Preform Design Research Articles

Reliability-Based Design Optimization of Bearing Hub Preform for Minimizing Defects Considering Manufacturing Tolerance in Hot Forging Process

A study on the optimal design of preforms has previously been actively conducted as a method to solve defects such as voids and flash in forged products. However, previous research has generally been performed through deterministic optimization for ideal cases that do not take manufacturing tolerances into account. As a result, the application of such optimal designs in actual processes may be limited due to various factors such as material manufacturing tolerances and the machining environment of preforms. Therefore, this study conducted reliability-based optimization considering tolerances in billets and preforms. The objective of the study was to optimize the design of a bearing hub and minimize defects in the final product. When comparing deterministic optimization and reliability-based optimization, the former showed relatively superior results in terms of defect indicators but had a higher occurrence of voids and lower forming loads, increasing the probability of void occurrence. On the other hand, the reliability-based optimization showed relatively lower performance in quality improvement indicators, but it successfully met the target reliability of 99% by reducing the probability of defect occurrence. These results were derived using an approximate model based on the Kriging method, providing an optimal design that is practical and effective in actual manufacturing processes.

CNN-based preform design: effect of training data configuration on strain distribution in forged products

CNN-based preform design: effect of training data configuration on strain distribution in forged products

Knit-Mycelium Hybrids: Textile Design Strategies for Biofabrication Systems Based on Mycocrete Injection in 3D Knitted Tubular Formworks

This paper investigates the design potential of monolithically grown Mycelium-based Composites (MBCs), focusing on integrating 3D knitted formworks within the fabrication process. Mycelium has gained attention as a sustainable, biodegradable construction material with insulating and self-healing capabilities. While there have been advancements in MBC, challenges remain regarding geometrical complexity and design potential at scale through in situ practices. Recent interest has emerged in digital fabrication methods and mould creation using textile logic and CNC knitting. However, fabricating mycelium within tubular soft moulds present a lack of stability and uneven growth distribution. The novel technique using injection filling of Mycocrete, a viscous mycelium paste, overcomes this structural disintegration. This method enables the creation of complex designs within a two-staged fabrication process while providing high structural performance. The paper presents three case studies demonstrating the impact of hanging, draping, and internal shape integration as fabrication steps as design tools for geometrical possibilities and diversity of expressions. It examines the relationship between knitted soft preform design and biofabrication parameters in relation to design expression, scale and mycelium growth. The paper concludes by emphasising the significance of 3D knitted formworks in scaling up MBCs in the built environment and its potential for implementing textile design parameters in MBC expressions and geometries. The fabrication steps provide newfound design opportunities, opening possibilities for aesthetical, material-saving and functionally graded design approaches. Further research in this area holds promise for advancing sustainable construction and textile design practices.

Preform design to reduce forging load and grain size simultaneously in disk forging of IN718

In this study, we propose a new methodology for designing preform shapes for turbofan blisk and disk forgings of IN718 superalloy using a CNN (Convolutional Neural Network). The objective function of the preform design model is set to minimize grain size and reduce forging load. Various preform shape candidates were generated using NURBS (Non-Uniform Rational B-Splines) curves, defined by points on the target shape outline, and the grain size was calculated through FE (Finite Element) analysis based on the JMAK (Johnson-Mehl-Avrami-Kolmogorov) model to train the CNN model. The preform shapes derived from the proposed load and grain size-aware CNN model were compared and validated against those from previous studies regarding grain size and load reduction. An objective function f, which is capable of quantitatively expressing the load and grain size improvement, was developed for comparison and validation. The results showed an improvement of 19.64% for the blisk and 18.96% for the disk compared to previous studies. This research is expected to significantly contribute to the forging of aerospace components.

Optimizing profiled ring preforms for enhanced deformation uniformity using the isothermal field method

One of the main challenges faced by the profiled ring rolling (PRR) process is to ensure the deformation uniformity of the ring, which is closely related to the design of the ring preform. The paper explores the application of the isothermal field method (IFM) in designing preforms for PRR processes, targeting the aerospace sector's high-end equipment manufacturing. Through the integration of advanced computational models and practical design principles, a comprehensive approach involving IFM, finite element simulation, support vector machine modeling, and genetic algorithm optimization is employed to determine the geometric dimensions of rational preforms. The material flow behavior during the PRR process is analyzed, and the effects of different isotherms combinations on strain, stress and temperature distribution are discussed. The findings demonstrate that adjusting the preform's shape during the section forming stage can optimize the uniformity of strain, stress, and temperature within the forging. The stable ring rolling process revealed no macroscopic or microscopic defects, validating the design method of ring preform based on IFM is reasonable. The research contributes to advancing near-net shape forming technologies, offering a novel approach to preform design that marries theoretical analysis with practical manufacturability considerations.

