Tool sequence optimization based on three logical modes of robot control via CPLEX optimization

Cluster tools have advantages of shorter cycle times, faster process development, and better yield for less contamination. The sequence of dual-arm cluster tools is a complex logistics process during the semiconductor production. Efficient use of cluster tools is naturally very significant to competitive fab operations. Generating an optimized sequence in a computationally efficient manner and assessing the quality of the requirements to improve the fab production are the key factors for semiconductor manufacturing productivity. The Petri net modeling is introduced to minimize the makespan of the process for the three different logical modes and select a better mode after comparing the makespan among the three logical modes. The tool sequence optimization problem is formulated as optimization firing transition sequences based on the Petri net and then the formulation is converted to be linearly solved by the branch-and-cut method in the standard commercial solver CPLEX. Special methods for the linear conversion are highlighted. Due to the limited calculation time requirement for the real production and the large scale of the problem, special methods for the efficiency tuning are applied according to the characteristics of the problem. Numerical testing is supported by one of the most advanced semiconductor enterprises and the computational results show significant improvement compared with the traditional manual sequence results.     

Three-dimensional numerical simulation of splat formation on substrates in plasma spraying

Plasma sprayed coatings are built up by the accumulation of splats formed by the impacting, spreading and solidifying of molten droplets on the substrate. A three-dimensional computational model including heat transfer and solidification is established to simulate the formation process of a single splat using the computational fluid dynamics (CFD) software, FLUENT. The fluid flow and energy equations are discretized and solved according to typical finite volume method on an unstructured grid. A volume of fluid (VOF) tracking algorithm is used to track the droplet flow with free surface. In order to understand the splat formation mechanism, the process of splat formation caused by impacting and spreading of a molten nickel droplet on a polished mild steel surface is simulated. On this basis, the simulations of impact of a molten droplet on substrate with different conditions including the surface morphology, thermal conductivity, initial temperature of the substrate and the thermal contact resistance are presented. The results clearly show the effect of those parameters on the shape of the final splat and splash behaviors.     

Implementation of dynamic matrix control on field programmable gate array

High performance computer is often required by model predictive control (MPC) systems due to the heavy online computation burden. To extend MPC to more application cases with low-cost computation facilities, the implementation of MPC controller on field programmable gate array (FPGA) system is studied. For the dynamic matrix control (DMC) algorithm, the main design idea and the implemental strategy of DMC controller are introduced based on a FPGA’s embedded system. The performance tests show that both the computation efficiency and the accuracy of the proposed controller can be satisfied due to the parallel computing capability of FPGA.     

Study on bending conditions of plate in coil box

In a coil box between the roughing and finishing stands on a hot strip mill, a problem has been encountered that the entry region of the plate touches the bending rolls and deforms. As a result, the defective coil occurs. The condition of plate bending, which forms a new deformation feature in coiling, is analyzed. In this paper, the authors focus on the research of the effects of coiling parameters, such as the thickness of plate, roll speed and feeding speed of plate in coil box, and on specific plate bending. A finite element method is developed to simulate this coiling process. Based on numerical simulation, the effects of the coiling parameters on the mechanics and deformation of the bending plate are obtained. Numerical simulation tests have verified the validity of the developed model.     

Chaff cloud jamming suppression based on wavelet transform

Radar target signals and chaff cloud jamming signals have different characters by the wavelet transform. The wavelet coefficients of radar target signals are highly correlated with its near-and-near-scale wavelet coefficients, however the correlativity between the wavelet coefficients of chaff cloud jamming signals and its near-and-near scale wavelet coefficients is less significant. Based on the binary-base discrete wavelet transform and the correlation algorithm, the method of target entropy to estimate standard variance of the jamming signals and each scale is proposed to ensure reasonable threshold, to suppress chaff cloud signals and finally to reconstruct mixed signals by the improved spatially selective noise filtration (ISSNF) method. The extensive simulation results show that the proposed method can availably suppress chaff cloud jamming and decontaminate target echo.     

Bit stream oriented enumeration tree pruning algorithm

Packet analysis is very important in our digital life. But what protocol analyzers can do is limited because they can only process data in determined format. This paper puts forward a solution to decode raw data in an unknown format. It is certain that data can be cut into packets because there are usually characteristic bit sequences in packet headers. The key to solve the problem is how to find out those characteristic sequences. We present an efficient way of bit sequence enumeration. Both Aho-Corasick (AC) algorithm and data mining method are used to reduce the cost of the process.     

Optimal linear phase finite impulse response band pass filter design using craziness based particle swarm optimization algorithm

An efficient method is proposed for the design of finite impulse response (FIR) filter with arbitrary pass band edge, stop band edge frequencies and transition width. The proposed FIR band stop filter is designed using craziness based particle swarm optimization (CRPSO) approach. Given the filter specifications to be realized, the CRPSO algorithm generates a set of optimal filter coefficients and tries to meet the ideal frequency response characteristics. In this paper, for the given problem, the realizations of the optimal FIR band pass filters of different orders have been performed. The simulation results have been compared with those obtained by the well accepted evolutionary algorithms, such as Parks and McClellan algorithm (PMA), genetic algorithm (GA) and classical particle swarm optimization (PSO). Several numerical design examples justify that the proposed optimal filter design approach using CRPSO outperforms PMA and PSO, not only in the accuracy of the designed filter but also in the convergence speed and solution quality.     

Reputation-based collaborative spectrum sensing scheme in cognitive radio networks

Collaborative spectrum sensing is proposed to improve the detection performance in cognitive radio (CR) networks. However, most of the current collaborative sensing schemes are vulnerable to the interference of the malicious secondary users (SUs). In this paper we propose a reputation-based collaborative spectrum sensing scheme to improve the security of cooperative sensing by mitigating the impacts of misbehaviors. The fusion center calculates the reputation rating of each SU according to their history reports to weight their sensing results in the proposed scheme. We analyze and evaluate the performance of the proposed scheme and its advantages over previous schemes in expansibility and integrity. Simulation results show that the proposed scheme can minimize the harmful influence from malicious SUs.     

Fault diagnosis for singular stochastic systems

This paper studies the fault diagnosis of singular stochastic systems. The probability distribution of output is measured by probability density functions (PDFs), which are modeled by a square root B-spline expansion. An adaptive nonlinear observer is proposed to estimate the size of the fault occurring in systems. Furthermore, the linear matrix inequality (LMI) approach is applied to establish sufficient conditions for the existence of the observer. Finally, the simulation results are given to indicate the method for diagnosing the fault.     

Automatic product image classification with multiple support vector machine classifiers

For the task of visual-based automatic product image classification for e-commerce, this paper constructs a set of support vector machine (SVM) classifiers with different model representations. Each base SVM classifier is trained with either different types of features or different spatial levels. The probability outputs of these SVM classifiers are concatenated into feature vectors for training another SVM classifier with a Gaussian radial basis function (RBF) kernel. This scheme achieves state-of-the-art average accuracy of 86.9% for product image classification on the public product dataset PI 100.