A Methodology to Adapt and Understand a Manufacturing System and Operations using Discrete-Event Simulation
D. Phanindra Kshatra1, P. Ratna Prasad2, S. Akhil3, B.L.N.S.S. Charan Raghavendra4, S.V.S. Prakash5

1D.Phanindra Kshatra, Department of Mechanical Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Vijayawada, India,
2P.Ratna Prasad*, Department of Mechanical Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Vijayawada, India,
3S.Akhil, Department of Mechanical Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Vijayawada, India.
4B.L.N.S.S. Charan Raghavendra, Department of Mechanical Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Vijayawada, India.
5S.V.S. Prakash, Department of Mechanical Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Vijayawada, India.
Manuscript received on July 20, 2019. | Revised Manuscript received on August 10, 2019. | Manuscript published on August 30, 2019. | PP: 4998-5003 | Volume-8 Issue-6, August 2019. | Retrieval Number: F9206088619/2019©BEIESP | DOI: 10.35940/ijeat.F9206.088619
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Discrete-Event Simulation (DES) is concerned with system and modeling of that system, where the state of the system is transformed at different discrete points from time to time, and several event occurs from time to time and the changes in state variables will transform then activities/attributes connected to these state variables changes according to the event. It is a robust methodology in the manufacturing industry for strategic, tactical, and operational applications for an organization, and yet organizations ignore to use simulation and do not rely on it. Moreover, companies that are using DES are not using the potential benefits but merely used as a short-hand basis for problems like bottlenecks, optimization, and in later stages of production like PLM, this paper aims to apply and analyze Discrete-Event Simulation through a Manufacturing System. The work describes here is to understand the concept of simulation for a system and to practice Discrete Event methodology.
Keywords: Manufacturing System, Operations, Simulation, Discrete-Event Simulation, Computer Simulation, Discrete-Event Methodology, Dynamic Demand.