Detailed preform design procedure considering the effect of heat treatment in IN718 disk forging

We investigated the impact of heat treatment on preform deduction during the hot forging of In718 turbine disks. Proposed preform design method leverages a Convolutional Neural Network (CNN) to aim for minimized damage and uniform grain size in the final forged products. For damage calculation, we employ the Lemaitre damage model, while the Johnson-Mehl-Avrami-Kolmogorov (JMAK) model is utilized for grain size calculation. The CNN, trained on datasets of NURBS-generated preform shapes and final forged disks from them, showed superior performance in terms of damage and grain size of forged disk compared with other existing approaches. Moreover, the results indicate that preforms deduced with heat treatment considerations can lead to significant improvements in forging results, including up to a 17% reduction in average grain size and a 16% decrease in standard deviation compared to preforms without heat treatment consideration. These results underscore the importance of considering heat treatment in preform design, offering valuable insights for industries where the integrity of forged products, like aerospace, is critical.

The Method of Ply Generating in Composite Laminate in Fibersim

In Fibersim the digital design of the composite preforms laying process begins with the creation of laminates, which define the required preforms and its plies. The digital design of ply-based laying process, zone-based laying process, multi-ply-based laying process, and the methods of multi-ply and zone-based laying process are elaborated.

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.

An analytical friction model for fibre tow slippage in Tailored Fibre Placement preforms based on pull-out experiments

Fibre tow slippage in conventional reinforcement forming is a major defect which can be turned into an additional degree of freedom in preforms made by Tailored Fibre Placement (TFP). Controlling slippage of reinforcing fibre tows, which are deposited on a conventional reinforcement using the TFP technology, is an advantage which enlarges the preform design space Fial et al. (2018). Moreover, when TFP is used to locally reinforce a conventional reinforcement, slippage of the deposited fibre tow during forming, is required depending on its orientation relative to the conventional reinforcement layout to avoid defects. Therefore, characterizing the friction behaviour of the reinforcing fibre tows is necessary to take advantage of its slippage as an additional degree of freedom. In this paper, an analytical friction model describing the interactions of the fibre tows with the backing material and the stitching yarn in TFP preforms is developed based on pull-out experiments. A parametric study allows expressing the parameters of the analytical friction model as function of the stitching parameters.

Micro Computed Tomography based stochastic design and flow analysis of dry fiber preforms manufactured by automated fiber placement

The effective design of channels in dry tape preforms is crucial for achieving desired preform permeability for successful resin injection for composites manufacturing using Automated Fiber Placement (AFP) process. Achieving target gaps and their locations in the AFP layup is extremely challenging. This work investigates the correlation between the spatial variability of the preforms and the in-plane permeability using an X-ray Computed Tomography (XCT) based characterization framework. The tomographic images of two different dry carbon tape preforms with different tape widths were used to generate realistic and XCT based stochastic models to be used for numerical permeability predictions. The variability in the tape placement by the robotic head and its effect on preform permeability was also examined through stochastic geometric modeling of the laid preform. A benchmark transient permeability measurement set-up was utilized to obtain experimental in-plane preform permeability through 2D radial mold filling. The in-plane numerical permeability values showed significant scatter, with a coefficient of variance of 75%–130%, which deviated from the experimental measurements by approximately one order of magnitude. These findings strongly re-affirm that the experimental permeability measurement technique based on transient mold filling of dry fiber AFP preforms is complex however, the XCT based stochastic modeling technique is an effective way to estimate the permeability of dry fiber AFP preforms virtually.

