The Experts below are selected from a list of 11994 Experts worldwide ranked by ideXlab platform
Mengchu Zhou - One of the best experts on this subject based on the ideXlab platform.
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scheduling of single arm cluster tools for an atomic layer deposition process with residency time constraints
IEEE Transactions on Systems Man and Cybernetics, 2017Co-Authors: Fajun Yang, Yan Qiao, Mengchu ZhouAbstract:In semiconductor manufacturing, there are wafer fabrication processes with wafer revisiting. Some of them must meet wafer residency time constraints. Taking atomic layer deposition (ALD) as a typical wafer revisiting process, this paper studies the challenging scheduling problem of single-arm cluster tools for the ALD process with wafer residency time constraints. It is found that there are only several scheduling strategies that are applicable to this problem and one needs to apply each of them to decide whether a Feasible Schedule can be found or not. This work, for each applicable strategy, performs the schedulability analysis and derives the schedulability conditions for such tools for the first time. It proposes scheduling algorithms to obtain an optimal Schedule efficiently if such conditions are met. It finally gives illustrative examples to show the application of the proposed concepts and approach.
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pareto optimization for scheduling of crude oil operations in refinery via genetic algorithm
IEEE Transactions on Systems Man and Cybernetics, 2017Co-Authors: Yan Hou, Mengchu ZhouAbstract:With the interaction of discrete-event and continuous processes, it is challenging to Schedule crude oil operations in a refinery. This paper studies the optimization problem of finding a detailed Schedule to realize a given refining Schedule. This is a multiobjective optimization problem with a combinatorial nature. Since the original problem cannot be directly solved by using heuristics and meta-heuristics, the problem is transformed into an assignment problem of charging tanks and distillers. Based on such a transformation, by analyzing the properties of the problem, this paper develops a chromosome that can describe a Feasible Schedule such that meta-heuristics can be applied. Then, it innovatively adopts an improved nondominated sorting genetic algorithm to solve the problem for the first time. An industrial case study is used to test the proposed solution method. The results show that the method makes a significant performance improvement and is applicable to real-life refinery scheduling problems.
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schedulability analysis and optimal scheduling of dual arm cluster tools with residency time constraint and activity time variation
IEEE Transactions on Automation Science and Engineering, 2012Co-Authors: Mengchu ZhouAbstract:With wafer residency time constraint of cluster tools in semiconductor manufacturing, activity time variation can make an originally Feasible Schedule inFeasible. Thus, it is difficult to Schedule them and schedulability is a vitally important issue. With bounded activity time variation considered, this paper addresses their real-time scheduling issues and conducts their schedulability analysis. A Petri net (PN) model and a control policy are presented. Based on them, this paper derives closed-form schedulability conditions. If schedulable, an algorithm is developed to obtain an offline periodic Schedule. This Schedule together with the control policy forms a real-time Schedule. It is optimal in terms of cycle time and can be analytically computed, which represents significant advance in this area.
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application of petri nets and lagrangian relaxation to scheduling automatic material handling vehicles in 300 mm semiconductor manufacturing
Systems Man and Cybernetics, 2007Co-Authors: Dayinl Iao, Muder Jeng, Mengchu ZhouAbstract:This paper deals with vehicle-scheduling problem (VSP) in an automatic material-handling environment in 300-mm semiconductor wafer manufacturing. We adopt Petri nets (PNs) modeling techniques to model the complicated coupling dynamics among transport jobs and overhead hoist transport (OHT) vehicles in a 300-mm OHT loop. The congestion phenomenon among OHT vehicles is captured. With help of the PN models, we formulate the OHT VSP as an integer programming problem whose objective is to Schedule OHT vehicles to transport jobs such that average job completion time is minimized. Instead of solving for the optimal solution, we develop a solution methodology to generate a Feasible Schedule efficiently. A Lagrangian relaxation step is first taken to decompose the PN-based, integer programming problem into individual job-scheduling subproblems. To reduce computation efforts in solving each subproblem optimally, we develop an approximation method to solve each job subproblem by utilizing a reduced PN model of the job. Lagrangian multipliers are then optimized by a surrogate subgradient method. A heuristic algorithm is developed to adjust the dual solution to a Feasible Schedule. Numerical results demonstrate that our solution methodology can generate good Schedules within a reasonable amount of computation time for realistic problems. Compared to a popular vehicle-dispatching rule, our approach can achieve in average 32% improvements on the average delivery time in our realistic test cases.
C M Tam - One of the best experts on this subject based on the ideXlab platform.
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particle swarm optimization for resource constrained project scheduling
International Journal of Project Management, 2006Co-Authors: Hong Zhang, C M TamAbstract:Abstract This paper introduces the particle swarm optimization (PSO)-based approach to resolve the resource-constrained project scheduling problem (RCPSB) with the objective of minimizing project duration. Activities priorities for scheduling are represented by particles and a parallel scheme is utilized to transform the particle-represented priorities to a Feasible Schedule according to the precedence and resource constraints so as to be evaluated. Then the framework of the PSO scheme for the RCPSB is developed. Computational analyses are provided so as to investigate the performance of the PSO-based approach for the RCPSB. The study aims at developing an alternative and efficient optimization methodology for solving the RCPSB and opening the application of PSO to the optimization issues for construction project management.
Hong Zhang - One of the best experts on this subject based on the ideXlab platform.
