Preform Optimization Research Articles

Minimum cost, stability constrained preform optimization for hybrid manufacturing

This paper describes a new mathematical framework for optimum preform design in hybrid manufacturing, where additive manufacturing is combined with machining. The framework minimizes the combined cost for deposition and machining, while respecting the constraint imposed by machining stability (i.e., machining parameters that produce chatter are rejected). A case study is presented where a thin wall design is parameterized to describe the overbuilt deposition geometry. A grid of candidate solutions is selected to calculate cost and the stability limit considering both the part and tool dynamics. The minimum cost option is deposited and machined to demonstrate the approach.

Time-cost-quality tradeoff considering resource-scheduling problems

Duration, cost, and resources are defined as project constraints. Consequently, in each project, one of these constraints is received attention compared with another. Thus, the abilities of construction project manager should include balancing these constraints in a way that all the project objectives are fulfilled. Achieving this balance is conducted by determining the best alternative for each activity, while minimizing project total cost and duration and satisfies resources constraints as well as smoothing resource histograms. For that purpose, this study aims at optimizing project schedule to provide this balance by using multi construction methods which is mainly based on multiskilling strategy. As will be discussed, to achieve this goal, a model was developed and genetic algorithm is used to preform optimization. This study contributes to the body of knowledge a model able to produce schedules with appropriate project duration, cost, and quality, also satisfy resource constraints with most leveled histograms.

A framework for hybrid manufacturing cost minimization and preform design

This paper describes preform design optimization in hybrid additive-subtractive manufacturing. In hybrid manufacturing, the question of what form and what geometry the additive preform should take has largely been a matter of intuition and experience, or trial and error. The choice of a more optimal preform depends on the target parameters, such as stiffness, cost, or lead time. We demonstrate a framework for preform optimization using static stiffness, and then the combined cost of additive and subtractive manufacturing, while respecting stable cutting conditions for the tool-part combination. The procedure is illustrated by comparing three preform geometries for a thin wall.

Numerical simulation for expansion of preform and optimization of preform in thermoset composites

The expansion of preform and the optimization of preform have become important steps in the molding process. At present, there are some questions in the expansion of thermoset composite material preform and precompression, for example, the inaccurate dimensions, cracks, and wrinkles. For the expansion of preform, the finite element inverse algorithm is used as the expansion algorithm, and then the initial solution is optimized by the arc length mapping method, the expansion of preform is realized by the iterative equation which is solved by the ABAQUS solver. The effectiveness of the expansion of preform is verified through the comparison between the finite element inverse algorithm with DYNAFORM. The optimization of the precompression process is researched in order to solved the problems of cracks and wrinkles in the integral precompression method of preform. Firstly, the precompression sequence is adjusted by the precompression method, and then the precompression direction is optimized by the genetic algorithm. Through numerical simulation, the maximum thinning rate is reduced to 13%, and the maximum thickening rate is reduced to 6%, which improve the problems of cracks and wrinkles of preform, and the effectiveness of the optimization method is verified.

Optimization of Preform for Stub Axle Forging Using Simulation Software

There is a growing demand for more efficient and economic manufacturing process to improve product quality, reduce production cost, reduce lead time and increase productivity. The application of computer aided design and manufacturing (CAD/CAM) techniques to forging is becoming increasingly popular as the resulting improvements in yield and productivity. Modeling and simulation have become a major concern in recent and advanced research. In this paper die design for forging of an automobile component “Stub Axle” is presented. In die forging process, complex shape component cannot be made in one stage and therefore, the use of preform die becomes essential. The initial preform design was carried out by conventional method. The simulation has been carried out using software DEFORM-3D. The main goal of this study is to design an optimal preform shape resulting an optimal initial billet selection. Keywords:CAD/CAM, Preform, DEFORM-3D, Simulation, Forging

Preform optimization for the anchor shackle during closed die forging process on one ton hammer

In a closed die forging process material utilization and its control is more important for economical forging. The initial geometry of the forged part is known as a preform, for the volume of the preform, it is necessary to consider the volume of the finished part and the volume of flash. Burning and machining allowances are also to be considered to achieve the high quality of the part. It is very difficult to accurately calculate the volume requirement for the preform and also it is impractical and uneconomical to do the sample tryout on the shop floor. Now a day’s finite element analysis (FEA) is very useful for the simulation of the closed die hot forging process to optimize the preform volume. Anchor shackle is used in the transmission line and it is manufactured with the help of a closed die hot forging process on a one-ton hammer. In this paper finite element analysis is used for the optimization of preform volume for the anchor shackle. Three preforms have been designed in Creo 4.0 and analyzed for the completely filled cavity of dies at the end of the simulation process. The results of finite element simulation show that preform 2 with the size of Ø36 mm × 100 mm long is optimum and it is also validated with the actual experiment result.

