Optimal Parallel Machine Allocation Problem in IC Packaging Using IC-PSO: An Empirical Study

2017 ◽  
Vol 34 (06) ◽  
pp. 1750034
Author(s):  
Robert Cuckler ◽  
Kuo-Hao Chang ◽  
Liam Y. Hsieh
Keyword(s):  
Empirical Study ◽  
Stochastic Simulation ◽  
Integrated Circuit ◽  
Flow Shop ◽  
Numerical Study ◽  
Real Data ◽  
Solution Quality ◽  
Ic Packaging ◽  
Metamodeling Technique ◽  
Machine Allocation

We model and apply a stochastic-simulation-based methodology to optimize the machine allocation of a flexible flow shop (FFS) dedicated to integrated circuit (IC) packaging. This contrasts with most previous research on non-deterministic FFS problems wherein stochastic simulation is mostly used to estimate throughput, cycle time, delay cost, or some other measure(s) in order to compare the performances of already-existing heuristic-based algorithms. The methodology applied in this research, called progressive simulation metamodeling for IC Packaging (IC-PSO), while rooted in the traditional metamodeling technique known as Response Surface Methodology (RSM), contrasts with RSM in that it is equipped with well-designed mechanisms to ensure an ever-increasing solution quality in an attempt to achieve the desirable optimality. The computational efficiency that IC-PSO affords IC packaging companies is demonstrated via a numerical study. Meanwhile, an empirical study based on real data was conducted to validate the viability of the proposed methodology in real settings.

Acoustic microscopy techniques for the inspection of integrated circuit devices and packages

1992 ◽  
Vol 50 (2) ◽  
pp. 966-967
Author(s):  
Thomas M. Moore
Keyword(s):  
Integrated Circuit ◽  
Acoustic Microscopy ◽  
Hybrid Technique ◽  
Frequency Scanning ◽  
Ic Packaging ◽  
Ic Package ◽  
Microscopy Techniques ◽  
Ic Package Inspection ◽  
Pulse Echo ◽  
Scanning Acoustic Microscope

In the last decade, a variety of characterization techniques based on acoustic phenomena have come into widespread use. Characteristics of matter waves such as their ability to penetrate optically opaque solids and produce image contrast based on acoustic impedance differences have made these techniques attractive to semiconductor and integrated circuit (IC) packaging researchers.These techniques can be divided into two groups. The first group includes techniques primarily applied to IC package inspection which take advantage of the ability of ultrasound to penetrate deeply and nondestructively through optically opaque solids. C-mode Acoustic Microscopy (C-AM) is a recently developed hybrid technique which combines the narrow-band pulse-echo piezotransducers of conventional C-scan recording with the precision scanning and sophisticated signal analysis capabilities normally associated with the high frequency Scanning Acoustic Microscope (SAM). A single piezotransducer is scanned over the sample and both transmits acoustic pulses into the sample and receives acoustic echo signals from the sample.

scholarly journals Robust estimation for multivariate wrapped models

METRON ◽  
2021 ◽  
Author(s):  
Giovanni Saraceno ◽  
Claudio Agostinelli ◽  
Luca Greco
Keyword(s):  
Robust Estimation ◽  
Numerical Study ◽  
Real Data ◽  
Likelihood Method ◽  
Weighted Likelihood ◽  
Finite Sample ◽  
Pearson Residuals ◽  
Data Points ◽  
Wrapped Distributions ◽  
Standard Techniques

AbstractA weighted likelihood technique for robust estimation of multivariate Wrapped distributions of data points scattered on a $$p-$$ p - dimensional torus is proposed. The occurrence of outliers in the sample at hand can badly compromise inference for standard techniques such as maximum likelihood method. Therefore, there is the need to handle such model inadequacies in the fitting process by a robust technique and an effective downweighting of observations not following the assumed model. Furthermore, the employ of a robust method could help in situations of hidden and unexpected substructures in the data. Here, it is suggested to build a set of data-dependent weights based on the Pearson residuals and solve the corresponding weighted likelihood estimating equations. In particular, robust estimation is carried out by using a Classification EM algorithm whose M-step is enhanced by the computation of weights based on current parameters’ values. The finite sample behavior of the proposed method has been investigated by a Monte Carlo numerical study and real data examples.

