Expected Response Times for Closed-Loop Multivehicle AMHS

We present an analytical approach for estimating the expected time for an automated material handling system (AMHS) to respond to move requests at loading stations in a vehicle-based, unidirectional, closed-loop AMHS. The expected response times are important for estimating the expected work-in-process (WIP) levels at the loading stations for design purposes, and for evaluating the performance of the AMHS as delayed response can impact the production cycle times. The expected response time approximation is validated by comparing the analytical model to the simulation results using a SEMATECH 300 mm hypothetical fab data set. Note to Practitioners - This paper describes an analytic method for estimating the average time for the AMHS to respond to lots ready for movement in a 300 mm wafer fab. The analysis is based on a large-scale model, requires standard solvers, and provides a very fast and reasonably accurate alternative to high-fidelity simulation. It is intended to support the early stage of fab design/redesign, allowing engineers to examine many different options before committing to the time and expense of simulation.     

Performance evaluation of an automated material handling system for a wafer fab

Discrete-event simulation model was developed to evaluate the performance of an automated material handling system (AMHS) for a wafer fab with a zone control scheme avoiding all vehicle collision. The layout of this AMHS is a custom configuration. The track option contains turntables, turnouts and high-speed express lanes. The behavior of the interarrival for all stockers from the real data set was analyzed to verify the assumption of the simulation model. The results show that the underlying distributions of most stockers for interarrival times belong to the exponential or Weibull distribution. The simulation results show that the number of vehicles significantly affects the average delivery time and the average throughput. A simple one-factor response surface model is used to determine the appropriate vehicle numbers. This study was also investigated to determine the vehicle numbers in an automated guided vehicle-based intrabay material handling system.     

Simulation study for a proposed segmented automated material handling system design for 300-mm semiconductor fabs

With the increase in the size and weight of 300-mm wafers, the factory area must be enlarged accordingly. Due to the flow of material over long distances, the elimination of manual wafer handling has become necessary. Consequently, an automated material handling system (AMHS) is required for 300-mm semiconductor manufacturing facilities. The design of an AMHS must not only be capable of meeting numerous complex material handling requirements, but it must also simplify control and reduce capacity loss. In this study, a segmented dual-track bidirectional loop (SDTBL) design for an AMHS is proposed. The configuration is based on a double-loop flow path structure that is divided into non-overlapping segments, each containing a certain number of vehicles operating in bidirectional mode. A transfer buffer is set to enable conversion between segments and connect each independent zone. This structure eliminates congestion and blocking without requiring additional investment by operating vehicles on mutually exclusive tracks. The segmentation strategies and steps for two scenarios are developed in this research, and a simulation is performed to evaluate the performance of each segmented strategy. The simulation results show that the proposed strategies can reduce the cycle time and increase stocker utilization by up to 55.55% and 39.39%, respectively, while the throughput remains the same. The proposed design has great potential for practical application.     

Dynamic vehicle allocation control for automated material handling system in semiconductor manufacturing

The current study examines the dynamic vehicle allocation problems of the automated material handling system (AMHS) in semiconductor manufacturing. With the uncertainty involved in wafer lot movement, dynamically allocating vehicles to each intrabay is very difficult. The cycle time and overall tool productivity of the wafer lots are affected when a vehicle takes too long to arrive. In the current study, a Markov decision model is developed to study the vehicle allocation control problem in the AMHS. The objective is to minimize the sum of the expected long-run average transport job waiting cost. An interesting exhaustive structure in the optimal vehicle allocation control is found in accordance with the Markov decision model. Based on this exhaustive structure, an efficient algorithm is then developed to solve the vehicle allocation control problem numerically. The performance of the proposed method is verified by a simulation study. Compared with other methods, the proposed method can significantly reduce the waiting cost of wafer lots for AMHS vehicle transportation.     

