NSGA-II-BnF for multi-objective decision making. Recently, many metaheuristic evolutionary algorithms have been proposed for tackling multi-objective optimization problems (MOPs). These algorithms demonstrate excellent capabilities and offer available solutions to decision makers. However, their convergence performance may be challenged by some MOPs with elaborate Pareto fronts such as CFs, WFGs, and UFs, primarily due to the neglect of diversity. We solve this problem by proposing an algorithm with elite exploitation strategy, which contains two parts: first, we design a biased elite allocation strategy, which allocates computation resources appropriately to elites of the population by crowding distance-based roulette. Second, we propose a self-guided fast individual exploitation approach, which guides elites to generate neighbors by a symmetry exploitation operator, which is based on mathematical hyperbolic tangent function. Furthermore, we designed a mechanism to emphasize the algorithm’s applicability, which allows decision makers to adjust the exploitation intensity with their preferences. We compare our proposed NSGA-II-BnF with four other improved versions of NSGA-II (NSGA-IIconflict, rNSGA-II, RPDNSGA-II, and NSGA-II-SDR) and four competitive and widely-used algorithms (MOEA/D-DE, dMOPSO, SPEA-II, and SMPSO) on 36 test problems (DTLZ1–DTLZ7, WGF1–WFG9, UF1–UF10, and CF1–CF10), and measured using two widely used indicators—inverted generational distance (IGD) and hypervolume (HV). Experiment results demonstrate that NSGA-II-BnF exhibits superior performance to most of the algorithms on all test problems.

scholarly journals Target Localization Based on Bistatic T/R Pair Selection in GNSS-Based Multistatic Radar System

2021 ◽  
Vol 13 (4) ◽  
pp. 707
Author(s):  
Yu’e Shao ◽  
Hui Ma ◽  
Shenghua Zhou ◽  
Xue Wang ◽  
Michail Antoniou ◽  
...  
Keyword(s):  
Optimization Methods ◽  
Optimization Method ◽  
Satellite System ◽  
Radar System ◽  
Target Localization ◽  
Computational Load ◽  
Matrix Fusion ◽  
Global Navigation Satellite ◽  
Multistatic Radar ◽  
Combined Algorithm

To cope with the increasingly complex electromagnetic environment, multistatic radar systems, especially the passive multistatic radar, are becoming a trend of future radar development due to their advantages in anti-electronic jam, anti-destruction properties, and no electromagnetic pollution. However, one problem with this multi-source network is that it brings a huge amount of information and leads to considerable computational load. Aiming at the problem, this paper introduces the idea of selecting external illuminators in the multistatic passive radar system. Its essence is to optimize the configuration of multistatic T/R pairs. Based on this, this paper respectively proposes two multi-source optimization algorithms from the perspective of resolution unit and resolution capability, the Covariance Matrix Fusion Method and Convex Hull Optimization Method, and then uses a Global Navigation Satellite System (GNSS) as an external illuminator to verify the algorithms. The experimental results show that the two optimization methods significantly improve the accuracy of multistatic positioning, and obtain a more reasonable use of system resources. To evaluate the algorithm performance under large number of transmitting/receiving stations, further simulation was conducted, in which a combination of the two algorithms were applied and the combined algorithm has shown its effectiveness in minimize the computational load and retain the target localization precision at the same time.

An Interactive Morphological Matrix Computational Design Tool: A Hybrid of Two Methods

2007 ◽  
Author(s):  
Cari R. Bryant ◽  
Matt Bohm ◽  
Robert B. Stone ◽  
Daniel A. McAdams
Keyword(s):  
Computational Design ◽  
Design Tool ◽  
Design Tools ◽  
Concept Generation ◽  
University Of Missouri ◽  
Generation Algorithm ◽  
Design Theories ◽  
The University ◽  
Matrix Generator

This paper builds on previous concept generation techniques explored at the University of Missouri - Rolla and presents an interactive concept generation tool aimed specifically at the early concept generation phase of the design process. Research into automated concept generation design theories led to the creation of two distinct design tools: an automated morphological search that presents a designer with a static matrix of solutions that solve the desired input functionality and a computational concept generation algorithm that presents a designer with a static list of compatible component chains that solve the desired input functionality. The merger of both the automated morphological matrix and concept generation algorithm yields an interactive concept generator that allows the user to select specific solution components while receiving instantaneous feedback on component compatibility. The research presented evaluates the conceptual results from the hybrid morphological matrix approach and compares interactively constructed solutions to those returned by the non-interactive automated morphological matrix generator using a dog food sample packet counter as a case study.

