 |
WSC 2005 Final Abstracts |
Semiconductor Manufacturing Track
Tuesday 3:30:00 PM 5:00:00 PM
Factory Simulation
Chair: John
Fowler (Arizona State University)
Efficient Simulations for Capacity Analysis and
Automated Material Handling System Design in Semiconductor Wafer
Fabs
Jesus A. Jimenez, Gerald Mackulak, and John W. Fowler (Arizona
State University)
Abstract:
The Automated Material Handling System (AMHS) must be
designed effectively so that it never becomes a limiting factor for the
capacity of 300mm wafer fabs. Ideally, a fully integrated fab simulation model
(i.e. a model containing detailed modeling constructs for the production
operations, the tools, the AMHS, and tool AMHS interactions) should be used in
order to design the AMHS. However, the problem is that it takes too much time
to simulate and analyze these models. Experimentation has demonstrated that
certain capacity models with less detailed AMHS representations can generate
accurate system predictions in comparison to the values produced by fully
integrated models. Because these less detailed models run faster, we can thus
assess efficiently the effects of an AMHS design configuration on equipment
capacity. A case study comparing the computational efficiency and the quality
of the performance predictions at different levels of detail will be
presented.
A Framework for Standard Modular Simulation in
Semiconductor Wafer Fabrication Systems
Jose A. Ramirez-Hernandez,
Heshan Li, and Emmanuel Fernandez (University of Cincinnati), Swee Leong
(National Institute of Standards and Technology (NIST)) and Charles R. McLean
(National Institute of Standards and Technology)
Abstract:
This paper presents the application of a framework,
proposed by the National Institute of Standards and Technology (NIST), for
standard modular simulation in semiconductor wafer fabrication facilities
(fabs). The application of the proposed framework resulted in the
identification and specification of four different elements in the context of
semiconductor fabs: (1) market sector, (2) hierarchical modeling levels, (3)
simulation case studies, (4) models and data. An example of the application of
the proposed simulation framework to a benchmark semiconductor fab model, the
so-called "Mini-fab", is presented. In this example, evaluation of production
performance under different workforces is studied. Current and future research
is focused on the improvement of the proposed framework (e.g., design and
testing of generic case studies).
A Discrete Event Simulation Model Simplification
Technique
Rachel T. Johnson, John W. Fowler, and Gerald T. Mackulak
(Arizona State University)
Abstract:
Cycle Time – Throughput curves (CT-TH), which plot the
average cycle time versus start rate for a given product mix, are often used
to support decisions made in manufacturing settings, such as the impact of
proposed changes in start rate on mean cycle time. Discrete event simulation
is often used to generate estimations of cycle time at a significant number of
traffic intensities (start rates). However, simulation often requires long run
lengths and extensive output analysis. In most manufacturing environments, the
time and/or budget available for such simulations is limited. As demands for
faster and more accurate results are required, alternative approaches to
improving simulation efficiency must be investigated. This research seeks to
develop a procedure for simplifying a detailed model into a fast (abstract)
simulation model that achieves a statistically indistinguishable level of
accuracy and precision. This technique has particular application in the
simulation of semiconductor manufacturing facilities.
Wednesday 8:30:00 AM 10:00:00 AM
Factory Control
Chair: Lars
Mönch (Technical University of Ilmenau)
Analysis of Production Control Methods for
Semiconductor Research and Development Fabs Using Simulation
Vikram
Ramamurthi, Michael E. Kuhl, and Karl D. Hirshman (Rochester Institute of
Technology)
Abstract:
A semiconductor company must bring technology to the
market as soon as its application is deemed feasible to be a leader in the
industry. The goal of this paper is to investigate production control methods
in semiconductor R&D fabs to minimize the time to market for the
aforementioned technology. Simulation models of a representative R&D fab
are run with different levels of bottleneck utilization, lot priorities,
primary and secondary dispatching strategies and due date tightness as
treatment combinations in a formally designed experiment. The fab performance
measures are percent on time delivery, average cycle time, standard deviation
of cycle time and average work-in-process. Fab characteristics are found to
influence the application of dispatching rules. However, several dispatching
rules are found to be robust across performance measures.