Application of a genetic algorithm in solving the capacity allocation problem with machine dedication in the photolithography area

Wafer fabrication is a complicated manufacturing process with high process capability. Hence, maximizing machine capacity to meet customer deadlines is a very important issue in this field. This study proposes an integer programming model and a heuristic algorithm approach to solve the loading balance problem for the photolithography area in the semiconductor manufacturing industry. Considering process capability, machine dedication, and reticle constraints, we aim to minimize the difference in loading between machines. Process capability means that each product must be processed in machines that meet the process specification. Machine dedication means that if the first critical layer of a wafer is assigned to a certain machine, then the following critical layers of such wafer must be processed in this certain machine to ensure wafer quality. This research compares the results of two methods and finds the best parameter settings of the genetic algorithm (GA). The computational performance results of the GA shows that we can find the near-optimal solution within a reasonable amount of time. Finally, this research analyzes machine capability and reticle flexibility to determine the best percentage that can be used as reference for application in the semiconductor industry.     

A novel approach to hedge and compensate the critical dimension variation of the developed-and-etched circuit patterns for yield enhancement in semiconductor manufacturing

Linewidth control is critical for yield enhancement in semiconductor manufacturing. As wafer fabrication reaching nano-technology nodes, existing approaches on advanced equipment control and advanced process control (AEC/APC) for variation control of individual processes are increasingly difficult to achieve desired process control due to shrinking process windows. This study aims to propose a novel approach to determine tool affinity to hedge the variation between the photolithography for pattern development and the etching process to effectively reduce the etching bias caused by tool misalignment. In particular, the proposed approach integrates a feed-forward run-to-run (R2R) controller and the proposed mini-max regret tool dispatching rules in light of the tool characteristics of the photolithography and etching processes. To validate the proposed approach, an empirical study was conducted in a leading semiconductor company in Taiwan and the results showed practical viability of the approach.     

A new iterative mutually coupled hybrid GA–PSO approach for curve fitting in manufacturing

Fitting data points to curves (usually referred to as curve reconstruction) is a major issue in computer-aided design/manufacturing (CAD/CAM). This problem appears recurrently in reverse engineering, where a set of (possibly massive and noisy) data points obtained by 3D laser scanning have to be fitted to a free-form parametric curve (typically a B-spline). Despite the large number of methods available to tackle this issue, the problem is still challenging and elusive. In fact, no satisfactory solution to the general problem has been achieved so far. In this paper we present a novel hybrid evolutionary approach (called IMCH-GAPSO) for B-spline curve reconstruction comprised of two classical bio-inspired techniques: genetic algorithms (GA) and particle swarm optimization (PSO), accounting for data parameterization and knot placement, respectively. In our setting, GA and PSO are mutually coupled in the sense that the output of one system is used as the input of the other and vice versa. This coupling is then repeated iteratively until a termination criterion (such as a prescribed error threshold or a fixed number of iterations) is attained. To evaluate the performance of our approach, it has been applied to several illustrative examples of data points from real-world applications in manufacturing. Our experimental results show that our approach performs very well, being able to reconstruct with very high accuracy extremely complicated shapes, unfeasible for reconstruction with current methods.     

Evaluating investment-return-based design for AMHS in semiconductor manufacturing system

An effective automated material handling system (AMHS) design improves production performance. Investment return is a primary concern for high technology companies when purchasing production equipment. This study demonstrates that when profit gained from investing in non-production equipment investment can be estimated, investment return can be evaluated and used as an investment index for non-production equipment. An effective approach based on Little’s law for AMHS design is proposed. This approach quantifies system improvement resulting from a specific AMHS design. Then, an activity and theory of constraints based (ABC/TOC) costing model is used to capitalize the improvement. Finally, the investment-return time length for that specific design can be evaluated. An investor can easily decide among several designs when using the proposed approach.     

A dispatching rule for photolithography scheduling with an on-line rework strategy

Generally speaking, wafer fabrication factories define the photolithography area as the dispatching center of the entire factory. To establish a set of operative dispatching rules in the photolithography area while taking into consideration the rework of defective products would assist in coordinating and balancing the workload of the entire production line. Furthermore, it would help to enhance both the productivity and efficiency of the wafer fabrication, reduce the on-line WIP stock, shorten the production cycle time, and satisfy the requirements of customers regarding production due time and product quality. This research uses on-line rework as the basis for bringing the factor of reworking of a batch process into the dispatching rule for measurement. It then develops the dispatching rule (Rw-DR) which includes the rework strategy. In addition, this research focuses on the batch with high finished proportion in the photolithography area for finding a way to complete the manufacturing procedure faster, lighten the machine workload of the waiting line, and at the same time increase the output quantity.     

