Machining fixture locating and clamping position optimization using genetic algorithms Abstract Deformation of the workpiece may cause dimensional problems in machining。 Supports and locators are used in order to reduce the error caused by elastic deformation of the workpiece。 The optimization of support, locator and clamp locations is a critical problem to minimize the geometric error in workpiece machining。 In this paper, the application of genetic algorithms (GAs) to the fixture layout optimization is presented to handle fixture layout optimization problem。 A genetic algorithm based approach is developed to optimise fixture layout through integrating a finite element code running in batch mode to compute the objective function values for each generation。 Case studies are given to illustrate the application of proposed approach。 Chromosome library approach is used to decrease the total solution time。 Developed GA keeps track of previously analyzed designs; therefore the numbers of function evaluations are decreased about 93%。 The results of this approach show that the fixture layout optimization problems are multi-modal problems。 Optimized designs do not have any apparent similarities although they provide very similar performances。75753

Keywords: Fixture design; Genetic algorithms; Optimization

1。 Introduction

Fixtures are used to locate and constrain a workpiece during a machining operation, minimizing workpiece and fixture tooling deflections due to clamping and cutting forces are critical to ensuring accuracy of the machining operation。 Traditionally, machining fixtures are designed and manufactured through trial-and-error, which prove to be both expensive and time-consuming to the manufacturing process。 To ensure a workpiece is manufactured according to specified dimensions and tolerances, it must be appropriately located and clamped, making it imperative to develop tools that will eliminate costly and time-consuming trial-and-error designs。 Proper workpiece location and fixture design are crucial to product quality in terms of precision, accuracy and finish of the machined part。 

Theoretically, the 3-2-1 locating principle can satisfactorily locate all prismatic shaped workpieces。 This method provides the maximum rigidity with the minimum number of fixture elements。 To position a part from a kinematic point of view means constraining the six degrees of freedom of a free moving body (three translations and three rotations)。 Three supports are positioned below the part to establish the location of the workpiece on its vertical axis。 Locators are placed on two peripheral edges and intended to establish the location of the workpiece on the x and y horizontal axes。 Properly locating the workpiece in the fixture is vital to the overall accuracy and repeatability of the manufacturing process。 Locators should be positioned as far apart as possible and should be placed on machined surfaces wherever possible。 Supports are usually placed to encompass the center of gravity of a workpiece and positioned as far apart as possible to maintain its stability。 The primary responsibility of a clamp in fixture is to secure the part against the locators and supports。 Clamps should not be expected to resist the cutting forces generated in the machining operation。 

For a given number of fixture elements, the machining fixture synthesis problem is the finding optimal layout or positions of the fixture elements around the workpiece。 In this paper, a method for fixture layout optimization using genetic algorithms is presented。 The optimization objective is to search for a 2D fixture layout that minimizes the maximum elastic deformation at different locations of the workpiece。 ANSYS program has been used for calculating the deflection of the part under clamping and cutting forces。 Two case studies are given to illustrate the proposed approach。

2。 Review of related works

Fixture design has received considerable attention in recent years。 However, little attention has been focused on the optimum fixture layout design。 Menassa and DeVries[1]used FEA for calculating deflections using the minimization of the workpiece deflection at selected points as the design criterion。 The design problem was to determine the position of supports。 Meyer and Liou[2] presented an approach that uses linear programming technique to synthesize fixtures for dynamic machining conditions。 Solution for the minimum clamping forces and locator forces is given。 Li and Melkote[3]used a nonlinear programming method to solve the layout optimization problem。 The method minimizes workpiece location errors due to localized elastic deformation of the workpiece。 Roy andLiao[4]developed a heuristic method to plan for the best supporting and clamping positions。 Tao et al。[5]presented a geometrical reasoning methodology for determining the optimal clamping points and clamping sequence for arbitrarily shaped workpieces。 Liao and Hu[6]presented a system for fixture configuration analysis based on a dynamic model which analyses the fixture–workpiece system subject to time-varying machining loads。 The influence of clamping placement is also investigated。 Li and Melkote[7]presented a fixture layout and clamping force optimal synthesis approach that accounts for workpiece dynamics during machining。 A combined fixture layout and clamping force optimization procedure presented。They used the contact elasticity modeling method that accounts for the influence of workpiece rigid body dynamics during machining。 Amaral et al。 [8] used ANSYS to verify fixture design integrity。 They employed 3-2-1 method。 The optimization analysis is performed in ANSYS。 Tan et al。 [9] described the modeling, analysis and verification of optimal fixturing configurations by the methods of force closure, optimization and finite element modeling。  采用遗传算法优化加工夹具定位英文文献和中文翻译:http://www.youerw.com/fanyi/lunwen_86771.html