An empirical study-based state space model for multilayer overlay errors in the step-scan lithography process

RSC Advances ◽  
2015 ◽  
Vol 5 (126) ◽  
pp. 103901-103906 ◽  
Author(s):  
Fuyun He ◽  
Zhisheng Zhang
Keyword(s):  
Empirical Study ◽  
State Space ◽  
Integrated Circuit ◽  
Manufacturing Process ◽  
Semiconductor Manufacturing ◽  
State Space Model ◽  
Key Factors ◽  
Space Model ◽  
Lithography Process ◽  
Multistage Manufacturing

In semiconductor manufacturing, the multilayer overlay lithography process is a typical multistage manufacturing process; one of the key factors that restrict the reliability and yield of integrated circuit chips is overlay error between the layers.

scholarly journals Weighted Mask R-CNN for Improving Adjacent Boundary Segmentation

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
SungMin Suh ◽  
Yongeun Park ◽  
KyoungMin Ko ◽  
SeongMin Yang ◽  
Jaehyeong Ahn ◽  
...  
Keyword(s):  
Cell Membrane ◽  
Edge Detection ◽  
Numerical Study ◽  
Simulated Data ◽  
Real Data ◽  
Environmental Research ◽  
Single Image ◽  
Heterogeneous Objects ◽  
In Virtue Of ◽  
Instance Segmentation

In the recent era of AI, instance segmentation has significantly advanced boundary and object detection especially in diverse fields (e.g., biological and environmental research). Despite its progress, edge detection amid adjacent objects (e.g., organism cells) still remains intractable. This is because homogeneous and heterogeneous objects are prone to being mingled in a single image. To cope with this challenge, we propose the weighted Mask R-CNN designed to effectively separate overlapped objects in virtue of extra weights to adjacent boundaries. For numerical study, a range of experiments are performed with applications to simulated data and real data (e.g., Microcystis, one of the most common algae genera and cell membrane images). It is noticeable that the weighted Mask R-CNN outperforms the standard Mask R-CNN, given that the analytic experiments show on average 92.5% of precision and 96.4% of recall in algae data and 94.5% of precision and 98.6% of recall in cell membrane data. Consequently, we found that a majority of sample boundaries in real and simulated data are precisely segmented in the midst of object mixtures.

Iterated Local Search and Other Algorithms for Buffered Two-Machine Permutation Flow Shops with Constant Processing Times on One Machine

2020 ◽  
pp. 1-25
Author(s):  
Hoang Thanh Le ◽  
Philine Geser ◽  
Martin Middendorf
Keyword(s):  
Local Search ◽  
Flow Shop ◽  
Iterated Local Search ◽  
Flow Shop Scheduling ◽  
Np Hard ◽  
Ant Colony Optimization Algorithm ◽  
Solution Quality ◽  
Processing Times ◽  
One Machine ◽  
Special Case

The two-machine permutation flow shop scheduling problem with buffer is studied for the special case that all processing times on one of the two machines are equal to a constant c. This case is interesting because it occurs in various applications, e.g., when one machine is a packing machine or when materials have to be transported. Different types of buffers and buffer usage are considered. It is shown that all considered buffer flow shop problems remain NP-hard for the makespan criterion even with the restriction to equal processing times on one machine. However, the special case where the constant c is larger or smaller than all processing times on the other machine is shown to be polynomially solvable by presenting an algorithm (2BF-OPT) that calculates optimal schedules in [Formula: see text] steps. Two heuristics for solving the NP-hard flow shop problems are proposed: i) a modification of the commonly used NEH heuristic (mNEH) and ii) an Iterated Local Search heuristic (2BF-ILS) that uses the mNEH heuristic for computing its initial solution. It is shown experimentally that the proposed 2BF-ILS heuristic obtains better results than two state-of-the-art algorithms for buffered flow shop problems from the literature and an Ant Colony Optimization algorithm. In addition, it is shown experimentally that 2BF-ILS obtains the same solution quality as the standard NEH heuristic, however, with a smaller number of function evaluations.

scholarly journals Confidence Interval Based Fuzzy Evaluation Model for an Integrated-Circuit Packaging Molding Process

2019 ◽  
Vol 9 (13) ◽  
pp. 2623 ◽  
Author(s):  
Chun-Ming Yang ◽  
Kuo-Ping Lin ◽  
Kuen-Suan Chen
Keyword(s):  
Confidence Interval ◽  
Integrated Circuit ◽  
Evaluation Model ◽  
Measurement Data ◽  
Electronics Industry ◽  
Green Economy ◽  
Fuzzy Evaluation ◽  
Molding Process ◽  
Ic Packaging ◽  
Fuzzy Evaluation Model

