Cycle time analysis for wafer revisiting process in scheduling of single-arm cluster tools

Some wafer fabrication processes performed by cluster tools require revisiting. With wafer revisiting, a cluster tool is very difficult to be scheduled due to a large number of possible schedules for the revisiting process. Atomic layer deposition (ALD) is a typical process with wafer revisiting that should be performed by cluster tools. This paper discusses the scheduling problem of single-arm cluster tools for the ALD process. In scheduling such a system, the most difficult part is to schedule the revisit...     

晶圆重入加工的组合设备终止暂态的调度与分析

晶圆重入是半导体组合设备加工中典型的复杂加工工艺,分析和优化暂态加工过程对于晶圆重入加工具有重要意义.为了满足加工需求和提高组合设备的加工性能,基于稳态重入加工的双臂组合设备Petri网模型和1-晶圆周期调度策略,采用虚拟晶圆的加工模式分析了系统的终止暂态过程,讨论了系统终止暂态的加工时间分布,并给出相应的解析式进行描述.利用eM-Plant仿真平台建立了重入加工的双臂组合设备终止暂态的仿真模型,并用例子验证了1-晶圆周期调度的可行性及解析式的有效性,为研究晶圆重入加工过程的优化提供了有效方法和手段.     

腔室清洗的单臂组合设备初始暂态调度

为了提升腔室洁净度,晶圆厂需对组合设备腔室进行清洗操作,从而提高晶圆的加工质量.考虑腔室清洗时间和晶圆驻留时间的约束条件下,本文研究了单臂组合设备的初始暂态调度问题.首先,提出了机械手的初始暂态活动规则,并对机械手活动序列进行描述,实现了系统的初始暂态可调度性;其次,对机械手在初始暂态和稳态的活动时间进行了建模;然后,根据系统的时间特性,建立了初始暂态调度的线性规划模型;最后,通过实例验证了该方法的有效性.与已有的虚拟晶圆方法相比,该调度方法能有效减少初始暂态的完工时间,提高了组合设备的晶圆生产效率.     

具有清洗工艺的单臂组合设备终止暂态调度

随着多品种小批量生产模式的普及,导致了组合设备频繁的暂态加工过程.为了提高组合设备的生产柔性,同时考虑晶圆驻留时间约束和腔室清洗时间约束,研究了单臂组合设备的终止暂态调度问题.首先,提出了 1-周期清洗工艺的暂态调度规则,并采用了面向资源的Petri网对单臂组合设备的终止暂态过程进行建模,引入避免死锁的变迁触发规则;其次,根据系统的终止暂态时间特性并考虑不同的调度情形,建立了终止暂态调度的线性规划模型;最后,通过实例验证了该方法的可行性.实验结果表明,与运用改进拉式策略的虚拟晶圆方案相比,该调度方案可有效地减少组合设备终止暂态的完工时间,并满足晶圆制造的工艺要求.     

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.     

具有多品种晶圆混合加工的单臂组合设备调度

为了提高晶圆制造中组合设备的生产效率,在考虑晶圆驻留时间约束条件下,研究没有共享加工模块的多品种晶圆混合加工的单臂组合设备调度问题.首先,采用面向资源的Petri网模型描述多种晶圆产品的混合加工过程,引入控制变迁避免模型的死锁,采用赋时库所和赋时变迁模拟系统资源的活动时间.其次,通过虚拟加工的方法平衡工序的负载,基于系统Petri网模型和拉式调度策略,推导出单臂组合设备在多品种晶圆混合加工情形下的可调度性判定条件,并以解析形式描述.最后,提出了系统稳态调度求解算法并以实例验证了算法的有效性和可行性.     

Rule-based scheduling in wafer fabrication with due date-based objectives

Wafer fabrication is a capital-intensive and highly complex manufacturing process. In the wafer fabrication facility (fab), wafers are grouped as a lot to go through repeated sequences of operations to build circuitry. Lot scheduling is an important task for manufacturers to improve production efficiency and meet customers’ requirements of on-time delivery. In this research we propose a dispatching rule for lot scheduling in wafer fabs, focusing on three due date-based objectives: on-time delivery rate, mean tardiness, and maximum tardiness. Although many dispatching rules have been proposed in the literature, they usually perform well in some objectives and bad in others. Our rule implements good principles in existing rules by means of (1) an urgency function for a single lot, (2) a priority index function considering total urgency of multiple waiting lots, (3) a due date extension procedure for dealing with tardy lots, and (4) a lot filtering procedure for selecting urgent lots. Simulation experiments are conducted using nine data sets of fabs. Six scenarios formed by two levels of load and three levels of due date tightness are tested for each fab. Performance verification of the proposed rule is achieved by comparing with nine benchmark rules. The experimental results show that the proposed rule outperforms the benchmark rules in terms of all concerned objective functions.     

