A Case Study in Scheduling Reentrant Manufacturing Lines: Optimal and Simulation-Based Approaches

2006 ◽  
Author(s):  
J.A. Ramirez-Hernandez ◽  
E. Fernandez
Keyword(s):  
Simulation Based ◽  
Reentrant Manufacturing

Dynamic Simulation-Based Case Study of Fusion on Small-Scale Electrical Grids

2015 ◽  
Vol 68 (2) ◽  
pp. 341-345 ◽  
Author(s):  
Shutaro Takeda ◽  
Satoshi Konishi ◽  
Yasushi Yamamoto ◽  
Ryuta Kasada ◽  
Shigeki Sakurai
Keyword(s):  
Dynamic Simulation ◽  
Small Scale ◽  
Electrical Grids ◽  
Simulation Based

Reliability-Based Analysis and Optimization of the Gravity Balancing Performance of Spring-Articulated Serial Robots with Uncertainties

2021 ◽  
pp. 1-32
Author(s):  
Vu Linh Nguyen ◽  
Chin-Hsing Kuo ◽  
Po Ting Lin
Keyword(s):  
Pso Algorithm ◽  
Reliability Based Design Optimization ◽  
Swarm Optimization ◽  
Reliability Based Design ◽  
Serial Robots ◽  
Simulation Based ◽  
Serial Robot ◽  
Simulation Results ◽  
Uncertainty Level

Abstract This article proposes a method for analyzing the gravity balancing reliability of spring-articulated serial robots with uncertainties. Gravity balancing reliability is defined as the probability that the torque reduction ratio (the ratio of the balanced torque to the unbalanced torque) is less than a specified threshold. The reliability analysis is performed by exploiting a Monte Carlo simulation (MCS) with consideration of the uncertainties in the link dimensions, masses, and compliance parameters. The gravity balancing begins with a simulation-based analysis of the gravitational torques of a typical serial robot. Based on the simulation results, a gravity balancing design for the robot using mechanical springs is realized. A reliability-based design optimization (RBDO) method is also developed to seek a reliable and robust design for maximized balancing performance under a prescribed uncertainty level. The RBDO is formulated with consideration of a probabilistic reliability constraint and solved by using a particle swarm optimization (PSO) algorithm. A numerical example is provided to illustrate the gravity balancing performance and reliability of a robot with uncertainties. A sensitivity analysis of the balancing design is also performed. Lastly, the effectiveness of the RBDO method is demonstrated through a case study in which the balancing performance and reliability of a robot with uncertainties are improved with the proposed method.

Design and Validation of a Simulation-Based Modular Planning and Scheduling System of Semiconductor Fabrication Facilities

2011 ◽  
Vol 48-49 ◽  
pp. 378-381
Author(s):  
Li Li ◽  
Fei Qiao
Keyword(s):  
Simulation Modeling ◽  
General Structure ◽  
Structure Model ◽  
Planning And Scheduling ◽  
Scheduling System ◽  
Information Layer ◽  
Simulation Based ◽  
Semiconductor Fabrication ◽  
Control Modules

A simulation-based modular planning and scheduling system developed for semiconductor fabrication facilities (SFFs) is discussed. Firstly, the general structure model (GSM) for SFFs, composed of a configurable definition layer, a physical layer, a process information layer and a planning and scheduling layer, is proposed. Secondly, a data-based dynamic simulation modeling method is given. Thirdly, a simulation-based modular planning and scheduling system (SMPSS) for SFFs, including model modules, release control modules, scheduling modules and rescheduling modules, is designed and developed. Finally, a case study is used to demonstrate the effectiveness of

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