The electronics industry in Taiwan has achieved a complete information and communication technology chain with a firm position in the global electronics industry. The integrated-circuit (IC) packaging industry chain adopts a professional division of labor model, and each process (including wafer dicing, die bonding, wire bonding, molding, and other subsequent processes) must have enhanced process capabilities to ensure the quality of the final product. Increasing quality can also lower the chances of waste and rework, lengthen product lifespan, and reduce maintenance, which means fewer resources invested, less pollution and damage to the environment, and smaller social losses. This contributes to the creation of a green process. This paper developed a complete quality evaluation model for the IC packaging molding process from the perspective of a green economy. The Six Sigma quality index (SSQI), which can fully reflect process yield and quality levels, is selected as a primary evaluation tool in this study. Since this index contains unknown parameters, a confidence interval based fuzzy evaluation model is proposed to increase estimation accuracy and overcome the issue of uncertainties in measurement data. Finally, a numerical example is given to illustrate the applicability and effectiveness of the proposed method.

scholarly journals Numerical Study of the 10 January 1998 Lake-Effect Bands Observed during Lake-ICE

2005 ◽  
Vol 62 (9) ◽  
pp. 3232-3249 ◽  
Author(s):  
Gregory J. Tripoli
Keyword(s):  
Lake Michigan ◽  
Numerical Study ◽  
Real Data ◽  
Streamwise Vorticity ◽  
Lake Ice ◽  
Fine Grid ◽  
Near Surface ◽  
Wave Trapping ◽  
Initial Location ◽  
Grid Nesting

Abstract This paper presents the results of a series of idealized cloud resolving simulations of the evolution of moist roll convection observed as part of the Lake-Induced Convection Experiment (Lake-ICE) that took place during the 1997/98 winter over central Lake Michigan. Satellite and radar observations of the roll convection depict striking linear rolls stretching from 10 km off the western shore of the lake, across to the eastern shore, and then continuing across Michigan. The spacing of the primary rolls was observed to be 6 km, giving a ratio of spacing to depth of about 5:1, which is consistent with theory. In addition, a longer wavelength (13 km) of stationary banding was observed parallel to the shoreline. In an earlier study of this case, multiply nested simulations of the convective rolls based on real data variable initialization were successful in producing banded structures with similar spacing and location over the water to those observed using fine grid resolution of about 500 m. Unfortunately, the initial locations of simulated bands were organized primarily by numerical effects of grid interpolation. This suggested that the spacing of the bands was robust, but that their initial location was highly sensitive to subtle systematic forcings. In this paper, a set of idealized model experiments, designed to isolate the role that physically realistic local forcing plays in the organization of the rolls, was performed. Because externally generated upstream turbulence was suppressed in these tests so as not to bias the result, the generation of rolls was delayed until 20–30 km downwind of the observed location and the location simulated in the previous grid nesting experiments. It was shown that the subtle effects of the shoreline geometry were sufficient to spawn a near-surface streamwise vorticity that became the primary seed for roll development at the most efficient mode of roll convection. These results suggest that previous structures evolved in the upstream shear-driven land-based mixed layer were likely also important in determining where the nonlocal overturning was first triggered. It is not clear from these results whether the shear-driven structures that evolved over the land also played a significant role in organizing the structural geometry of the lake rolls. Results also suggested that the shore parallel bands were a robust feature of the atmospheric structure resulting from resonant gravity wave trapping in the frontal layer.

Prediction of Wire Sweep During the Encapsulation of IC Packaging With Wire Density Effect

2004 ◽  
Vol 127 (3) ◽  
pp. 335-339 ◽  
Author(s):  
Chien-Chang Pei ◽  
Sheng-Jye Hwang
Keyword(s):  
Integrated Circuit ◽  
Three Dimensional ◽  
Density Effect ◽  
Molding Process ◽  
Molding Compound ◽  
Mesh Model ◽  
Ic Packaging ◽  
Filling Analysis ◽  
The Wire ◽  
Mold Flow

More wires in a package and smaller wire gaps are the trend in the integrated circuit (IC) packaging industry. The effect of wire density is becoming increasingly apparent, especially on the flow pattern of the epoxy molding compound during the molding process and, hence, on the amount of wire sweep. In most mold flow simulations, the wire density effect is ignored. In order to consider the wire density effect on the predicted amount of wire sweep in the analysis, several indirect approaches were used by researchers before. But those approaches were not general enough to be applied to all cases. This paper presents a more direct and convenient approach to consider wire density effect by including wires in the mesh model for three-dimensional (3D) mold-filling analysis. A thin small outline package (TSOP) with 53 wires is used as the demonstration example, and all the wires are modeled in the 3D mesh. By comparison with experimental results, it is shown that this approach can accurately describe the wire density effect. When the wires are included in the mesh model, the predicted wire sweep results are better than those without considering the wire density effect.

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