Comparing designs for computer simulation experiments

Johnson, _______; Jones, Jones; Fowler, Marsha; Montgomery,

doi:10.1109/wsc.2008.4736101

Cited by 15 publications

(14 citation statements)

References 21 publications

(22 reference statements)

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“…A special kind of substitution is meta-modeling, where the input-output behavior of the whole simulation model is approximated by an analytical model [25]-note that the transition between aggregation and substitution is quite smooth with the latter being the result of repeated aggregation. [26] for instance propose a framework that incorporates substitution and aggregation strategies (e. g. generation of processing times based on triangular probability distribution) that performed very well in several test cases with regard to accuracy and simulation runtime.…”

Section: Literature On Correct Level Of Complexitymentioning

confidence: 99%

The correct level of model complexity in semiconductor fab simulation — Lessons learned from practice

Rank

Hammel

Schmidt

et al. 2016

2016 27th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC)

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It is well-known that semiconductor manufacturing is one of the most complex types of production. Consequently, making the right decisions in order to get the optimum output of a semiconductor fab is quite challenging. For that reason, sophisticated discrete event simulation studies may be seen as a kind of magic tool for fab managers to face the ever-increasing complexity. But building complex dynamic simulation models in order to solve complex problems is not always the best solution. This article gives an overview of the discussion about the correct level of complexity of discrete event simulation models and lists the main reasons for the creation of overcomplex models. To provide guidance for practitioners, lessons learned are derived from four "real world" use cases in which the correct level of complexity was a major issue.

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Section: Literature On Correct Level Of Complexitymentioning

confidence: 99%

The correct level of model complexity in semiconductor fab simulation — Lessons learned from practice

Rank

Hammel

Schmidt

et al. 2016

2016 27th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC)

View full text Add to dashboard Cite

show abstract

“…Thus, one has to make compromise between the accuracy of the model and the efficiency in calculation, since an accurate model may need a larger sample size which results in longer time to compute. In general, using surrogate models requires additional computer simulation experiments to verify the results and performing physical experiments to validate the model and the optimized solutions (Johnson et al, 2008). Surrogate modeling approaches for the simulation-based experiments generally involve four steps:…”

Section: Designmentioning

confidence: 99%

Hydrodynamic Analysis and Optimization of a Hinged Type Wave Energy Converter

Peng

Qiu

et al. 2016

Volume 6: Ocean Space Utilization; Ocean Renewable Energy

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SeaWEED(Sea Wave Energy Extraction Device) is a multi-body floating wave energy converter (WEC) with hinged joints developed by Grey Island Energy Inc.(GIE) in Canada. Initial conceptual studies have been carried out to evaluate the performance of the first generation device by testing an 1:16 scale model in a wave basin. The experimental results were compared with the numerical solutions. Based on the experimental studies, improvements were made and a second generation model with a new geometry of the hull and a new connection structure was developed. This thesis is mainly focused on the numerical analysis and optimization of the second generation SeaWEED model. In the numerical studies, the hydraulic power take-off (PTO) system was simulated by a linear spring damper system coupled with the motion of the hinged bodies. The vertical hinge motion was computed at a series of wave periods using WAMIT. Optimization was focused on the PTO damping and the geometrical parameters in terms of the draft and the length of the truss structure between hinged bodies by using the response surface method. The optimization was conducted in regular waves and in irregular sea states. An optimal combination of length, draft and PTO damping was recommended for an intended operation location. Thanks to all the other colleagues in our group; we studied together, worked together; and I am glad to see that we all made big progress during the study in the Advanced Marine Hydrodynamics Laboratory.

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“…In the literature, there exist numerous statistical methods for conducting computer experiments, some of which obeying a design optimisation criteria (Santner et al, 2003;Chen et al, 2006;Johnson et al, 2008).…”

Section: Design Of Computer Experimentsmentioning

confidence: 99%

A Metamodel Simulation Based Optimisation Approach for the Tidal Turbine Location Problem

Eisenmann¹,

Qassim

Rosman

2014

AST

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A metamodel simulation based optimisation approach for the tidal turbine location problem is introduced. The method comprises design of experiments, computational simulations, metamodel construction and formulation of a mathematical optimisation model. Sample plans with different number of data points are used to fit 2nd and 3rd order polynomial as a function of two design parameters: longitudinal and lateral spacing, with a view to approximating the power output of tidal turbine farms with inline and staggered layouts, each Aquatic Science and Technology ISSN 2168-9148 2015 of them with a fixed number of turbines. The major advantage this method has, in comparison to those reported in the literature, is the capability to analyse different design parameter combinations that satisfy optimality criteria in reasonable computational time, while taking into account complex flow-turbine interactions.

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Comparing designs for computer simulation experiments

Cited by 15 publications

References 21 publications

The correct level of model complexity in semiconductor fab simulation — Lessons learned from practice

The correct level of model complexity in semiconductor fab simulation — Lessons learned from practice

Hydrodynamic Analysis and Optimization of a Hinged Type Wave Energy Converter

A Metamodel Simulation Based Optimisation Approach for the Tidal Turbine Location Problem

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