Preform Optimization of Functional Bevel Gear for Warm Forging Processes

Optimizing the design of the preform shapes used in warm forging processes is important for improving quality and reducing cost. The main objective of this study was to optimize the design of a preform shape for a bevel gear to obtain a good product and to improve the efficiency of the warm forging process. Quality parameters included in the fitness function were form-filling, preform volume, and complexity. First, basic principles pertaining to the cross sections, thickness, and concave radius of a bevel gear preform were applied in conjunction with certain theoretical expressions and empirical methods to produce an initial preform shape and initial geometry. Subsequently, mathematical evaluation models of the fitness function were generated to optimize the preform shape. Finally, a genetic algorithm was applied to solve the multi-objective optimization problem, and the best solution was determined considering the accuracy of the results, within the close proximity set generated by the multi-objective genetic algorithm optimization. The optimal preform shape was decreased in weight by approximately 8% and its flash dimensions were decreased by about 5% compared to the initial preform shape. This research is expected to improve the efficiency of fabricating bevel gears by means of warm forging processes.

Metamodelling of the Correlations of Preform and Part Performance for Preform Optimisation in Sheet Moulding Compound Processing

In the design of parts consisting of long-fibre-reinforced Sheet Moulding Compounds (SMC), the potential for the optimisation of processing parameters and geometrical design is limited due to the high number of interdependent variables. One of the influences on fibre orientations and therefore mechanical part performance is the initial filling state of the compression moulding tool, which is defined by the geometry and positioning of the SMC preform. In the past, response surface methodology and linear regression analysis were successfully used for a simulation-based optimisation of rectangular preform size and position in regard to a part performance parameter. However, the computational demand of these increase exponentially with an increase in the number of design variables, such as in the case of more complex preform geometries. In this paper, these restrictions are addressed with a novel approach for metamodelling the correlation of preform and the resulting mechanical part performance. The approach is applied to predicting the maximum absolute deflection of a plate geometry under bending load. For metamodelling, multiple neural networks (NN) are trained on a dataset obtained by process and structural simulation. Based on the discretisation of the plate geometry used in these simulation procedures, the binary initial filling states (completely filled/empty) of each element are used as inputs of the NNs. Outputs of the NNs are combined by ensemble modelling to form the metamodel. The metamodel allows an accurate prediction of maximum deflection; subsequent validation of the metamodel shows differences in predicted and simulated maximum deflection ranging from 0.26% to 2.67%. Subsequently, the metamodel is evaluated using a mutation algorithm for finding a preform that reduces the maximum deflection.

Precise Forming of Complex Magnesium Alloy Components Based on Finite Element Method and Quantitative Preforming Design

To solve the difficulties associated with integral precise extrusion forming for complex components of magnesium alloy, Deform-3D finite element simulation software was used to conduct numerical analyses for the forming process. Different extrusion schemes were used for determining the overall extrusion difficulties associated with special-shaped thin-walled complex components of magnesium alloy. The effects of a preformed blank on the filling and formation of folding defects in the forming process were studied. Based on the principle of minimum energy in the process of plastic deformation and the law of least resistance, volume predistribution and equal distance flow quantitative compensation methods were put forward. These methods were used to optimize the size and structure of the preform, forming a uniform material flow distribution. They also enabled one to manifest a uniform material flow velocity distribution, reduce the forming load, and avoid the creation of folding and filling defects during the final forming, for the realization of an efficient and reliable preform optimization design for magnesium alloy profiled complex components. The results obtained from a forming test, microstructure and mechanical properties test showed that the mechanical properties of the extruded component all met the service indexes. This design method can provide a theoretical reference for preforming design of profiled complex components.

Preform optimization of a brake drum part based on quasi-equipotential field and response surface methods

Taking the hot forging preform design of the brake drum part as the research object, a method for designing the forging preform based on the analysis of the Quasi-equipotential Field Method and Response Surface Method is established. Based on the analysis of the distribution and characteristics of the equipotential field between the blank and the final forging, the inverse fitting method was used to extract the equipotential lines and point cloud noise reduction, fitting, and smoothing processing to achieve efficient and accurate reconstruction of the equipotential lines. The non-uniform scaling method is used to achieve a reasonable scaling of the preform and a reasonable control of its material distribution. Taking the forging filling rate as the target response, the potential value and the forging volume ratio as design variables, a response surface model is established, and the volume ratio and potential value of the pre-forged part and the final forged part are optimized to obtain 1.023 and 0.167 V, respectively. Finally, the optimized preformed shape is obtained. Simulation results show that it can achieve good effects of full filling, no defects, high material utilization, and low forming load.

