Open AccessMarkov Process in Varying Value in Production by Machinery with Two Components
Author(s) -
C. Mohan,
P. Selvaraju,
S. Shanmugan
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.j9504.0881019
Subject(s) - production (economics) , component (thermodynamics) , work (physics) , process (computing) , reliability engineering , computer science , markov process , production rate , markov chain , operations management , risk analysis (engineering) , manufacturing engineering , engineering , business , economics , microeconomics , mathematics , mechanical engineering , statistics , physics , thermodynamics , operating system , machine learning
Additive manufacturing is finding increasing applications in industries ranging from electronics to aerospace and even medical sectors. However, these machines are very expensive which hinders researcher investigations. Thus it is important to have an alternative data source for such machines. A probable solution is to develop a simulator to replicate such machine based on same input parameters and thus obtain results similar to that from an actual machine. This would help developers and researchers investigate several aspects of additive manufacturing without using the actual machine. This paper reports an investigation conducted to study the behavior of a selective laser melting machine under different scenarios. Influences due to components such as vacuum pump, reciprocating pump, gas inlet valve, vent valve, elevator and wiper have been included. Experimental result data has been used to build codes in C# software to program the PLC simulator. Validation experiments confirmed simulation output. The present work helps the end user to inspect real time simulations such as vacuum creation, inert gas atmosphere progression. Thus, simulation results offer time and resource savings to an additive manufacturing end user by him/her make informed decisions by supplying exact parameter settings suitable to his/her manufacturing requirements.