A virtual process chain for sheet molding compound (SMC) composites is established and validated by means of experimental investigations on a demonstrator structure. The flow in the compression molding step is simulated via a Coupled-Eulerian-Lagrangian approach using an anisotropic non-Newtonian fluid flow model. Evolution of the fiber orientation distribution (FOD) is described by Jeffery's equation. The predicted FOD is mapped to structural simulations employing a neutral data format. A mean-field anisotropic damage model is used to predict the damage evolution in the demonstrator. Simulated FOD at the end of the compression molding is validated by computer tomography. Structural simulations are validated by means of a cyclic four-point bending test on the demonstrator. The predicted results show increased accuracy with the experiments by transferring FOD data within the virtual process chain. Critical points of high damage concentrations leading to failure agree with the experimental observations.

Virtual process chain of sheet molding compound: Development, validation and perspectives

The manufacturing process of Sheet Molding Compounds (SMC) induces a reorientation of fibers during the flow, which influences local properties and is of interest for structural computations. Typically, the reorientation is described with an evolution equation for the second order fiber orientation tensor, which requires a closure approximation and multiple empirical parameters to describe long fibers. However, CT scans of SMC microstructures show that fiber bundles stay mostly intact during molding. Treating hundreds of fibers in such a bundle as one instance enables direct simulation on component scale. This work proposes a direct simulation approach, in which bundle segments experience Stokes’ drag forces and opposing forces are applied to the fluid field. The method is applied to specimens with a double-curved geometry and compared to CT scans. The Direct Bundle Simulation provides increased accuracy of fiber orientations and enables prediction of fiber-matrix separation with affordable computational effort at component scale.

/pdf/direct-bundle-simulation-approach-for-the-compression-2uc4xa1gv4.pdf

Direct Bundle Simulation approach for the compression molding process of Sheet Molding Compound

Fiber reinforced polymers are key materials across different industries. The manufacturing processes of those materials have typically strong impact on their final microstructure, which at the same time controls the mechanical performance of the part. A reliable virtual engineering design of fiber-reinforced polymers requires therefore considering the simulation of the process-induced microstructure. One relevant microstructure descriptor in fiber-reinforced polymers is the fiber orientation. This work focuses on the modeling of the fiber orientation phenomenon and presents a historical review of the different modelling approaches. In this context, the article describes different macroscopic fiber orientation models such as the Folgar-Tucker, nematic, reduced strain closure (RSC), retarding principal rate (RPR), anisotropic rotary diffusion (ARD), principal anisotropic rotary diffusion (pARD), and Moldflow rotary diffusion (MRD) model. We discuss briefly about closure approximations, which are a common mathematical element of those macroscopic fiber orientation models. In the last section, we introduce some micro-scale numerical methods for simulating the fiber orientation phenomenon, such as the discrete element method (DEM), the smoothed particle hydrodynamics (SPH) method and the moving particle semi-implicit (MPS) method.

https://www.mdpi.com/2504-477X/4/2/69/pdf

Fiber Orientation Predictions—A Review of Existing Models

Robotic grasping has become increasingly important in many application areas such as industrial manufacturing and logistics. Because of the diversity and uncertainty of objects and environments, common grippers with one single grasping mode face difficulties to fulfill all the tasks. Hence, we proposed a soft gripper with multiple grasping modes in this study. The gripper consists of four modular soft fingers integrated with layer jamming structure and tendon-driven mechanism. Each finger's rotating shaft of the base uses a torsional spring to decouple the bending deformation and relative rotation. An octopus-mimicking vacuum sucker is installed in the fingertip to generate suction. The effectiveness of the bending deformation and variable stiffness of the design were proved by finite element simulation. Thus, the control model of the finger was built, and the control strategy of multimode grasping of the gripper was proposed. Three control modes were designed to realize the four anthropomorphic grasping modes, including wrap, pinch, hook, and suck. Furthermore, the grasping performance was evaluated to show the abilities. The experiments indicated the superior performance of the proposed gripper and the multimode grasping ability that satisfies various grasping tasks. 

