Parallel Micro Manipulator for Effective Optical Spot Array Alignment

2014 ◽  
Author(s):  
Zheng Yuan Li ◽  
Sae Whan Park ◽  
Yong Seok Inh ◽  
Jong Yoon Choi ◽  
Ja Choon Koo
Keyword(s):  
Genetic Algorithm ◽  
Parallel Manipulator ◽  
Experimental Result ◽  
Kinematic Characteristic ◽  
Maskless Lithography ◽  
Nano Fabrication ◽  
Micro Manipulator ◽  
Spot Array ◽  
Exposure Process ◽  
Lithography Technology

Photolithography is one of the core technologies of micro-nano fabrication. Recently, lithography technology is applied to diverse field of technologies. These technologies include MEMS (micro electro mechanical system) devices, FPD (flat panel display), and semiconductor industry. When it comes to the typical exposure process of lithography technology, photomask costs is occupying large portion of the optical system. So, how to reduce the cost of the mask and employing maskless lithography technology has become an important issue to engineers. Although there being both advantages and disadvantages, maskless lithography is a receiving substantial attention from engineers in the fileds of micro-nano fabrication. With the development of technology, low cost, flexibility, efficiency in the fabrication of device are in high demand in maskless lithography technology. How to generate line/space patterns is gaining considerable attention in terms of maskless lithography exposure process. In order to achieve the accurate alignments of numerous optical heads within a reasonable amount of tack time, installing autonomous position align micro parallel manipulator system in each optical heads required. Applied parallel manipulator that consists of four 2-DOF (degree of freedom) decoupled actuator gives chances to provide 6-DOF independence motion, and has strength in high accuracy. It is thus, this parallel manipulator is suitable for the experiment. This paper covers the follows: First, we reported the DMD (Digital Micro mirror Device)-based makless lithography system to introduce spot array method in maskless digital exposure process. Second, applying a redundant parallel micro manipulator and analyzing kinematic characteristic of the 4-[PP]PS parallel manipulator is described. After that, comparing benefits and drawbacks of 4-[PP]PS parallel and 4-DOF serial manipulator is covered. Third, proposing a suitable error model of the system and applying the genetic algorithm to alignment spot array concerning position correction. Finally, we designed experiment which has vision sensor and align unit to verify positioning algorithm. Simulation and experimental result will be shown with the regard to parallel manipulator can find the optimal solution based on genetic algorithm and carry out the problem of spot array alignment by reducing the position error of the system.

Parallel micro manipulator for optical spot array alignment of maskless lithography

2015 ◽  
Vol 21 (12) ◽  
pp. 2663-2668
Author(s):  
Zheng Yuan Li ◽  
Jong Yoon Choi ◽  
Yong Seok Ihn ◽  
Sang-Hoon Ji ◽  
Ja Choon Koo
Keyword(s):  
Maskless Lithography ◽  
Micro Manipulator ◽  
Spot Array

Optical Head Alignment Method Using Serial Manipulators for Maskless Lithography System

2014 ◽  
Author(s):  
Jong Yoon Choi ◽  
Sae Whan Park ◽  
Yong Seok Inh ◽  
Zheng Yuan Li ◽  
Ja Choon Koo
Keyword(s):  
Optical System ◽  
Cost Efficiency ◽  
Fitness Function ◽  
Alignment Algorithm ◽  
Maskless Lithography ◽  
Test Bed ◽  
Unit Scale ◽  
Lithography System ◽  
Spot Array ◽  
Lithography Technology