Scheduling Dual-Arm Cluster Tools With Multiple Wafer Types and Residency Time Constraints

Accompanying the unceasing progress of integrated circuit manufacturing technology, the mainstream production mode of current semiconductor wafer fabrication is featured with multi-variety, small batch, and individual customization, which poses a huge challenge to the scheduling of cluster tools with single-wafer-type fabrication. Concurrent processing multiple wafer types in cluster tools, as a novel production pattern, has drawn increasing attention from industry to academia, whereas the corresponding research remains insufficient. This paper investigates the scheduling problems of dual-arm cluster tools with multiple wafer types and residency time constraints. To pursue an easy-to-implement cyclic operation under diverse flow patterns,we develop a novel robot activity strategy called multiplex swap sequence. In the light of the virtual module technology, the workloads that stem from bottleneck process steps and asymmetrical process configuration are balanced satisfactorily. Moreover, several sufficient and necessary conditions with closed-form expressions are obtained for checking the system's schedulability. Finally, efficient algorithms with polynomial complexity are developed to find the periodic scheduling, and its practicability and availability are demonstrated by the offered illustrative examples.     

Manufacturing cell design using simulated annealing: An industrial application

In this paper, we give a brief summary of simulated annealing (SA) procedures used to solve combinatorial optimization problems. We then present the manufacturing cell design problem which consists of designing cells of limited size in order to minimize inter-cell traffic. We show how to use a SA approach to obtain a good, if not optimum, solution to this problem. Finally, we apply this approach to an industrial problem and compare the results to the ones obtained using the so-called twofold heuristic algorithm.     

Flow-shop sequencing using hybrid simulated annealing

Simulated annealing (SA) heuristics have been successfully applied on a variety of complex optimization problems. This paper presents a new hybrid SA approach for the permutation flow-shop scheduling (FSS) problem. FSS is known to be NP-hard, and thus the right way to proceed is through the use of heuristics techniques. The proposed approach combines the characteristics of a canonical SA procedure together with features borrowed from the field of genetic algorithms (GAs), such as the use of a population of individuals and the use of a novel, non-standard recombination operator for generating solutions. The approach is easily implemented and performs near-optimal schedules in a rather short computation time. Experiments over multiple benchmarks test problems show that the developed approach has higher performance than that of other FSS meta-heuristic approaches, generating schedules of shorter makespans faster. The experiments include comparisons between the proposed hybrid model, a genetic algorithm, and two other standard simulated annealing approaches. The final solutions obtained by the method are within less than 1% in average from the optimal solutions obtained so far.     

Decomposition-based classified ant colony optimization algorithm for scheduling semiconductor wafer fabrication system

Due to its typical features, such as large-scale, multiple re-entrant flows, and hybrid machine types, the semiconductor wafer fabrication system (SWFS) is extremely difficult to schedule. In order to cope with this difficulty, the decomposition-based classified ant colony optimization (D-CACO) method is proposed and analyzed in this paper. The D-CACO method comprises decomposition procedure and classified ant colony optimization algorithm. In the decomposition procedure, a large and complicate scheduling problem is decomposed into several subproblems and these subproblems are scheduled in sequence. The classified ACO algorithm then groups all of the operations of the subproblems and schedules them according to machine type. To test the effect of the method, a set of simulations are conducted on a virtual fab simulation platform. The test results show that the proposed D-CACO algorithm works efficiently in scheduling SWFS.     

稳态调度下单臂组合设备时间延迟分析与优化

在半导体晶圆制造过程中,驻留时间延迟过长对晶圆质量具有消极影响.本文研究单臂组合设备稳态调度中如何合理地分配机械手等待时间,抵消驻留时间延迟的问题.首先,采用Petri网模型描述晶圆制造过程,分析了单臂组合设备稳态调度的时间特性,获得了稳态下工序驻留时间延迟计算表达式.其次,通过解构机械手等待时间对驻留时间延迟的影响机理,提出了一种机械手等待时间分配优先级规则.进一步,将虚拟瓶颈工序用于辅助分配机械手等待时间,结合优先级规则,提出了一种单臂组合设备稳态调度启发式算法.最后,通过例子验证了算法的可行性与有效性.与传统拉式策略和尽早加工策略对比,该算法能有效地减少单臂组合设备稳态调度下的驻留时间延迟并能满足晶圆制造的严格要求.     

