A. Sherif El-Gizawy

An approach for development of damage-free drilling of carbon fiber reinforced thermosets

A new comprehensive approach to select cutting parameters for damage-free drilling in carbon fiber reinforced epoxy composite material is presented. The approach is based on a combination of Taguchis experimental analysis technique and a multi-objective optimization criterion. The optimization objective includes the contributing effects of the drilling performance measures: delamination, damage width, surface roughness, and drilling thrust force. A hybrid process model based on a database of experimental results together with numerical methods for data interpolation are used to relate drilling parameters to the drilling performance measures. Case studies are presented to demonstrate the application of this method in the determination of optimum drilling conditions for damage-free drilling in BMS 8-256 composite laminate. A process map based on the results is presented as a tool for drilling process design and optimization for the investigated tool/material combination.

Modeling of Process Induced Residual Stresses in Resin Transfer Molded Composites with Woven Fiber Mats

Cure-dependent mechanical properties are used in finite element-based models to determine process-induced residual stresses and deformations in composite parts. The complete cure cycle in resin transfer molding process is modeled in a series of sub steps. The composite mechanical properties are specified in each step according to the composite cure history. The cool down stage after the composite cure is also analyzed. The effects of resin shrinkage on the development of residual stresses and deformations are investigated as well. Case studies involving composite parts with woven carbon and fiberglass mats and epoxy resin are presented to demonstrate the effectiveness of the developed models. Residual stresses were found to be compressive throughout the investigated composite parts. Resin shrinkage resulted in a decrease in residual stresses. The present study establishes the bases for quantifying the combined effects of thermomechanical and thermochemical responses of the material on the development of process induced residual stresses and deformations in resin transfer molded composites.

Development of process maps for superplastic forming of Weldalite™ 049

The activation energy under superplastic forming (SPF) conditions for the Al–Cu–Li alloy Weldalite™ 049 (W049) had been reported in a few publications with insufficient information to establish the material constitutive equation. In the present work, the constitutive equation of the alloy was developed through superplastic uniaxial testing with the main axis of the specimen parallel, perpendicular, and at 45° to the rolling direction. The results of the investigation showed that the activation energy was not a function of orientation with respect to the rolling direction, but a function of the strain rate. The data generated from the tests was used to generate process maps for W049 which correlate the processing conditions to the available formability and the developed microstructure. The formability map shows that the alloy exhibits its maximum formability in the region bounded by a temperature of 485°C and a strain rate of 5×10−4 s−1. The formability drops to much lower values, at slower strain rates.

Computer-aided monitoring system for flexible assembly operations

Abstract A computer-aided monitoring strategy for flexible assembly operations is presented. This strategy uses knowledge-based expert systems for error detection and diagnosis. The hierarchy of the system is embedded in a blackboard control structure to facilitate parallel, asynchronous communication and to enhance the flexibility of the system. The developed detection and diagnosis modules of the system were validated experimentally on a prototype robotic assembly work cell. The investigation demonstrated the uniqueness of the new system through the elimination of error propagation and the need for event backtracking if an environment change occurs.

Numerical characterization of mold injection in resin transfer molding process

A control volume technique based on the finite difference method is used to characterize the flow behavior in resin transfer molding (RTM) of composite structures. Resin flow through fiber mats is modeled as a two-phase flow through porous media. The transient time terms are considered, and the concept of the fraction volume of fluid (VOF) is applied in order to accurately describe the behavior of the free boundary at the interface between the two fluids involved in the process, the resin and the air. Flow experiments in a transparent mold were performed to verify the numerical model. Experimental results on flow behavior of EPON 826 epoxy resin into irregular mold cavity with fiberglass mats agree well with the present numerical simulation. Several parametric studies using the developed model are conducted to investigate the effects of injection pressure and mold design on resin flow pattern, mold filling time, and pressure distribution inside the mold.

Cure dependent lamina stiffness matrices of Resin Transfer Molded composite parts with woven fiber mats

Models are presented for determination of cure dependent stiffness matrices for composites manufactured with woven fiber mats. Five-harness carbon and eight-harness glass mats with EPON 826 resin composites are considered. The models presented here take into account important material/process parameters with emphasis on: (1) the effects of cure-dependent resin mechanical properties, (2) fiber undulation due to the weave of the fiber fill and warp bundles, and (3) resin interaction with the fiber bundles at a microscopic scale. In the present study these effects are considered in the determination of mechanical properties of a Resin Transfer Molded (RTM) part

Optimal Neural Network Model for Characterization of Process‐Induced Damage in Drilling Carbon Fiber Reinforced Epoxy Composites

In this paper, a method for robust design of a neural network (NN) model for prediction of delamination (Da), damage width (Dw), and hole surface roughness (Ra) during drilling in carbon fiber reinforced epoxy (BMS 8‐256) is presented. This method is based on a parametric analysis of neural network models using a design of experiments approach. The effects of number of neurons (N), hidden layers (L), activation function (AF), and learning algorithm (LA) on the mean square error (MSE) of model prediction are quantified. Using the aforementioned method, a robust NN model was developed that predicted process‐induced damage with high accuracy.

A multiple objective based strategy for process design of machining operations

In this paper a general strategy for process design using nonlinear goal programming is developed and applied to machining operations. The developed strategy allows different priority levels for each objective. The resulting design and optimization problem can be solved using unconstrained nonlinear techniques with no need for linearization. Evaluation of the developed strategy was conducted using single pass machining operations. The study proved the effectiveness of the strategy in selecting the optimum process conditions under different production priorities. The developed strategy is also compared with a strategy based on a fuzzy nonlinear programming model. The fuzzy-based solution can be considered as the fuzzy alternative or the approximation of the multiple objective solution.

Computer-Aided Engineering Approach for Parametric Investigation of Locked Plating Systems Design

The present paper presents an integrated computer-aided engineering (CAE) approach combining digital imaging, solid modeling, robust design methodology, and finite element analysis in order to conduct a parametric investigation of the design of locked plating systems. The present study allows for understanding the contributions of different design parameters on the biomechanics and reliability of these systems. Furthermore, the present approach will lead to exploration of optimum design parameters that will result in robust system performance. Three-dimensional surface models of cortical and cancellous femoral bone were derived via digital computed tomography (CT) image processing techniques and a medical imaging analysis program. A nine orthogonal array matrix simulation (L9) was conducted using finite element methods to study the effects of the various design parameters on plate performance. The introduced technique was demonstrated and experimentally verified on a case study using a Smith & Nephew PERI- LOC distal femur locking plate and a Synthes Less Invasive Stabilization System (LISS).

Incorporating Neural Network Material Models Within Finite Element Analysis for Rheological Behavior Prediction

The accuracy of a finite element model for design and analysis of a metal forging operation is limited by the incorporated material model’s ability to predict deformation behavior over a wide range of operating conditions. Current rheological models prove deficient in several respects due to the difficulty in establishing complicated relations between many parameters. More recently, artificial neural networks (ANN) have been suggested as an effective means to overcome these difficulties. To this end, a robust ANN with the ability to determine flow stresses based on strain, strain rate, and temperature is developed and linked with finite element code. Comparisons of this novel method with conventional means are carried out to demonstrate the advantages of this approach.Copyright