A novel method for design and simulation of 3D woven preform

Increasing demand for high-performance applications of composite materials requires an integral forming process for complex components. As a composite reinforcement, 3D (three-dimensional) woven fabric has advantages in producing near-net-shaped preforms. However, previous studies focused on plates with uniform thickness, which are often variable thicknesses or special-shaped parts in practical applications. Some structures are prepared by stitching and then formed in the mold, but this increases the fiber damage. This study proposes a fabric design method based on yarn movement. By controlling the movement direction and distance of each yarn, the warp path in the fabric can be designed, which cause the change of fabric structure and achieve the integrated forming of special-shaped preforms. Based on this method, a software package for the preforms design and simulation is developed, which can be used for various woven and 3D textiles to illustrate its versatility.

Preform design with increased materials utilization and processing map analysis for aluminum hot forging process

In this article the conventional aluminum hot crown forging process for mass production of shock absorber assembly is experimentally and numerically studied. The preform design method was proposed to improve the quality of post-forged product, save the material weight, and decrease manufacturing cost for finishing process. Finite element (FE) simulation software was employed to numerically analyze the material flow lines, strain, temperature, and effective stress distribution to reduce time and cost in obtaining the appropriate preform design. Furthermore, the software is used to extract the numerical results of power dissipation efficiency and instability from the processing map analysis of stress-strain rate material data in different temperature and strain conditions, which are useful parameters to analyze formability and microstructures of material. Then, the improved hot forging design was achieved by the combined-analysis of preforming design, material utilization, and processing map. The numerical results have accurately predicted the poor quality and serious underfilling defects in the conventional post-forged product, and finally the improved design have successfully diminished defects, met precision tolerances and satisfied quality requirements. The proposed design saves material weight up to 10.26 %, increases material utilization from 79.01 % to 88.08 % which improves the problem of excessive flash in the conventional case, and reduces the forging load up to 12.40 % which benefit the dies life. Two intriguing areas were microstructurally examined and the results showed that the grain sizes are adequately fine to satisfy the expected mechanical properties.

Study on the shear-pretension coupling behavior of 3D uniform and variable thickness woven fabrics

Pretension is regarded as an effective way to suppress the draping defects caused by the excessive shearing deformation of preforms during the manufacturing of woven composites. However, the research of shear-pretension coupling behavior on the 3D woven fabric uniform and variable thickness structures has not been carried out. In present study, the behavior of the two kinds of woven fabric structures is investigated. The picture frame shear test for fabrics are conducted with applied pre-tension for the work. The relationship between shear stress and shear angle under different pre-tension levels of the two kinds of fabrics is analyzed. Furthermore, the detailed comparison of shear-pretension coupling behavior between the two kinds of woven fabric structures is also analyzed. Finally, the effect of variable thickness condition on the in-plane shear properties for woven fabric variable thickness structure is investigated. The research provides experimental data support for the forming design of preforms of heterogeneous 3D composite structures.

A Systematic Review of Factors Affecting the Process Parameters and Various Measurement Techniques in Forging Processes

Forging is a primary manufacturing process used in several manufacturing industries. Aircraft and automobile industries are manufacturing products with high‐dimensional accuracy and quality that are highly precise or near the required shape. Customers require products that are free of cracks and fulfill their functional requirements. This leads to the advancement of the forging process due to its ability to form complicated and intricate shapes. Herein, a detailed review of the aspects of forging is given in which the optimization of factors like preform design, forging conditions, workpiece dimensions, die design, lubricant properties, and thermal treatment parameters are discussed, enhancing the tool life and forging quality of the product. The selection of die‐forging tool material and methods for enhancing the surface quality of forged products are also reviewed. The article also presents methods for measurement of forging quality, tool life, machine effectiveness, forging image acquisition, and forging parameters, which can significantly reduce the risk of error at every step of the forging process. This review serves as a reference for researchers to increase production rate, enhance the effectiveness of measurement system, and improve the quality of forged products with technological advancement.