基于蚁群算法的半导体生产线调度方法研究

为了解决具有可重入特性的半导体生产线调度问题,提出基于蚁群算法的半导体生产线调度模型（ASWFSM）。在模型中,利用图论的方法把调度方案的寻优过程转换为蚂蚁对有向图的搜索,并且,引入专家系统作为推理机避免了寻优过程中对可行节点判断的复杂性。仿真试验证明,此模型具有良好的调度效果和稳定性。     

A simulated annealing algorithm for the job shop cell scheduling problem with intercellular moves and reentrant parts

This paper addresses the problem of scheduling parts in job shop cellular manufacturing systems by considering exceptional parts that need to visit machines in different cells and reentrant parts which need to visit some machines more than once in non-consecutive manner. Initially, an integer linear programming (ILP) model is presented for the problem to minimize the makespan, which considers intercellular moves and non-consecutive multiple processing of parts on a machine. Due to the complexity of the model, a simulated annealing (SA) based solution approach is developed to solve the problem. To increase the efficiency of the search algorithm, a neighborhood structure based on the concept of blocks is applied. Subsequently, the efficiency of the ILP model and the performance of the proposed SA are assessed over a set of problem instances taken from the literature. The proposed ILP model was coded in Lingo 8.0 and the solution obtained by the proposed SA was compared to the optimal values. The computational results demonstrate that the proposed ILP model and SA algorithm are effective and efficient for this problem.     

Applying simulated annealing for designing cellular manufacturing systems using MDmTSP

The design of cellular manufacturing systems involves many structural and operational issues. One of the important design steps is the formation of part families and machine cells (cell formation). Despite a large number of papers on cell formation published worldwide, only a handful incorporates operation sequence in layout design (intra-cell move calculations). We propose a solution to solve the part-family and machine-cell formation problem considering the within-cell layout problem, simultaneously. In this paper, the cellular manufacturing system is formulated as a multiple departures single destination multiple travelling salesman problem (MDmTSP) and a solution methodology based on simulated annealing is proposed to solve the formulated model. Numerical examples show that the proposed method is efficient and effective in finding optimal solutions. The results also indicate that the proposed approach performs well compared to some well-known cell formation methods.     

基于eM-Plant的虚拟晶圆制造自动组合装置

针对难以用解析法验证半导体加工装置的调度可行性问题,提出仿真建模研究的新方法。利用仿真软件eM-Plant建立晶圆制造中单臂自动组合装置的参数化仿真模型,构建一个虚拟的晶圆制造系统。该系统为研究自动组合装置控制问题提供有效手段,是验证半导体制造生产调度可行性的仿真平台。     

融合K-调和均值和模拟退火粒子群的混合聚类算法

针对K-调和均值和模拟退火粒子群聚类算法的优缺点,提出了1种融合K-调和均值和模拟退火粒子群的混合聚类算法。首先通过K-调和均值方法将粒子群分成若干个子群,每个粒子根据其个体极值和所在子种群的全局极值来更新位置。同时引入模拟退火思想,抑制了早期收敛,提高了计算精度。本文使用Iris、Zoo、Wine和Image Segmentation,4个数据库,以F-measure为评价聚类效果的标准,对混合聚类算法进行了验证。研究发现,该混合聚类算法可以有效地避免陷入局部最优,在保证收敛速度的同时增强了算法的全局搜索能力,明显改善了聚类效果。该算法目前已用于无锡一淡水养殖基地的水产健康养殖水质分析系统,运行效果良好。     

遗传模拟退火算法在服装排料中的研究

提出了一种基于遗传模拟退火算法的启发式排样算法,并将这种算法应用于服装排样领域以减少原料的浪费。该算法通过基于遗传模拟退火算法的全局优化概率搜索,寻找排样件在排样时的最优次序及各自的旋转角度,然后采用基于左下角(BL)策略的启发式排样算法实现自动排样。     

聚类问题的自适应杂交差分演化模拟退火算法

针对K-均值聚类算法对初始值敏感和易陷入局部最优的缺点,提出了一个基于自适应杂交差分演化模拟退火的K-均值聚类算法。该算法以差分演化算法为基础,通过模拟退火算法的更新策略来增强全局搜索能力,并运用自适应技术来选择学习策略、确定算法的关键参数。实验结果表明,该算法能较好地克服传统K-均值聚类算法的缺点,具有较好的全局收敛能力,且算法稳定性强、收敛速度快,将新算法与传统的K-均值聚类算法以及最近提出的几个同类聚类算法进行了比较。     

改进的退火遗传优化策略应用研究

地震参数反演属于典型的非线性优化问题。针对遗传算法和模拟退火算法各自的优缺点,将改进的遗传算法与模拟退火算法相结合,提出了改进的退火遗传算法（ISAGA）。该方法通过筛选和修复进行初始种群的选择,采用允许父代参与竞争的退火选择机制,并根据模拟退火思想对交叉和变异概率进行自适应的调整,从而增加了种群的多样性并提高了收敛速度。该方法既具备了遗传算法强大的全局搜索能力,也拥有模拟退火算法强大的局部搜索能力。经理论模型试算结果表明,该方法不仅收敛速度快,优化精度高,抗干扰能力强,而且避免了局部收敛和依赖初始模型等问题,计算所得反演参数更接近于实际观测值。