As the cost of photo masks for display panel is very high, researchers have been developing maskless lithography using electron beam in this system. However the maskless lithography system has typical drawback in some respects. These issues include productivity, size of the system and cost efficiency. To cope with these problems, take reflectance rate and position of spot array into consideration is required. The lithography technology has been focused on studying both reflectance of light from DMDs (digital micromirror devices) and the position of generated spot array. As the lithography technology has been developed steadily, there exists plenty type of maskless lithography nowadays. DMD-based optical maskless lithography system is gaining substantial attention from researchers and engineers for its outstanding performance concerning cost efficiency and high throughput. Also, accurate alignment of spot array is on requisition under the condition of micro-unit scale. As a result, the maskless lithography system is faced with the problem relevant to accurate alignment. For instance, the actual alignment of spot array has been done by hand although it has a chance to show deleterious effects on productivity. In this paper, an alignment algorithm was suggested for the purpose of satisfying generation of accurate alignment of spot array. The algorithm is based on concerning kinematics of maskless lithography system. Thus, the suggested algorithm enable to reducing the error that has been measured from the spot array. Defining spot array error that is fitness function of genetic algorithm is introduced at first. An alignment algorithm that has correlation with kinematics of the optical system and spot array error will be represented in sequence. After that, designing 4 DOF align unit will be covered in kinematics analysis chapter. Finally, designing test bed of optical system using vision sensor and align unit is considered in order to validate the suggested alignment algorithm with experiment.

A Genetic Algorithm for Minimizing Relocations at Container Yard in Container Terminal

2014 ◽  
Vol 931-932 ◽  
pp. 1683-1688
Author(s):  
Phatchara Sriphrabu ◽  
Kanchana Sethanan ◽  
Somnuk Theerakulpisut
Keyword(s):  
Genetic Algorithm ◽  
Current Practice ◽  
Container Terminal ◽  
Experimental Result ◽  
Container Ship ◽  
Storage Assignment ◽  
Storage Location ◽  
Location Assignment

This paper focuses on storage location assignment and exported container relocation in container yard of container terminal with the objective of minimizing the number of container lifting. On the lifting steps, the truck with yard crane should be chosen in order to deliver a container from container yard to container ship, and this action can reduce container ship's docking time and increase effectiveness in container terminal service. In this paper, a genetic algorithm (GA) in container storage assignment and a heuristic for the container relocation determination are adopted. Also, the current practice including first-in-first-stored (FIFS) and simple relocation (SR) is used to compare the effectiveness of the GA and the proposed heuristic (RH). The experimental result presented that the proposed method is able to construct the effective solutions of storage location assignment of exported containers, and it reduces the number of relocations of exported container effectively.

scholarly journals Energy-Efficient Gabor Kernels in Neural Networks with Genetic Algorithm Training Method

Electronics ◽  
2019 ◽  
Vol 8 (1) ◽  
pp. 105 ◽  
Author(s):  
Fanjie Meng ◽  
Xinqing Wang ◽  
Faming Shao ◽  
Dong Wang ◽  
Xia Hua
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Neural Networks ◽  
Energy Efficient ◽  
Experimental Result ◽  
Training Method ◽  
Traffic Sign Recognition ◽  
Traffic Sign ◽  
Sign Recognition ◽  
Deep Model

Deep-learning convolutional neural networks (CNNs) have proven to be successful in various cognitive applications with a multilayer structure. The high computational energy and time requirements hinder the practical application of CNNs; hence, the realization of a highly energy-efficient and fast-learning neural network has aroused interest. In this work, we address the computing-resource-saving problem by developing a deep model, termed the Gabor convolutional neural network (Gabor CNN), which incorporates highly expression-efficient Gabor kernels into CNNs. In order to effectively imitate the structural characteristics of traditional weight kernels, we improve upon the traditional Gabor filters, having stronger frequency and orientation representations. In addition, we propose a procedure to train Gabor CNNs, termed the fast training method (FTM). In FTM, we design a new training method based on the multipopulation genetic algorithm (MPGA) and evaluation structure to optimize improved Gabor kernels, but train the rest of the Gabor CNN parameters with back-propagation. The training of improved Gabor kernels with MPGA is much more energy-efficient with less samples and iterations. Simple tasks, like character recognition on the Mixed National Institute of Standards and Technology database (MNIST), traffic sign recognition on the German Traffic Sign Recognition Benchmark (GTSRB), and face detection on the Olivetti Research Laboratory database (ORL), are implemented using LeNet architecture. The experimental result of the Gabor CNN and MPGA training method shows a 17–19% reduction in computational energy and time and an 18–21% reduction in storage requirements with a less than 1% accuracy decrease. We eliminated a significant fraction of the computation-hungry components in the training process by incorporating highly expression-efficient Gabor kernels into CNNs.