Cyclic thermal shock behaviors of carbon fibers reinforced SiCN ceramics with bio-inspired Bouligand-like architectures

Ceramic matrix composites (CMCs) are commonly used for high temperature components in aircrafts. However, thermal shock, as a typical loading case, will cause high thermal stresses in CMCs resulting in brittle fracture failure, and material cracking caused by thermal shock can further reduce the effectiveness of thermal protection function. In the present paper, we propose a bionic hierarchical fiber preform design method to improve the thermal shock resistance of ceramics. The effect of architectures of fiber preforms of continuous carbon fiber-reinforced CMCs on the thermal shock resistance was investigated to understand its importance and the related mechanical mechanisms. Thermal shock (cycling) tests were performed with continuous carbon fibers reinforced SiCN ceramic matrix composites (Cf/SiCN) prepared by PIP. 3D micro-CT scan and three-point bending tests were also conducted to evaluated the resultant damage. The results showed that smaller internal damage and higher thermal shock resistance can be obtained in comparison to pure SiCN ceramics, and the underlying mechanism can be explained by the fact that smaller pitch angle can resist the through-thickness crack propagation via promoting diffused in-plane damage. The present study offers a possibility in developing biomimetic Cf/SiCN ceramics with excellent thermal shock behavior.

Automatic preform design and optimization for aeroengine disk forgings

To ensure a more uniform forging distribution microstructure and improve the service performance of aeroengine disk parts, an automated preform design method is proposed for integrated preform shape design and optimization based on the non-uniform rational B-spline (NURBS) curve, finite element method, and genetic algorithm (GA). First, the random preform shape graph is automatically constructed by the NURBS curve design criterion. The volume and shape complexity are used as the constraints of the preform. Second, the ratio of the mesh area within the set strain range to the total mesh area is used as the fitness function for the uniformity of deformation, and the GA is used for optimization. Finally, a large disk forging is an example of its optimal design. Results show that the deformation uniformity of the forgings is excellent, its fitness value is as high as 99.59%, and problems, such as folding, underfilling, and limited distribution of flash, do not exist, thereby verifying the effectiveness of the method. In addition, the method has the advantage of strong universality, that is, it can find the preform shape with good deformation uniformity for any shape forgings.

Preform necessity and preform design at hot closed-die forging – a general design approach

The parts obtained by forging are better than those manufactured by any other metalworking process in many aspects. This determines their widespread use where human safety and reliability are critically important. Industries such as aerospace, defence, automotive and agriculture, construction, mining are some of the largest customers using forged parts. The design of hot closed-die processes very often requires engineers to deal with two important challenges - the necessity of preform (intermediate) steps and the shape of these intermediate steps. A general design approach for determination of necessity of preforms and their shape at hot closed-die forging is presented in this article.

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.

A novel bottom-up methodology for design and fabrication of three-dimensional braided hybrid composites based on the law of yarn routing and grouping

A hybrid is an effective means to improve the comprehensive properties of composites. In the current article, by investigating the yarn routing and grouping law in three-dimensional braiding, a novel bottom-up methodology for the design and fabrication of three-dimensional braided hybrid composites is proposed based on the [ m, m] hybrid unit. Three-dimensional braided hybrid composites with different sizes of hybrid unit were prepared and drop-hammer based impact tests were conducted to study the composites' dynamic mechanical performances. It was found that the three-dimensional braided hybrid composites based on the bottom-up methodology present much better structural integrity and toughness than conventional ply-stacked hybrid counterparts and significant dependence of mechanical performances on the size of hybrid unit. We found that the smaller the size of hybrid unit, the better the mechanical performance. The results demonstrated the feasibility and effectiveness of the proposed bottom-up methodology and could enable the design and fabrication of three-dimensional braided preforms and composites with certain well designed structures and functions.

A Preform Design Approach for Uniform Strain Distribution in Forging Processes Based on Convolutional Neural Network

Abstract This study provides a preform design approach for uniform strain distribution in forging products based on a convolutional neural network (CNN). The appropriate preform design prevents underfill problems by improving the material flow inside forging dies and achieving a uniform strain distribution in forging products. The forging deformation process and mechanical properties are improved with a uniform strain distribution. The forging and strain distribution results are analyzed through rigid–plastic finite element forging simulations with different initial geometries. The simulation data are fed into the CNN model as an input array, from which the geometric characteristics are extracted by convolution operations with filters (weight array). The extracted features are linked to the considered initial shapes, which are input into the CNN model as an output array. The presented model derives the preform shape for a target forging with uniform strain distributions using the training weights. According to the training database, the proposed design method can be applied to different forging geometries without any iterations. By creating a number of low-level CNN (LC) models based on the training data, the efficiency of the preform design can be improved. The best preform among the derived preform candidates is chosen by comparing the forging results. Compared with previous studies using the same design criteria, the proposed model predicted the preform with a strain distribution improved by 16.3–38.4%.