Metal flow behavior of P/M connecting rod preform in flashless forging based on isothermal compression and numerical simulation

The intrinsic properties and the damage behavior of powder metallurgy (P/M) connecting rod preform have significant effects on its metal flow behavior during flashless forging into its final complex shape with substantial densification. The P/M material constitutive equation were established using isothermal compression tests, and then used to study the metal flow behavior of a P/M connecting rod preform during flashless forging based on finite element modelling (FEM). Moreover, the preform geometry was designed based on these metal flow mechanisms. Experiments and flashless forging of P/M connecting rod preforms were performed in order to verify the accuracy of the simulations. The simulated results are well consistent with the experimental results. Results showed that the shank is much more prone to cracking due to the higher deformation rate and the faster cooling rate. The optimal dimensions of the P/M preform were obtained. When the preform geometry are optimized, the average density of the connecting rod increases homogeneously, and becomes superior to that of the original shape. This work suggests that the geometry of the preform can be designed efficiently based on our models. This work can help to derive a P/M connecting rod preform optimization methodology, which can offer the possibility of improving the quality of the connecting rods efficiently.

Multi-objective preform optimization for spherical hinge mandrel based on response surface methodology

The multi-objective optimization was studied in application of response surface method and orthogonal design for a preform design of vehicle thrust rod spherical hinge mandrel. Firstly, taking deformation uniformity and mold filling completeness as objectives, then an orthogonal experiment was designed to acquire main factors which influence total deformation quality. The effects of two main factors were precisely predicted through MATLAB and the results were discussed by optimal graphics. Secondly, on basis of optimized results, a second-order response surface model was established through equant design. The model was designed for preform re-optimization taking lower forging load and mold maximum effective stress as objectives. In application of preform optimization method, the best polytechnic parameters were selected, and qualified products were produced.

Design of a genetic algorithm to preform optimization for hot forging processes

To this day, the design of preforms for hot forging processes is still a manual trial and error process and therefore time consuming. Furthermore, its quality vastly depends on the engineer’s experience. At the same time, the preform is the most influencing stage for the final forging result. To overcome the dependency on the engineer’s experience and time-consuming optimization processes this paper presents and evaluates a preform optimization by an algorithm for cross wedge rolled preforms. This algorithm takes the mass distribution of the final part, the preform volume, the shape complexity, the appearance of folds in the final part and the occurring amount of flash into account. This forms a multi-criteria optimization problem resulting in large search spaces. Therefore, an evolutionary algorithm is introduced. The developed algorithm is tested with the help of a connecting rod to estimate the influence of the algorithm parameters. It is found that the developed algorithm is capable of creating a suitable preform for the given criteria in less than a minute. Furthermore, two of the five given algorithm parameters, the selection pressure und the population size, have significant influence on the optimization duration and quality.

The use of function-driven shape definition method and GRA–EMM-based Taguchi method to multi-criterion blade preform optimization

For a blade with complex shape, preform design plays an important part in the quality of an achieved part in the forging process. So many optimization methods were developed in many researches to obtain an optimal preform. However, in these researches, they lack accuracy and efficiency in defining preform shape, and there is no systematical strategy of implementing multi-criterion optimization processes. In order to overcome these defects, a function-driven shape definition method was proposed in this paper. This method can transform geometrical shape into numerical variables which define geometrical shape easily and can be used in mathematical functions in such methods as Taguchi method and response surface method. Besides, a novel Taguchi method coupling with gray relational analysis (GRA) and entropy measurement method (EMM) was developed, which provides a systematic way of optimizing preforms from the perspective of multi-criterion. In this method, GRA transforms multiple objectives into gray relational grade and EMM determines the weights of objectives. Finally, these two methods were applied in blade preform optimization to validate their effectiveness and efficiency. The results showed that the optimized blade was decreased by 16.6% in strain variance and by 20.2% in total load.

Exploring Filling Law of Small Fillet of Dual Clutch Hub

In extruding the dual clutch hub with small fillet gear, the filling of small fillet gear is not complete due to the large forming resistance. A method of preforming the blank into a concave shape is proposed. The mechanical analysis and finite element simulation are used to analyze the principle that the blank of concave shape can promote the filling of small fillet gear, stamping and extruding are both used to form the dual clutch hub and the preform is used to simulate the fillet gear’s extruding to analyze the influence of the geometric parameters of the preform on the forming quality. The mapping relationship between the geometric parameters of the preform and the size of unfilled fillet gear is established by using the BP neural network. The multi-objective genetic algorithm is used to optimize the geometric parameters of the preform. From the results we can see that the frictional resistance decreases due to reduced contact area between the blank and the mold when the section shape of the blank is concave, and at the same time, the tangential thrust is generated on the blank, so the filling of small fillet gear is better; BP neural network combined with genetic algorithm can reliably optimize the geometric parameters of the preform. The filling performance of the fillet gear is better under the optimal preform, and the forming quality of the dual clutch hub is improved. The experimental result verified the feasibility of the method and the accuracy of the simulation.

