Browsing by Subject "Design of experiments"
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Item Open Access Accounting for parameter uncertainty in large-scale stochastic simulations with correlated inputs(Institute for Operations Research and the Management Sciences (I N F O R M S), 2011) Biller, B.; Corlu, C. G.This paper considers large-scale stochastic simulations with correlated inputs having normal-to-anything (NORTA) distributions with arbitrary continuous marginal distributions. Examples of correlated inputs include processing times of workpieces across several workcenters in manufacturing facilities and product demands and exchange rates in global supply chains. Our goal is to obtain mean performance measures and confidence intervals for simulations with such correlated inputs by accounting for the uncertainty around the NORTA distribution parameters estimated from finite historical input data. This type of uncertainty is known as the parameter uncertainty in the discrete-event stochastic simulation literature. We demonstrate how to capture parameter uncertainty with a Bayesian model that uses Sklar's marginal-copula representation and Cooke's copula-vine specification for sampling the parameters of the NORTA distribution. The development of such a Bayesian model well suited for handling many correlated inputs is the primary contribution of this paper. We incorporate the Bayesian model into the simulation replication algorithm for the joint representation of stochastic uncertainty and parameter uncertainty in the mean performance estimate and the confidence interval. We show that our model improves both the consistency of the mean line-item fill-rate estimates and the coverage of the confidence intervals in multiproduct inventory simulations with correlated demands.Item Open Access A design of experiments approach to military deployment planning problem(IEEE, 2008) Yıldırım, Uğur Z.; Sabuncuoğlu, İhsan; Tansel, Barbaros; Balcıoğlu, A.We develop a logistics and transportation simulation that can be used to provide insights into potential outcomes of proposed military deployment plans.More specifically, we model the large-scale real-world military Deployment Planning Problem.It involves planning the movement of military units from their home bases to their final destinations using different transportation assets on a multimodal transportation network. We use an intelligent design of experiments approach to evaluate logistics factors with the greatest impact on the overall achievement of a typical real-world military deployment plan.Item Open Access Experimental and finite element analysis of EDM process and investigation of material removal rate by response surface methodology(2013) Hosseini Kalajahi, M.; Rash Ahmadi, S.; Nadimi Bavil Oliaei, S.In this study, thermal modeling and finite element simulation of electrical discharge machining (EDM) has been done, taking into account several important aspects such as temperature-dependent material properties, shape and size of the heated zone (Gaussian heat distribution), energy distribution factor, plasma flushing efficiency, and phase change to predict thermal behavior and material removal mechanism in EDM process. Temperature distribution on the cathode has been calculated using ANSYS finite element code, and the effect of EDM parameters on heat distribution along the radius and depth of the workpiece has been obtained. Temperature profiles have been used to calculate theoretical material removal rate (MRR) from the cathode. Theoretically calculated MRRs are compared with the experimental results, making it possible to precisely determine the portion of energy that enters the cathode for AISI H13 tool steel. Also in this paper, the effect of EDM parameters on MRR has been investigated by using the technique of design of experiments and response surface methodology. Finally, a quadratic polynomial regression model has been proposed for MRR, and the accuracy of this model has been checked by means of analysis of residuals. © 2013 Springer-Verlag London.Item Open Access Modeling and optimization of multi-scale machining operations(Bilkent University, 2012) Yılmaz, FevziMinimization of production time, cost and energy while improving the part quality is the main goal in manufacturing. In order to be competitive in today’s global markets, it is crucial to develop high precision machine tools and maintain high productive operation of the machine tools through intelligent and effective selection of machining parameters. A recent shift in manufacturing industry is towards the production of high value added micro parts which are mainly used in biomedical and electronics industries. However, the knowledge base for micro machining operations is quite limited compared to macro scale machining processes. Metal cutting, which allows production of parts with complex shapes made from engineering materials, constitutes a large portion in all manufacturing activities and expected to remain so in upcoming years. In this thesis, modeling and optimization of macro scale turning and micro scale milling operations have been considered. A well known multi pass turning problem from the literature is used as a benchmark tool to test the performances of Particle Swarm Optimization (PSO) technique and nonlinear optimization algorithms. It is shown that acceptable results can be obtained through PSO in short time. Micro scale milling operation is thoroughly investigated through experimental techniques where the influences of machining parameters on the process outputs (machining forces, surface quality, and tool life) have been investigated and factors affecting the process outputs are identified. A minimum unit cost optimization problem is formulated based on the pocketing operation and machining strategies are proposed for different machining scenarios using PSO technique.