Optimizing the Operation Sequence of Chip Shooter Machine Based on the Particle Swarm Optimization Algorithm

2012 ◽  
Vol 220-223 ◽  
pp. 1271-1276
Author(s):  
Wan Lei Liang ◽  
Xiao Dan Guan
Keyword(s):  
Genetic Algorithm ◽  
Pso Algorithm ◽  
Experimental Result ◽  
Coding System ◽  
Simulation Test ◽  
Before And After ◽  
Key Factor ◽  
Genetic Algorithm Method ◽  
Scheduling Method ◽  
The Cost

The mounting process is the key factor of the placement efficiency, it is also important for the improvement of the efficiency of whole production line and decrease of the cost. This paper analyzed the mounting process of the Chip Shooter machine, applied the PSO algorithm, constructed the corresponding coding system, proposed the corresponding particle update mechanism, introduced the partially matched crossover idea of the genetic algorithm into the PSO algorithm, and designed the new re-scheduling method of feeder position assignment to optimize the position assignment of feeders and the pickup and placement sequence of components, thus improved the placement efficiency. After comparing the results before and after the simulation test for selected 8 pieces of PCB, the average efficiency of this algorithm is 7.09% higher than genetic algorithm method that is based on sort encoding. The experimental result shows that, this algorithm is more efficiency on the improvement placement efficiency and decrease of the placement time for the chip shooter machine.

Multi-Objective Optimization of a 2-DoF Purely Translational Parallel Manipulator

2011 ◽  
Vol 317-319 ◽  
pp. 794-798
Author(s):  
Zhi Bin Li ◽  
Yun Jiang Lou ◽  
Yong Sheng Zhang ◽  
Ze Xiang Li
Keyword(s):  
Genetic Algorithm ◽  
Kinematic Analysis ◽  
Parallel Manipulator ◽  
Pareto Front ◽  
Parallel Robot ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Evolution Algorithm

The paper addresses the multi-objective optimization of a 2-DoF purely translational parallel manipulator. The kinematic analysis of the Proposed T2 parallel robot is introduced briefly. The objective functions are optimized simultaneously to improve Regular workspace Share (RWS) and Global Conditioning Index (GCI). A Multi-Objective Evolution Algorithm (MOEA) based on the Control Elitist Non-dominated Sorting Genetic Algorithm (controlled ENSGA-II) is used to find the Pareto front. The optimization results show that this method is efficient. The parallel manipulator prototype is also exhibited here.

scholarly journals Comparison of Planar Parallel Manipulator Architectures Based on a Multi-Objective Design Optimization Approach

2010 ◽  
Author(s):  
Damien Chablat ◽  
Ste´phane Caro ◽  
Raza Ur-Rehman ◽  
Philippe Wenger
Keyword(s):  
Genetic Algorithm ◽  
Design Optimization ◽  
Parallel Manipulator ◽  
Optimization Problem ◽  
Optimization Approach ◽  
Objective Functions ◽  
Multi Objective ◽  
Planar Parallel Manipulator ◽  
Moving Platform ◽  
Pareto Frontiers

This paper deals with the comparison of planar parallel manipulator architectures based on a multi-objective design optimization approach. The manipulator architectures are compared with regard to their mass in motion and their regular workspace size, i.e., the objective functions. The optimization problem is subject to constraints on the manipulator dexterity and stiffness. For a given external wrench, the displacements of the moving platform have to be smaller than given values throughout the obtained maximum regular dexterous workspace. The contributions of the paper are highlighted with the study of 3-PRR, 3-RPR and 3-RRR planar parallel manipulator architectures, which are compared by means of their Pareto frontiers obtained with a genetic algorithm.

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