scholarly journals Ls-II: An Improved Locust Search Algorithm for Solving Optimization Problems

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Octavio Camarena ◽  
Erik Cuevas ◽  
Marco Pérez-Cisneros ◽  
Fernando Fausto ◽  
Adrián González ◽  
...  
Keyword(s):  
Optimization Problems ◽  
Search Algorithm ◽  
Search Space ◽  
Optimization Method ◽  
Superior Performance ◽  
Solution Quality ◽  
Original Algorithm ◽  
Motion Models ◽  
Search Mechanism ◽  
Solitary Phase

The Locust Search (LS) algorithm is a swarm-based optimization method inspired in the natural behavior of the desert locust. LS considers the inclusion of two distinctive nature-inspired search mechanism, namely, their solitary phase and social phase operators. These interesting search schemes allow LS to overcome some of the difficulties that commonly affect other similar methods, such as premature convergence and the lack of diversity on solutions. Recently, computer vision experiments in insect tracking methods have conducted to the development of more accurate locust motion models than those produced by simple behavior observations. The most distinctive characteristic of such new models is the use of probabilities to emulate the locust decision process. In this paper, a modification to the original LS algorithm, referred to as LS-II, is proposed to better handle global optimization problems. In LS-II, the locust motion model of the original algorithm is modified incorporating the main characteristics of the new biological formulations. As a result, LS-II improves its original capacities of exploration and exploitation of the search space. In order to test its performance, the proposed LS-II method is compared against several the state-of-the-art evolutionary methods considering a set of benchmark functions and engineering problems. Experimental results demonstrate the superior performance of the proposed approach in terms of solution quality and robustness.

A New Concept of a Two-Dimensional Supersonic Relative Inlet Mach Number Compressor Cascade

2009 ◽  
Author(s):  
Toyotaka Sonoda ◽  
Markus Olhofer ◽  
Toshiyuki Arima ◽  
Bernhard Sendhoff
Keyword(s):  
Mach Number ◽  
Total Pressure ◽  
Optimization Method ◽  
Superior Performance ◽  
Compressor Cascade ◽  
Pressure Loss Coefficient ◽  
Supersonic Inlet ◽  
Flow Mechanisms ◽  
Improved Performance ◽  
Total Pressure Loss Coefficient

In this study, a numerical shape optimization method based on evolutionary algorithms coupled with a verified CFD solver has been applied to the ambitious target of a shock free 2-D supersonic inlet Mach number compressor cascade. The study is based on the DLR-PAV-1.5 supersonic compressor cascade designed by the pre-compression blading concept. The DLR cascade airfoil has been optimized using a verified CFD code. A superior performance of the optimized supersonic cascade with about 24% reduction of the total pressure loss coefficient compared to the original cascade has been realized. The flow mechanisms observable around the blade with improved performance and the resulting design concept are discussed in this paper.

A Hybrid-Type Expert System for the Design of Marine Power Plants Using AI Technique and Design Optimization Method

1987 ◽  
Author(s):  
S. Akagi ◽  
T. Tanaka ◽  
H. Kubonishi
Keyword(s):  
Expert System ◽  
Design Process ◽  
Numerical Optimization ◽  
Power Plants ◽  
Optimization Method ◽  
Design Tool ◽  
Production Rules ◽  
Type Representation ◽  
Cad System ◽  
Hybrid Type

Abstract A hybrid-type expert system is developed for supporting the initial design process of marine power plants. Firstly, discussion is given generally to understand design process in the view point of applying the AI technique effectively to design. Based on the result of the discussion, a hybrid-type expert CAD system with coupling the AI technique and the numerical optimization method is developed. In the system, the design knowledge is represented in the production rules, and the data of machineries consisting the plant are described by the frame-type representation. Through the system execution, it is ascertained that the system is effective not only as the design tool assisting designers but also as the tool instructing inexperienced designers.

