Design Of Virtual Experiment Research Articles

XU-RSM: Diffuse response surface model for reliability-based design optimization

We focus on a new response surface methodology (XU-RSM) adapted to RBDO, based on Diffuse Approximation. This method uses simultaneously the points in the space of probabilistic variables (U-space) and the points in the space of physical variables (X-space). The two grids form a "virtual design of experiments" and are progressively explored in order to minimize the number of the "exact" function evaluations. A variant of the first order reliability method FORM is chosen to calculate the safety index. A case study is investigated for the numerical control (NC) machining operations of ultrahigh strength steel. We show how the proposed method can decrease the amount of function calculations and reduce the computing time.

Lead‐free solder joint reliability estimation of flip chip package using FEM‐based sensitivity analysis

PurposeIntegration of Cu/low‐k interconnects into the next‐generation integrated circuit chips, particularly for devices below the 90 nm technology node, has proved necessary to meet the urgent requirements of reducing RC time delay and low power consumption. Accordingly, establishment of feasible and robust packaging technology solutions in relation to the structural design, as well as material selection of the packaging components, has become increasingly important. Moreover, the nature of low‐k materials and the use of lead‐free solder greatly increases the complications in terms of ensuring enhanced packaging level reliability. The foregoing urgent issue needs to be quickly resolved while developing various advanced packages. This paper aims to focus on the issues.Design/methodology/approachThe prediction model, especially for the fatigue life of lead‐free solder joints, combined with virtual design of experiment with factorial analysis was used to obtain the sensitivity information of selecting geometry/material parameters in the proposed low‐k flip‐chip (FC) package. Moreover, a three‐dimensional non‐linear strip finite element model associated with the two levels of specified boundary condition of global‐local technique was adopted to shorten the time of numerical calculation, as well as to give a highly accurate solution.FindingsThe results of thermal cycling in experimental testing show good agreement with the simulated analysis. In addition, the sensitivity of analysis indicates that the type of underfill material has a significant effect on the lead‐free solder joint reliability.Originality/valueA suitable combination of concerned designed factors is suggested in this research to enhance the reliability of low‐k FC packaging with Pb‐free solder joints.

Virtual Experiment Design for the Transient Hot-Bridge Sensor

The development of stable, highly sensitive sensors for measuring the thermal transport properties of a wide range of materials requires a detailed evaluation of all the effects having an impact on the measurement result. The virtual experiment design (VED), which is based on the simulation of potential experiments, offers a powerful tool to design and optimize new measurement configurations such as, for example, the transient hot-bridge sensor. The main effects of the applied simplified data analysis on the measurement uncertainty, i.e., the strip configuration, the neglected insulating foil, the linearized analysis and the shortened measurement time, are analyzed. All factors are found to be tolerable with respect to the total measurement uncertainty.

Investigation of work hardening of flat-rolled helical-involute gears through grain-flow analysis, FE-modeling, and strain signature

Net-shape forming of gears is under investigation by a number of researchers. The proposed new methods would reduce waste through chip elimination. Flat rolling of external-precision involute-helical gears is discussed in the current paper. This method is expected to have the additional advantage of producing stronger gears. The work-hardening effect on the critical regions of gear is investigated through the use of three-dimensional DEFORM finite element models (FEM). The simulation models were calibrated against designed experiments with a specific gear design. Also, current production gears were compared with gears manufactured through the new process. Samples were destructively tested to obtain metallurgical data. Hardness maps and grain-flow photographs were produced for the two groups of gears. Validation of FE modeling has opened the way for optimization of gear-rolling process through virtual design of experiments (DEX). It would be possible to vary FEM inputs such as blank material, gear specification, or die geometry and study the predicted impact on gear tooth strength.

Linking design process to customer satisfaction through virtual design of experiments

This work seeks to better understand how design processes affect design outcomes. Design process data were collected from journals kept as a part of mechanical engineering capstone design projects at Montana State University. Student processes were characterized by time coding journal entries using a 3 × 4 matrix of process variables. The data were modeled using a principal components artificial neural network, and the model used in a virtual designed experiment to obtain estimates for design process factors that significantly affect client satisfaction. Results indicate that greater client satisfaction is achieved through: greater problem definition (PD) activity and idea generation at conceptual design levels, and PD and engineering analysis activities at the system design level. Whereas, design activity at the detailed level associates with lower client satisfaction. These results support some aspects of existing models of “good” design process, and suggest adaptations of the models for novice designers.

Applying artificial neural networks and virtual experimental design to quality improvement of two industrial processes

Artificial neural networks (ANNs) are powerful tools to model the non-linear cause-and-effect relationships inherent in complex production processes, usually for process and quality control. This paper substantiates the concurrent application of ANNs and virtual design of experiments to quality improvement. For a chemical manufacturing process and a printed circuit board machining process, respectively, empirical ANN models were constructed and validated using historical data, which were further used to predict the outputs of well-designed process settings. The predicted results were then used to perform statistical tests and identify the significant factors and interactions that affect the quality-related output variables. For the production of a resin intermediate, it was revealed that the combination of low water concentration and an appropriate ratio of raw materials increases both the yield and product quality in a synergistic manner. For the machining of printed circuit board slot by a milling cutter, it was concluded that a high forwarding speed was preferred for the better quality of the milled surface. For both cases, the preliminary conclusions lead to the directions of further real-world experiments for quality improvement. The data mining approach integrating ANNs and virtual design of experiments showed great potential to achieve a better understanding of process behaviour and to improve the process quality efficiently.

Flip-Chip BGA Design to Avert Die Cracking

Fracture mechanics is applied to flip-chip BGA design to avert die cracking from its backside. Fracture mechanics is integrated with the finite element analysis (FEA) and design of virtual experiments (virtual DOE) to analyze the effects of location and length of a die crack, and the effects of some key material properties and package dimensions on die cracking of flip-chip BGA. The stress intensity factor (SIF) and the strain energy release rate (ERR) are taken as the design indices. The FEA is used to calculate the fracture parameters, and the virtual DOE is employed to determine contributions of each design parameter to die cracking and their acceptable design windows. The investigation consists of two parts. The first is relations of length and location of a die crack with the fracture parameters. The relations are established through sweeping along crack length for a crack located at the center of the die backside, and along the die backside surface. The critical crack length is determined for a specific design. The second is the virtual DOE based on fracture mechanics. Several key material properties and package dimensions are used as the design inputs. The main effects and interactions of these design parameters to die cracking are calculated. Based on it, some generic design guidelines are made. It is concluded that substrate and die thicknesses are the two most significant factors to die cracking of flip-chip BGA. Increasing substrate thickness and reducing die thickness are the most effective measures to design a package with high resistance to die cracking.