Simulation-based Assessment of Order Release
Strategies for a Distributed Shifting Bottleneck Heuristic
Lars
Mönch (Technical University of Ilmenau)
Abstract:
In this paper, we investigate the influence of several
order release strategies on the performance of a distributed shifting
bottleneck heuristic. The shifting bottleneck heuristic is a decomposition
approach that solves the overall scheduling problem by solving a sequence of
tool group scheduling problems and determines the overall solution by using a
disjunctive graph. We discuss a distributed version of the original shifting
bottleneck heuristic. By using a hierarchical approach we first assign planned
ready and completion dates to all lots with respect to a certain work area
where a work area is defined as a set of tool groups. We study several order
release strategies. It turns out that the distributed shifting bottleneck
heuristic performs well compared to dispatching rules only in high loaded job
shops. We present the results of computational experiments.
Using Simulation Based Approach to Improve on the
Mean Cycle Time Performance of Dispatching Rules
Chin Soon Chong
and Malcolm Yoke Hean Low (SIMTech) and Appa Iyer Sivakumar and Kheng Leng Gay
(Nanyang Technological University)
Abstract:
This paper presents a simulation based approach to
improve on the mean cycle time performance of dispatching rules. The method
applies recursive simulation technique on dispatching rules to search for new
improved solutions for a set of job shop problems. Due to the nature of the
recursive heuristic, performance criteria other than mean cycle time and
various dispatching rules can be implemented into the recursive simulation
framework without requiring too much effort. The performance of the proposed
approach is compared to the underlying dispatching rules as well as a
published tabu search procedure. The preliminary results show that the
approach outperforms the underlying dispatching rules and is comparable to the
tabu search procedure.
Wednesday 10:30:00 AM 12:00:00 PM
Tool Control
Chair: Olver
Rose (Dresden University of Technology)
Scheduling Cluster Tools Using Filtered Beam
Search and Recipe Comparison
Simon Oechsner (University of
Würzburg) and Oliver Rose (Technical University of Dresden)
Abstract:
Cluster tools have gained a lot of importance in
today’s semiconductor manufacturing. A cluster tool basically consists of
several processing chambers in a mainframe, several load locks to insert wafer
lots and a robot arm to move them. This means that these tools are able to
work on more than one lot at the same time. Since the lot combination
processed together can have an influence on the cycle times of these lots,
scheduling is needed to ensure that the overall cycle times are kept low. In a
previous work, we presented a method based on filtered beam search using
slowdown factors as evaluation methods. Here, we will present another
evaluation method based on recipe comparison that produces even better
results. We will also show results of a beam width parameter study.
Optimizing Robot Algorithms with
Simulation
Todd LeBaron (Brooks Automation) and Joerg Domasche
(Infineon Technologies AG)
Abstract:
Maximizing equipment throughput on multi-chambered
cluster tools is an ongoing objective for semiconductor fabs. The increasing
use of dual-armed robots and the need to process multiple products
simultaneously complicates this objective. Typically, when a new processing
technology is introduced, one chamber inside the tool is dedicated to the new
process, while the other chambers are assigned to run normal production
wafers. This results in multiple wafer flows or “parallel routes” within the
tool. Determining and implementing optimal robot schedulers to efficiently
handle the complexities within the tool is key to maximizing equipment
throughput. This paper introduces the components of a multi-chambered cluster
tool and dis-cusses how simulation was used at Infineon to develop, test, and
optimize efficient wafer selection rules. Several real-world cases are
detailed and reported.
An Analysis: Traditional Semiconductor Lithography
Versus Emerging Technology (Nano Imprint)
Walt Trybula (SEMATECH),
Robert Wright and Kranthi Mitra Adusumilli (International SEMATECH
Manufacturing Initiative) and Randy K Goodall (SEMATECH)
Abstract:
The introduction of emerging technologies into existing
manufacturing facilities is not necessarily encouraged by the people
responsible for the output of the facilities. Any “new” technology carries
risks and people responsible for delivering manufactured products are, by
nature, risk-adverse. This paper demonstrates the advantage of evaluating the
impact of attempting to introduce a new technology into an existing facility
before actually attempting the introduction. The first part of the analysis
examines the impact on the total product delivery for a comparable volume of
two facilities, one with the traditional processes and one with the new
process replacing existing ones. Based on these results, a conclusion can be
reached if there are sufficient benefits to consider pursuing the development
and introduction of the new techniques. An example is employed that evaluates
the introduction of nano-imprint.
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