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Simulation and Evaluation of the Mattress Manufacturing Process Design Model

by Duc Hoang Nguyen
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 184 - Number 36
Year of Publication: 2022
Authors: Duc Hoang Nguyen
10.5120/ijca2022922454

Duc Hoang Nguyen . Simulation and Evaluation of the Mattress Manufacturing Process Design Model. International Journal of Computer Applications. 184, 36 ( Nov 2022), 16-21. DOI=10.5120/ijca2022922454

@article{ 10.5120/ijca2022922454,
author = { Duc Hoang Nguyen },
title = { Simulation and Evaluation of the Mattress Manufacturing Process Design Model },
journal = { International Journal of Computer Applications },
issue_date = { Nov 2022 },
volume = { 184 },
number = { 36 },
month = { Nov },
year = { 2022 },
issn = { 0975-8887 },
pages = { 16-21 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume184/number36/32548-2022922454/ },
doi = { 10.5120/ijca2022922454 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:23:17.551770+05:30
%A Duc Hoang Nguyen
%T Simulation and Evaluation of the Mattress Manufacturing Process Design Model
%J International Journal of Computer Applications
%@ 0975-8887
%V 184
%N 36
%P 16-21
%D 2022
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, the design model of the mattress manufacturing process will be simulated and evaluated using Tecnomatix Plant Simulation software.Various SKU distribution control scenarios are tested to determine line balance.In addition, the sensitivity analysis of design parameters such as conveyor speed, lifter speed, as well as SKU loading time, etc. affecting the line balance was also examined. The simulation results showed that the Tecnomatix Plant Simulation software could beeffectively used for achievingoptimal parameters of the design systemas well as the SKU distribution control scheme.

References
  1. Jeffrey S. Smith. 2003. Survey on the use of simulation for manufacturing system design and operation. Journal of Manufacturing Systems, 22 (2), pp. 157-171.
  2. J Stoldt, A Schlegel, and M Putz. 2016. Enhanced integration of energy-related considerations in discrete event simulation for manufacturing applications. Journal of Simulation, 10:2, 113-122.
  3. https://www.plm.automation.siemens.com/global/en/products/manufacturing-planning/plant-simulation-throughput-optimization.html.
  4. Bangsow S. 2010. Manufacturing Simulation with Plant Simulation and SimTalk, Usage and Programming with Examples and Solutions. Springer.
  5. Zupan, H., Herakovic, N. 2015. Production line balancing with discrete event simulation: A case study. IFAC-PapersOnLine 48-3, 2305-2311.
  6. AndorBálintViharos and IstvánNémeth. 2018. Simulation and scheduling of AGV based robotic assembly systems. IFAC-PapersOnLine 51-11, 1415-1420.
  7. Ananya Chayaphum, SrisawatSupsomboon and Anan Butrat. 2019. The Optimal Number of Reach Trucks and Order Picker Trucks in Warehouse Determining Using Simulation. Research, Invention, and Innovation Congress, IEEE Xplore.
  8. Yongbing Feng and Guohua Gao. 2019. Design and Simulation Study on Logistics Planning in Automatic Plant Factory Based on Tecnomatix Plant Simulation. 2nd World Conference on Mechanical Engineering and Intelligent Manufacturing (WCMEIM), IEEE Xplore.
  9. Irina Makarova, Polina Buyvol and LarysaGubacheva. 2020. Creation of a Digital Twin of a Truck Assembly Process. International Russian Automation Conference, IEEE Xplore.
Index Terms

Computer Science
Information Sciences

Keywords

Discrete event simulation modelling production operations.

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