Preform Optimization for Bevel Gear of Warm Forging Process

Preform design is an important aspect in consideration of the improvement of quality and reduction of cost in warm forging process. Bevel gear being a key component of drive mechanisms in automotive industry requires lot of attention to its complex shape design optimization. A multi-objective optimization problem in designing preforms of warm forging for bevel gear by using genetic algorithm is solved and presented in this paper. The main objective of this study is to design an optimal preform part, which can get a better quality and the reliable preform shape systematically and theoretically.

Preform optimization and microstructure analysis on hot precision forging process of a half axle flange

Precision forging process of a half axle flange was studied based on numerical simulation and experiment. The preform shape was optimized to avoid the forging defects, and the microstructure of initial billet and obtained forging was also examined. The results showed that the unreasonable material flow behavior can cause the defects of laps and under-filling during final forging process. Through increasing the load surface and adding transition chamfer in the joint having dramatic variation of cross section, the preform shape was optimized and the forging defects were avoided. Moreover, the forging load was reduced to one third of the initial process after optimization. Both the grain growth and the recrystallization were observed during hot forging. However, due to the non-uniform distribution of strain, stress, and flowing velocity, the grain size and precipitation of cementite varied significantly in different positions of the obtained forging part.

Initial position optimization of preform for large-scale strut forging

The titanium alloy strut is a key load-bearing part for landing gear in aircraft. Closed-die forging with flash is adopted to manufacture the titanium alloy strut. The initial position of preform also has a notable influence on the cavity fill and metal lost into flash in the forging process. Complete die filling and even metal lost into flash at different portions of forging are the best forging process. Thus, an optimization method of initial position of preform for large-scale strut forging was developed based on the cavity fill and flash size. According to the geometrical characteristics and the deformation characteristics, a design variable x (description of initial position) and the fill indexes η 1 and η 2 were selected and defined. The objective function y consists of fill indexes. Numerical simulation combining algorithm of dichotomy to generate sampling data, and then the objective function can be produced. The finite element analysis was carried out for the optimum initial position searched by the objective function. If the simulation results is in the error range (such as < 5%), the optimum initial position was obtained, else the simulation results were added into sampling data to improve the objective function and the above steps were repeated. By using a developed optimization method, the initial position of preform for a large-scale titanium alloy strut forging process was determined after one improvement for objective function, where 5% is adopted as stop criteria in optimization procedure.

Preform optimization for hot forging processes using an adaptive amount of flash based on the cross section shape complexity

In multistage hot forging processes, the preform shape is the parameter mainly influencing the final forging result. Nevertheless, the design of multistage hot forging processes is still a trial and error process and therefore time consuming. The quality of developed forging sequences strongly depends on the engineer’s experience. To overcome these obstacles this paper presents an algorithm for solving the multi-objective optimization problem in designing preforms. Cross wedge rolled preforms were chosen as subject of investigation. An evolutionary algorithm is introduced to optimize the preform shape taking into account the mass distribution of the final part, the preform volume and the shape complexity. A crucial factor in preform optimization for hot forging processes is the amount of flash. Therefore an equation for improving the amount of flash is derived. The developed algorithm is tested using two connecting rods with different shape complexities as demonstration parts.

Mechanism of split-flow forming characteristics in plastic forming processing

The axial split-flow forming can be used to improve the metal flow and effectively reduce the forming force of large complex components. In this paper, in order to figure out the axial split-flow characteristics in the plastic forming, the flow regularity of the each deformation area in the material during the process of split-flow forming is studied based on the classical plasticity theory, the relationship between the split-flow area radius and the geometric parameters of the mold, and blank is analyzed with the analytic method of plastic mechanics, and a mathematical model for the split-flow area radius is built. The test shows that the model can be used to provide a theoretical reference to the accurate design on the axial split-flow forming of blank. Based on the energy theory and considering the complex coefficient, a mathematical model for the forming force of the axial split-flow forming unit is built. With a comparison among the forming experiments and finite element simulation analyses under different temperatures, the gray correlation degree between the model and the practical data in the experiment is 0.91, higher than 0.83 got by the traditional method. The developed model can reduction of the time in the preform optimization process and improvement the accuracy of forming force calculate in axial flow-split forming process. The result of this work can be used to theoretical guidance for practical engineering application of preforming and optimal design in axial split-flow precision forming.