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ant colony optimization based multi mode scheduling under renewable and nonrenewable resource constraints
Automation in Construction, 2013Co-Authors: Hong ZhangAbstract:Abstract An ant colony optimization (ACO)-based methodology for solving the multi-mode resource-constrained project scheduling problem (MRCPSP) considering both renewable and nonrenewable resources is presented. With regard to the MRCPSP solution consisting of activity sequencing and mode selection, two levels of pheromones are proposed to guide search in the ACO algorithm. Correspondingly, two types of heuristic information and probabilities as well as related calculation algorithms are introduced. Nonrenewable resource-constraint and elitist-rank strategy are taken into account in updating the pheromones. The flowchart of the proposed ACO algorithm is described, where a serial Schedule generation scheme is incorporated to transform an ACO solution into a Feasible Schedule. The parameter-selection and the resultant performance of the proposed ACO methodology are investigated through a series of computational experiments. It is expected to provide an effective alternative methodology for solving the MRCPSP by utilizing the ACO theory.
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particle swarm optimization for resource constrained project scheduling
International Journal of Project Management, 2006Co-Authors: Hong Zhang, C M TamAbstract:Abstract This paper introduces the particle swarm optimization (PSO)-based approach to resolve the resource-constrained project scheduling problem (RCPSB) with the objective of minimizing project duration. Activities priorities for scheduling are represented by particles and a parallel scheme is utilized to transform the particle-represented priorities to a Feasible Schedule according to the precedence and resource constraints so as to be evaluated. Then the framework of the PSO scheme for the RCPSB is developed. Computational analyses are provided so as to investigate the performance of the PSO-based approach for the RCPSB. The study aims at developing an alternative and efficient optimization methodology for solving the RCPSB and opening the application of PSO to the optimization issues for construction project management.
Taeeog Lee - One of the best experts on this subject based on the ideXlab platform.
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schedulability analysis of time constrained cluster tools with bounded time variation by an extended petri net
IEEE Transactions on Automation Science and Engineering, 2008Co-Authors: Jahee Kim, Taeeog LeeAbstract:Cluster tools for some wafer fabrication processes such as low-pressure chemical vapor deposition have strict wafer delay constraints. A wafer that completes processing in a processing chamber should leave the chamber within a specified time limit. Otherwise, the wafer suffers from severe quality troubles due to residual gases and heat within the chamber. An important engineering problem is to verify whether for given task times there exists a tool operation Schedule that satisfies the wafer delay limit. There have been studies on the problem, which all assume deterministic task times. However, in reality, the task times are subject to random variation. In this paper, we develop a systematic method of determining schedulability of time-constrained decision-free discrete-event systems, where time variation can be confined within finite intervals. To do this, we propose an extended Petri net for modeling such systems. We then develop a necessary and sufficient condition for which there always exists a Feasible Schedule and one for which there never exists any Feasible Schedule. We develop a graph-based computational procedure for verifying the schedulability conditions and determining the worst-case task delay. We demonstrate how the procedure can be used for cluster tool engineering to control wafer delays against wafer alignment failures and time variation.
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scheduling analysis of time constrained dual armed cluster tools
IEEE Transactions on Semiconductor Manufacturing, 2003Co-Authors: Jahee Kim, Taeeog Lee, Hwanyong Lee, Doobyeong ParkAbstract:Cluster tools, each of which consists of several single-wafer processing chambers and a wafer handling robot, have been increasingly used for diverse wafer fabrication processes. Processes such as some low pressure chemical vapor deposition processes require strict timing control. Unless a wafer processed at a chamber for such a process leaves the chamber within a specified time limit, the wafer is subject to quality problems due to residual gases and heat. We address the scheduling problem for such time-constrained dual-armed cluster tools that have diverse wafer flow patterns. We propose a systematic method of determining the schedulable process time range for which there exists a Feasible Schedule that satisfies the time constraints. We explain how to select the desirable process times within the schedulable process time range. We present a method of determining the tool operation Schedule. For more flexible scheduling under the time constraints, we propose a modification of the conventional swap operation in order to allow wafer delay on a robot arm during a swap operation. We compare the performance of the new swap strategy with that of the conventional swap strategy.
Dayinl Iao - One of the best experts on this subject based on the ideXlab platform.
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application of petri nets and lagrangian relaxation to scheduling automatic material handling vehicles in 300 mm semiconductor manufacturing
Systems Man and Cybernetics, 2007Co-Authors: Dayinl Iao, Muder Jeng, Mengchu ZhouAbstract:This paper deals with vehicle-scheduling problem (VSP) in an automatic material-handling environment in 300-mm semiconductor wafer manufacturing. We adopt Petri nets (PNs) modeling techniques to model the complicated coupling dynamics among transport jobs and overhead hoist transport (OHT) vehicles in a 300-mm OHT loop. The congestion phenomenon among OHT vehicles is captured. With help of the PN models, we formulate the OHT VSP as an integer programming problem whose objective is to Schedule OHT vehicles to transport jobs such that average job completion time is minimized. Instead of solving for the optimal solution, we develop a solution methodology to generate a Feasible Schedule efficiently. A Lagrangian relaxation step is first taken to decompose the PN-based, integer programming problem into individual job-scheduling subproblems. To reduce computation efforts in solving each subproblem optimally, we develop an approximation method to solve each job subproblem by utilizing a reduced PN model of the job. Lagrangian multipliers are then optimized by a surrogate subgradient method. A heuristic algorithm is developed to adjust the dual solution to a Feasible Schedule. Numerical results demonstrate that our solution methodology can generate good Schedules within a reasonable amount of computation time for realistic problems. Compared to a popular vehicle-dispatching rule, our approach can achieve in average 32% improvements on the average delivery time in our realistic test cases.