A hybrid push/pull-dispatching rule for a photobay in a 300 mm wafer fab

In this paper, the simulation analysis of an automated material handling system (AMHS) for a photobay in a 300 mm wafer fab was analyzed, considering the effects of the dispatching rules. Discrete-event simulation models were developed in an e-M Plant to study this system. Currently, the combination of the shortest distance with the nearest vehicle (SD_NV) and the first-encounter first-served (FEFS) dispatching rule was used in this system. In order to improve the system performance, a hybrid push/pull (PP) dispatching rule was proposed. The simulation results reveal a substantial improvement of the AMHS performance and reduced the WIP and cycle time as a consequence of implementing a PP dispatching rule.     

A modular simulation approach for automated material handling systems

In this paper, the authors present a modular simulation approach for the evaluation of automated material handling systems (AMHSs). The approach involves the use of high level modularity so that alternative AMHS scenarios can be evaluated using identical or nearly identical source code. The approach is implemented using the AutoMod simulation platform, and the efficacy of the strategy is demonstrated through a case study with the United States Postal Service. Results indicate that the approach is viable and that it is of value for the evaluation of AMHS scenarios in general.     

Cycle time analysis of dual-arm cluster tools for wafer fabrication processes with multiple wafer revisiting times

For some wafer fabrication processes, the wafers need to visit some processing modules for a number of times, which is referred to as the revisiting process. With wafer revisiting, it is very complicated to analyze the cycle time of a dual-arm cluster tool. Due to the fact that atomic layer deposition (ALD) process is a typical revisiting process in the semiconductor industry, study is conducted on cycle time analysis of dual-arm cluster tools for the ALD process with multiple revisiting times. The system is modeled by a type of Petri net. With this model, it is revealed that the system may never reach a steady state. Based on this finding, a method is presented to analyze the cycle time and analytical expressions are derived to calculate the cycle time for different cases. Several illustrative examples are given to show the applications of the proposed approach.     

光刻机的防死锁调度

半导体生产线是目前世界上公认的最复杂的制造系统之一。光刻机是半导体晶圆制造的瓶颈设备,其费用相当昂贵。光刻机由若干个自动组合装置组成,如果调度不当,生产可能会出现死锁。死锁的发生不仅大大降低光刻机的效率,而且破坏晶圆质量。本文利用图论的算法编制软件并进行仿真可以得到无死锁的调度方案。     

Multi-objective real-time dispatching for integrated delivery in a Fab using GA based simulation optimization

In a wafer fabrication Fab, the “integrated delivery”, which integrates the automated material handling system (AMHS) with processing tools to automate the material flow, is difficult to implement due to the system complexity and uncertainty. The previous dispatching studies in semiconductor manufacturing have mainly focused on the tool dispatching. Few studies have been done for analyzing combinatorial dispatching rules including lot dispatching, batch dispatching and automated guided vehicle (AGV) dispatching. To handle this problem, a GA (genetic algorithm) based simulation optimization methodology, which consists of the on-line scheduler and the off-line scheduler, is presented in this paper. The on-line scheduler is used to monitor and implement optimal combinatorial dispatching rules to the semiconductor wafer fabrication system. The off-line scheduler is employed to search for optimal combinatorial dispatching rules. In this study, the response surface methodology is adopted to optimize the GA parameters. Finally, an experimental bay of wafer fabrication Fab is constructed and numerical experiments show that the proposed approach can significantly improve the performance of the “integrated delivery system” compared with the traditional single dispatching rule approach.     

