Design Optimization of Machine-Tool Dynamics Based on Clarification of Competitive-Cooperative Relationships Between Characteristics

1987 ◽  
Vol 109 (1) ◽  
pp. 143-150 ◽  
Author(s):  
Masataka Yoshimura
Keyword(s):  
Machine Tool ◽  
Design Optimization ◽  
Structural Model ◽  
Optimization Methods ◽  
Optimization Method ◽  
Design Decision ◽  
Cooperative Relationships ◽  
Machine Tool Dynamics ◽  
Design Variables ◽  
Tool Dynamics

This paper proposes a design optimization method of machine-tool dynamics based on clarification of competitive and cooperative relationships between characteristics. Clarification of competitive and cooperative relationships between characteristics results in division of design variables into three groups. The design variables of each group are determined in each of the three-phase design optimization procedures. The design decision problem in each procedure is far simpler and easier than that in usual design optimization methods, in which all design variables are determined at the same time. The competitive and cooperative relations between characteristics are first clarified. Next, algorithmic procedures of the design optimization method are constructed. The method is demonstrated on a structural model of a milling machine.

Design Optimization of Machine-Tool Structures With Respect to Dynamic Characteristics

1983 ◽  
Vol 105 (1) ◽  
pp. 88-96 ◽  
Author(s):  
M. Yoshimura ◽  
T. Hamada ◽  
K. Yura ◽  
K. Hitomi
Keyword(s):  
Machine Tool ◽  
Design Optimization ◽  
Dynamic Characteristics ◽  
Machine Tools ◽  
Structural Model ◽  
Optimization Method ◽  
Practical Applications ◽  
Design Variables ◽  
Design Changes ◽  
Machine Tool Structures

This paper proposes a design optimization method in which simplified structural models and standard mathematical programming methods are employed in order to optimize the dynamic characteristics of machine-tool structures in practical applications. This method is composed of three phases: (1) simplification, (2) optimization, and (3) realization. As design variables employed in this optimization are greatly reduced, machine-tool structures are optimized effectively in practice. With large design changes being conducted through this multiphase procedure, dynamic characteristics of machine tools can be greatly improved. This method is demonstrated on a structural model of a vertical lathe.

Optimization of Machine System Designs Based on Decomposition and Hierarchical Ordering of Criteria and Design Variables

2000 ◽  
Author(s):  
Masataka Yoshimura ◽  
Ryousuke Nomura
Keyword(s):  
Design Optimization ◽  
Optimization Methods ◽  
Optimization Method ◽  
Hierarchical Optimization ◽  
Local Optimum ◽  
Optimization Strategy ◽  
Cooperative Relationships ◽  
Design Variables ◽  
Hierarchical Ordering ◽  
Basic Characteristics

Abstract Designs of machine products routinely have so many characteristics to be evaluated that usual design optimization methods often result in an unsatisfactory local optimum solution. In order to overcome this problem, this paper proposes a design optimization method based on decomposition by substructuralization and subsequent hierarchical ordering, considering the both conflicting and cooperative relationships between the characteristics under evaluation. First of all, each characteristic is divided into simpler basic characteristics. The pool of design variables is also divided into smaller groups, according to specific design features. Next, the relationships between the basic characteristics and the divided design variables, as well as the relationships among the characteristics themselves, are systematically identified and clarified. Then, based on this clarification, and after setting a core characteristic derived from the primary performance characteristic for the product under consideration, an optimization strategy and detailed hierarchical optimization procedures are constructed. In this paper, the proposed method is applied to machine tool structures and transportation products.

Design Optimization of Machine Structures Based on Multiphase Structural Modeling of Ideal, Intermediate, and Detailed Models

1990 ◽  
Author(s):  
Masataka Yoshimura
Keyword(s):  
Machine Tool ◽  
Design Optimization ◽  
Structural Model ◽  
Structural Modeling ◽  
Optimization Method ◽  
Ideal Model ◽  
Detailed Model ◽  
Intermediate Model ◽  
The Ideal

Abstract This paper proposes a design optimization method consisting of the multiphase structural modeling of ideal, intermediate, and detailed models for machine structures. In this method, the ideal characteristics are first obtained for a specific ideal model. Then, the detailed designs are determined so that the characteristics in the detailed model are as close to the ideal characteristics as possible. For easily and surely obtaining the final detailed designs, an intermediate model is introduced between the ideal model and the detailed model. This method not only effectively generates optimum detailed designs of machine structures but also brings about an easy realization of the optimum characteristics in practical manufactured machine products. The proposed method is applied to a machine-tool structural model for demonstrating the effectiveness of the method.

Design Optimization of Machine-Tool Structures Considering Manufacturing Cost, Accuracy, and Productivity

1984 ◽  
Vol 106 (4) ◽  
pp. 531-537 ◽  
Author(s):  
M. Yoshimura ◽  
Y. Takeuchi ◽  
K. Hitomi
Keyword(s):  
Machine Tool ◽  
Design Optimization ◽  
Structural Model ◽  
Structural Models ◽  
Optimization Method ◽  
Machining Accuracy ◽  
Manufacturing Cost ◽  
Structural Members ◽  
Machine Tool Structures ◽  
Machining Productivity

This paper proposes a multiphase design optimization method using simplified structural models in order to minimize manufacturing cost of machine-tool structures under constraints of machining accuracy, machining productivity, and local deformations of structural members. The manufacturing cost is divided into three components—material cost, welding cost, and machining cost, each of which is minimized in the multiphase optimization process. The method is demonstrated on a structural model of a double-column machine tool.

Multi Objective Design Optimization of Two Bar Truss Using NSGA II and TOPSIS

2014 ◽  
Vol 984-985 ◽  
pp. 419-424
Author(s):  
P. Sabarinath ◽  
M.R. Thansekhar ◽  
R. Saravanan
Keyword(s):  
Design Optimization ◽  
Optimization Problems ◽  
Optimization Methods ◽  
Optimal Solutions ◽  
Objective Functions ◽  
Nsga Ii ◽  
Multi Objective ◽  
Total Displacement ◽  
Design Variables ◽  
Conflicting Objectives

Arriving optimal solutions is one of the important tasks in engineering design. Many real-world design optimization problems involve multiple conflicting objectives. The design variables are of continuous or discrete in nature. In general, for solving Multi Objective Optimization methods weight method is preferred. In this method, all the objective functions are converted into a single objective function by assigning suitable weights to each objective functions. The main drawback lies in the selection of proper weights. Recently, evolutionary algorithms are used to find the nondominated optimal solutions called as Pareto optimal front in a single run. In recent years, Non-dominated Sorting Genetic Algorithm II (NSGA-II) finds increasing applications in solving multi objective problems comprising of conflicting objectives because of low computational requirements, elitism and parameter-less sharing approach. In this work, we propose a methodology which integrates NSGA-II and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for solving a two bar truss problem. NSGA-II searches for the Pareto set where two bar truss is evaluated in terms of minimizing the weight of the truss and minimizing the total displacement of the joint under the given load. Subsequently, TOPSIS selects the best compromise solution.

Smart Optimization of Machine Systems Using Hierarchical Genotype Representations

1999 ◽  
Author(s):  
Masataka Yoshimura ◽  
Kazuhiro Izui
Keyword(s):  
Structural Design ◽  
Hierarchical Structures ◽  
Optimization Methods ◽  
Optimization Method ◽  
Design Problems ◽  
Design Variables ◽  
The Hierarchical Structure ◽  
Machine Systems ◽  
System Designs ◽  
Crossover And Mutation

Abstract 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.

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