Discrete sizing, cross-sectional shape, topology optimization, and material selection of a framed automotive body

2021 ◽  
pp. 095440702110626
Author(s):  
Chao Ma
Keyword(s):  
Weight Reduction ◽  
Material Selection ◽  
Extreme Points ◽  
Optimization Method ◽  
Test Problems ◽  
Manufacturing Cost ◽  
Cross Sectional ◽  
Automotive Body ◽  
Discrete Design Variables ◽  
Sectional Shape

This study proposed a discrete structural optimization method for a framed automotive body. Up to four types of discrete design variables are considered simultaneously, that is, the sizing, cross-sectional shape, topology, and material variables. Firstly, to solve the nonconvex and nonlinear optimization problem, the original non-dominated sorting genetic algorithm, the third version (NSGA-III), is adapted. An improved extreme points identification scheme and a new mutation operator are proposed to stabilize the normalization of the population and accommodate the manufacturing constraints, respectively. Two test problems demonstrate that the modified NSGA-III can handle continuous and discontinuous multiple objective optimization. Subsequently, the classical 10-bar truss is used to illustrate the proposed method. A weight reduction of 4.5 kg is achieved as compared to previous optimal designs in the literature. Finally, a framed automotive body is optimized for maximizing the first order natural frequency and minimizing the total mass, the maximum stresses and the maximum displacements in different load cases and the manufacturing cost. The results obtained by different optimization procedures are presented and discussed. The results demonstrate the feasibility and effectiveness of the proposed method. A weight reduction of 17.59% is achieved while other structural performances satisfy the design requirements.

scholarly journals Employing particle swarm optimization algorithm for shrinkage parameter estimation in generalized Liu estimator

2020 ◽  
Vol 8 (1) ◽  
pp. 10
Author(s):  
Qamar Abdulkareem Abdulazeez ◽  
Zakariya Yahya Algamal
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Optimization Method ◽  
Least Square ◽  
Superior Performance ◽  
Ridge Estimator ◽  
Swarm Optimization ◽  
Liu Estimator ◽  
Ordinary Least Square ◽  
Parameter Matrix

It is well-known that in the presence of multicollinearity, the Liu estimator is an alternative to the ordinary least square (OLS) estimator and the ridge estimator. Generalized Liu estimator (GLE) is a generalization of the Liu estimator. However, the efficiency of GLE depends on appropriately choosing the shrinkage parameter matrix which is involved in the GLE. In this paper, a particle swarm optimization method, which is a metaheuristic continuous algorithm, is proposed to estimate the shrinkage parameter matrix. The simulation study and real application results show the superior performance of the proposed method in terms of prediction error.   

Topology Optimization of Rigid-Body Systems Considering Collision Avoidance

2020 ◽  
Vol 142 (8) ◽  
Author(s):  
Fritz Stöckli ◽  
Kristina Shea
Keyword(s):  
Topology Optimization ◽  
Rigid Body ◽  
Collision Avoidance ◽  
Optimization Problems ◽  
Computational Design ◽  
Optimization Method ◽  
The Body ◽  
Graph Grammar ◽  
Automated Synthesis ◽  
Inertia Properties

Abstract Passive dynamic mechanisms can perform simple robotic tasks without requiring actuators and control. In previous research, a computational design method was introduced that integrates dynamic simulation to evaluate and evolve configurations of such mechanisms. It was shown to find multiple solutions of passive dynamic brachiating robots (Stöckli and Shea, 2017, “Automated Synthesis of Passive Dynamic Brachiating Robots Using a Simulation-Driven Graph Grammar Method,” J. Mech. Des. 139(9), p. 092301). However, these solutions are limited, since bodies are modeled only by their inertia properties and thus lack a shape embodiment. This paper presents a method to generate rigid-body topologies based on given inertia properties. The rule-based topology optimization method presented guarantees that the topology is manifold, meaning that it has no disconnected parts, while still connecting all joints that need to be part of the body. Furthermore, collisions with the environment, as well as with other bodies, during their predefined motion trajectories are avoided. A collision matrix enables efficient collision detection as well as the calculation of the swept area of one body in the design space of another body by only one matrix–vector multiplication. The presented collision avoidance method proves to be computationally efficient and can be adopted for other topology optimization problems. The method is shown to solve different tasks, including a reference problem as well as passive dynamic brachiating mechanisms. Combining the presented methods with the simulation-driven method from Stöckli and Shea (2017, “Automated Synthesis of Passive Dynamic Brachiating Robots Using a Simulation-Driven Graph Grammar Method,” J. Mech. Des. 139(9), p. 092301), the computational design-to-fabrication of passive dynamic systems is now possible and solutions are provided as STL files ready to be 3D-printed directly.

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