基于改进PSO算法的移动机器人路径规划

针对粒子群优化(PSO)算法收敛速度快但容易陷入局部极值和细菌觅食优化(BFO)算法全局搜索能力强但效率低的问题,提出了一种将BFO算法的趋化、迁徙和复制操作引入到粒子群搜索过程的具有全局搜索能力和快速收敛的混合算法.在BFO算法和PSO算法的原理、操作步骤基础上,分别使用了PSO算法、BFO法和混合算法对移动机器人进行全局路径规划仿真试验,并分别给出了各算法的迭代次数、适应值曲线.仿真结果表明:与PSO算法和BFO算法相比,所提出的混合算法具有搜索时间短、迭代次数少的优点,较好验证了混合算法在移动机器人路径规划方面的可行性和有效性.     

Adhesive wafer bonding with photosensitive polymers for MEMS fabrication

Adhesive wafer bonding is a technique that uses an intermediate layer (typically a polymer) for bonding two substrates. The main advantages of using this approach are: low temperature processing (maximum temperatures lower than 400°C), surface planarization and tolerance to particles contamination (the intermediate layer can incorporate particles with the diameter in the layer thickness range). The main bonding layers properties required by a large field of applications/designs can be summarized as: isotropic dielectric constants, good thermal stability, low Young’s modulus, and good adhesion to different substrates. This paper reports on wafer-to-wafer adhesive bonding using SINR^TM polymer materials. Substrate coating process as well as wafer bonding process parameters optimization was studied. Statistical analysis methods were used to show repeatability and reliability of coating processes. Features of as low as 15 μm size were successfully resolved by photolithography and bonded. An unique megasonic-enhanced development process of the patterned film using low cost solvent was established and proven to exceed standard development method performance.     

Confidence level solutions for stochastic programming

We propose an alternative approach to stochastic programming based on Monte-Carlo sampling and stochastic gradient optimization. The procedure is by essence probabilistic and the computed solution is a random variable. We propose a solution concept in which the probability that the random algorithm produces a solution with an expected objective value departing from the optimal one by more than ? is small enough. We derive complexity bounds on the number of iterations of this process. We show that by repeating the basic process on independent samples, one can significantly reduce the number of iterations.     

粒子群优化算法在配方设计中的应用

随着群体智能研究的兴起,粒子群优化(PSO,Particle Swarm Optimization)算法已经成为新的研究热点。该算法模仿鸟类和鱼类群体觅食迁徙中个体与群体协调一致的机理,通过群体最优方向、个体最优方向和惯性权重的协调来求解实数化问题。本文从粒子群优化算法的理论分析切入,阐述了PSO算法的基本原理、算法流程,提出用PSO算法来解决卷烟配方优化设计这类组合优化问题,并对其实际应用效果进行分析和验证。     

Multi-Objective Particle Swarm Optimization with time variant inertia and acceleration coefficients

In this article we describe a novel Particle Swarm Optimization (PSO) approach to multi-objective optimization (MOO), called Time Variant Multi-Objective Particle Swarm Optimization (TV-MOPSO). TV-MOPSO is made adaptive in nature by allowing its vital parameters (viz., inertia weight and acceleration coefficients) to change with iterations. This adaptiveness helps the algorithm to explore the search space more efficiently. A new diversity parameter has been used to ensure sufficient diversity amongst the solutions of the non-dominated fronts, while retaining at the same time the convergence to the Pareto-optimal front. TV-MOPSO has been compared with some recently developed multi-objective PSO techniques and evolutionary algorithms for 11 function optimization problems, using different performance measures.     

A combinative technique to fabricate hot embossing master for PMMA tunneling sensors

A combinative approach of anisotropic bulk etching and modified plasma etching has been successfully employed in a single wafer to fabricate silicon masters for the hot embossing process. The masters hold both pyramid pits and positive profile sidewalls with smooth surfaces and steep angles. The SiO₂ layer is utilized as a etching mask with the aid of photoresist in three steps of photolithography patterning. The first polymethyl-methacrylate (PMMA)-based tunneling transducer with polymer membrane structures is fabricated by hot embossing replication with the silicon master. Consequently, the exponential relations between tunneling currents and applied deflection voltages are also reported.This work is partially supported by grants NSF/LEQSF (2001–04)-RII-02, DARPA DAAD19–02–1-0338, and NASA (2002)-Stennis-22.