Re-enactment simulation for buffer size optimization in semiconductor back-end production

2018 ◽  
Author(s):  
Jelle Adan ◽  
Stephan Sneijders ◽  
Alp Akcay ◽  
Ivo J.B.F. Adan
Keyword(s):  
Buffer Size ◽  
Size Optimization

scholarly journals Continuous process improvement implementation framework using multi-objective genetic algorithms and discrete event simulation

2019 ◽  
Vol 25 (5) ◽  
pp. 1020-1039 ◽  
Author(s):  
Parminder Singh Kang ◽  
Rajbir Singh Bhatti
Keyword(s):  
Discrete Event Simulation ◽  
Process Improvement ◽  
Continuous Process ◽  
Discrete Event ◽  
Buffer Size ◽  
Size Optimization ◽  
Continuous Process Improvement ◽  
Content Type ◽  
Event Simulation ◽  
Job Sequencing

Purpose Continuous process improvement is a hard problem, especially in high variety/low volume environments due to the complex interrelationships between processes. The purpose of this paper is to address the process improvement issues by simultaneously investigating the job sequencing and buffer size optimization problems. Design/methodology/approach This paper proposes a continuous process improvement implementation framework using a modified genetic algorithm (GA) and discrete event simulation to achieve multi-objective optimization. The proposed combinatorial optimization module combines the problem of job sequencing and buffer size optimization under a generic process improvement framework, where lead time and total inventory holding cost are used as two combinatorial optimization objectives. The proposed approach uses the discrete event simulation to mimic the manufacturing environment, the constraints imposed by the real environment and the different levels of variability associated with the resources. Findings Compared to existing evolutionary algorithm-based methods, the proposed framework considers the interrelationship between succeeding and preceding processes and the variability induced by both job sequence and buffer size problems on each other. A computational analysis shows significant improvement by applying the proposed framework. Originality/value Significant body of work exists in the area of continuous process improvement, discrete event simulation and GAs, a little work has been found where GAs and discrete event simulation are used together to implement continuous process improvement as an iterative approach. Also, a modified GA simultaneously addresses the job sequencing and buffer size optimization problems by considering the interrelationships and the effect of variability due to both on each other.

Spotting Differences in Molecular Dynamic Simulations of Influenza A M2 Protein-Ligand Complexes by Varying M2 construct, Lipid Bilayer and Force Field

2019 ◽  
Author(s):  
Dimitrios Kolokouris ◽  
Iris Kalenderoglou ◽  
Panagiotis Lagarias ◽  
Antonios Kolocouris
Keyword(s):  
Molecular Dynamic ◽  
Lipid Bilayer ◽  
Influenza A ◽  
Md Simulations ◽  
Membrane Curvature ◽  
Buffer Size ◽  
M2 Protein ◽  
Dynamic Simulations ◽  
Amphipathic Helices ◽  
Drug Protein Binding

<p>We studied by molecular dynamic (MD) simulations systems including the inward<sub>closed</sub> state of influenza A M2 protein in complex with aminoadamantane drugs in membrane bilayers. We varied the M2 construct and performed MD simulations in M2TM or M2TM with amphipathic helices (M2AH). We also varied the lipid bilayer by changing either the lipid, DMPC or POPC, POPE or POPC/cholesterol (chol), or the lipids buffer size, 10x10 Å<sup>2 </sup>or 20x20 Å<sup>2</sup>. We aimed to suggest optimal system conditions for the computational description of this ion channel and related systems. Measures performed include quantities that are available experimentally and include: (a) the position of ligand, waters and chlorine anion inside the M2 pore, (b) the passage of waters from the outward Val27 gate of M2 S31N in complex with an aminoadamantane-aryl head blocker, (c) M2 orientation, (d) the AHs conformation and structure which is affected from interactions with lipids and chol and is important for membrane curvature and virus budding. In several cases we tested OPLS2005, which is routinely applied to describe drug-protein binding, and CHARMM36 which describes reliably protein conformation. We found that for the description of the ligands position inside the M2 pore, a 10x10 Å<sup>2</sup> lipids buffer in DMPC is needed when M2TM is used but 20x20 Å<sup>2</sup> lipids buffer of the softer POPC; when M2AH is used all 10x10 Å<sup>2</sup> lipid buffers with any of the tested lipids can be used. For the passage of waters at least M2AH with a 10x10 Å<sup>2</sup> lipid buffer is needed. The folding conformation of AHs which is defined from hydrogen bonding interactions with the bilayer and the complex with chol is described well with a 10x10 Å<sup>2</sup> lipids buffer and CHARMM36. </p>

Flow Simulation and Size Optimization of Centrifugal Impeller

2013 ◽  
Vol 3 (1) ◽  
pp. 1-8
Author(s):  
Wesam Dawood Salman Al-rubia ◽  
◽  
S. Pavithran ◽  
Keyword(s):  
Flow Simulation ◽  
Centrifugal Impeller ◽  
Size Optimization

scholarly journals Fuzzy-Based Quality Adaptation Algorithm for Improving QoE from MPEG-DASH Video

2021 ◽  
Vol 11 (11) ◽  
pp. 5270
Author(s):  
Waqas ur Rahman ◽  
Md Delowar Hossain ◽  
Eui-Nam Huh
Keyword(s):  
State Of The Art ◽  
Video Quality ◽  
Buffer Size ◽  
Bandwidth Utilization ◽  
Adaptation Algorithm ◽  
Control Laws ◽  
Quality Video ◽  
Video Player ◽  
High Quality Video ◽  
Abr Algorithm

Video clients employ HTTP-based adaptive bitrate (ABR) algorithms to optimize users’ quality of experience (QoE). ABR algorithms adopt video quality based on the network conditions during playback. The existing state-of-the-art ABR algorithms ignore the fact that video streaming services deploy segment durations differently in different services, and HTTP clients offer distinct buffer sizes. The existing ABR algorithms use fixed control laws and are designed with predefined client/server settings. As a result, adaptation algorithms fail to achieve optimal performance across a variety of video client settings and QoE objectives. We propose a buffer- and segment-aware fuzzy-based ABR algorithm that selects video rates for future video segments based on segment duration and the client’s buffer size in addition to throughput and playback buffer level. We demonstrate that the proposed algorithm guarantees high QoE across various video player settings and video content characteristics. The proposed algorithm efficiently utilizes bandwidth in order to download high-quality video segments and to guarantee high QoE. The results from our experiments reveal that the proposed adaptation algorithm outperforms state-of-the-art algorithms, providing improvements in average video rate, QoE, and bandwidth utilization, respectively, of 5% to 18%, about 13% to 30%, and up to 45%.

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