Author(s):
1. Miloš Madić, Serbia
2. Marko Kovačević, Faculty of Engineering, Niš, Serbia
3. Miroslav Radovanović, Faculty of Mechanical Engineering in Niš, Serbia
4. Dušan Petković, Faculty of Mechanical Engineering in Niš, Serbia

Abstract:
Optimization of machining parameters is of prime importance for increasing machining efficiency and economics. Among traditional optimization methods, in recent years, modern meta-heuristic algorithms are being increasingly applied for solving machining optimization problems. The aim of this paper is to investigate possibilities of discrete Monte Carlo (MC) method for solving machining optimization problems which were solved by the past researchers using meta-heuristic algorithms. To analyze the applicability and performance of discrete MC method, two case studies of machining optimization problems, were considered. Although MC method is stochastic in nature, while solving machining optimization problems it has been demonstrated that probability of finding optimal value over 99.99% is achieved within few seconds. Specific features and merits of discrete MC method were also discussed.

Key words:
machining,optimization,discrete Monte Carlo method

Date of abstract submission:
04.05.2015.

Conference:
12th International conference on accomplishments in Electrical and Mechanical Engineering and Information Technology (DEMI 2015)

Final paper