Multimode Grasping Soft Gripper Achieved by Layer Jamming Structure and Tendon-Driven Mechanism

Robotic grasping has become increasingly important in many application areas such as industrial manufacturing and logistics. Because of the diversity and uncertainty of objects and environments, common grippers with one single grasping mode face difficulties to fulfill all the tasks. Hence, we proposed a soft gripper with multiple grasping modes in this study. The gripper consists of four modular soft fingers integrated with layer jamming structure and tendon-driven mechanism. Each finger's rotating shaft of the base uses a torsional spring to decouple the bending deformation and relative rotation. An octopus-mimicking vacuum sucker is installed in the fingertip to generate suction. The effectiveness of the bending deformation and variable stiffness of the design were proved by finite element simulation. Thus, the control model of the finger was built, and the control strategy of multimode grasping of the gripper was proposed. Three control modes were designed to realize the four anthropomorphic grasping modes, including wrap, pinch, hook, and suck. Furthermore, the grasping performance was evaluated to show the abilities. The experiments indicated the superior performance of the proposed gripper and the multimode grasping ability that satisfies various grasping tasks.

Multimode Grasping Soft Gripper Achieved by Layer Jamming Structure and Tendon-Driven Mechanism.

During the compression molding of long fiber reinforced plastics, significant deviations in fiber content have been observed. These can lead to a decrease of mechanical properties, which could ultimately lead to component failure. Experiments in compression molding with long fiber reinforced plastics in a complex structure show significant fiber jamming and decrease in fiber content in ribbed sections. The occurring Fiber Matrix Separation (FMS) during processing is assumed to be caused by intensive fiber interaction. The governing mechanisms on FMS are evaluated and a mechanistic model is applied to simulate and predict the effect of FMS during compression molding.

Experimental and Numerical Analysis of Fiber Matrix Separation during Compression Molding of Long Fiber Reinforced Thermoplastics

Compression molding of long fiber reinforced composites offers specific advantages in automotive applications due to the high strength to weight ratio, the comparably low tooling costs and short cycle times. However, the manufacturing process of long fiber composite parts presents a range of challenges. The phenomenon of fiber matrix separation (FMS) is causing severe deviations in fiber content, especially in complex ribbed structures. Currently, there is no commercial software that is capable to accurately predict FMS. This work uses a particle level mechanistic model to study FMS in a rib filling application. The direct fiber simulation (DFS) is uniquely suited to this application due to its ability to model individual fibers and their bending, as well as the interaction amongst fibers that leads to agglomeration. The effects of mold geometry, fiber length, viscosity, and initial fiber orientation are studied. It is shown that fiber length and initial fiber orientation have the most pronounced effects on fiber volume percentage in the ribs, with viscosity and part geometry playing a smaller role.

/pdf/simulative-prediction-of-fiber-matrix-separation-in-rib-27udd0bfs2.pdf

Simulative Prediction of Fiber-Matrix Separation in Rib Filling During Compression Molding Using a Direct Fiber Simulation

The space industry has seen promising advancements in additive manufacturing (AM) technologies, including the production of rocket engines and spacecraft components. Nevertheless, AM adoption decisions are still complex due to the many considerations, uncertainties, and stakeholders involved. This paper proposes and demonstrates a decision support framework – including a utility theory-based decision engine that was developed in-house – to support users in evaluating AM-use options. The key decision attributes (i.e., performance, cost, and time) of a space satellite bracket assembly were identified through a requirements definition process. Utility functions representing different decision-maker risk preferences were defined based on relevant spacecraft operating conditions. Attribute data for machine-material pair options were also quantified using data sheets, AM cost, and build-time models. The utility functions, attribute values, and attribute weights were input to the decision engine software for a machine-material pair recommendation. A sensitivity analysis was conducted by varying the utility functions, attribute weights, build volume, and applying “hard constraints”. The results demonstrated the versatility and applicability of the decision framework and engine in tackling AM machine-material pair selection problems, including for the satellite design and manufacturing use case.

A Decision Support Framework for Additive Manufacturing of Space Satellite Systems

In this paper, we formulate an optimal ordering policy as a stochastic control problem where each firm decides the amount of input goods to order from their upstream suppliers based on the current inventory level of its output good. For this purpose, we provide a closed-form solution for the optimal request of the raw materials for given a fixed production policy. We implement the proposed policy on a 15-firm acyclic network based on a real product supply chain. We first simulate ideal demand situations, and then we implement demand-side shocks (i.e., demand levels outside of those considered in the policy formulation) and supply-side shocks (i.e., halts in production for some suppliers) to evaluate the robustness of the proposed policies.

Ian Walter

Papers

Experimental and Numerical Analysis of Fiber Matrix Separation during Compression Molding of Long Fiber Reinforced Thermoplastics

Simulative Prediction of Fiber-Matrix Separation in Rib Filling During Compression Molding Using a Direct Fiber Simulation

A Decision Support Framework for Additive Manufacturing of Space Satellite Systems

Optimal Ordering Policies for Multi-Echelon Supply Networks