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Publication Open Access A model-based heuristic to the min max K-arc routing for connectivity problem(Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2014) Akbari, Vahid; Department of Industrial Engineering; Salman, Fatma Sibel; Faculty Member; Department of Industrial Engineering; College of Engineering; 178838We consider the post-disaster road clearing problem with the goal of restoring network connectivity in shortest time. Given a set of blocked edges in the road network, teams positioned at depot nodes are dispatched to open a subset of them that reconnects the network. After a team finishes working on an edge, others can traverse it. The problem is to find coordinated routes for the teams. We generate a feasible solution using a constructive heuristic algorithm after solving a relaxed mixed integer program. In almost 70 percent of the instances generated both randomly and from Istanbul data, the relaxation solution turned out to be feasible, i.e. optimal for the original problem.Publication Open Access A new identification method of specific cutting coefficients for ball end milling(Elsevier, 2014) Department of Mechanical Engineering; Khavidaki, Sayed Ehsan Layegh; Lazoğlu, İsmail; Faculty Member; Department of Mechanical Engineering; Manufacturing and Automation Research Center (MARC); Graduate School of Sciences and Engineering; College of Engineering; N/A; 179391The paper presents a new and accurate strategy for estimation of cutting coefficients for ball-end milling of free form surfaces in 3- and 5-axis operations. Since the cutting coefficients are not constant along the tool axis in the ball part of the cutter, the tool is considered by dividing the ball region into thin disks. In order to find the contribution of each disk to resultant cutting force, an experimental setup is designed to cut the workpiece while only that disk is in engaged with the workpiece. It is shown that this method is more efficient than common methods of mechanistic identification of cutting constants that are available in literature. The derivations are improved by considering the helix angle and cutting edge length to enhance the accuracy of the estimated cutting coefficients. Validation of the proposed strategy is demonstrated experimentally by simulation of cutting forces and comparing the results with conventional methods of identification of cutting coefficients that have been proposed in the literature. (C) 2014 Elsevier B.V.Publication Metadata only A novel analytical algorithm for prediction of workpiece temperature in end milling(Elsevier, 2022) N/A; Department of Mechanical Engineering; Akhtar, Waseem; Lazoğlu, İsmail; PhD Student; Faculty Member; Department of Mechanical Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 179391Temperature is a critical parameter in machining as it directly affects the cutting performance, part quality, residual stresses, distortion, tool life, etc. In this article, a novel analytical algorithm for fast temperature predic-tion in intermittent cutting processes like milling is proposed. For the first time, the temperature drop during the noncutting period is taken into consideration for the workpiece side. The model also takes into account time-varying chip thickness due to the trochoidal motion of the milling tool. Validation tests with Ti6Al4V showed the promise of the algorithm in predicting the milling temperature under various cutting conditions.(c) 2022 CIRP. Published by Elsevier Ltd. All rights reserved.Publication Metadata only Active damping of chatter in the boring process via variable gain sliding mode control of a magnetorheological damper(Elsevier, 2021) N/A; N/A; Department of Mechanical Engineering; Saleh, Mostafa Khalil Abdou; Ulasyar, Abasin; Lazoğlu, İsmail; PhD Student; Researcher; Faculty Member; Department of Mechanical Engineering; Manufacturing and Automation Research Center (MARC); Graduate School of Sciences and Engineering; N/A; College of Engineering; N/A; N/A; 179391In this article, a sliding mode control of a magnetorheological fluid damper is presented for active damping of chatter in the boring process for the first time. A boring bar is integrated with an in-house developed magnetorheological fluid damper system. The variable gain super twisting sliding mode control algorithm is designed and implemented for suppressing the chatter in the boring process. Simulations of the controller show its fast response and robustness against disturbances and parametric uncertainties. Validation cutting tests performed under various machining conditions showed that the stability limit can be increased significantly with the sliding mode control of the magnetorheological fluid damper.Publication Metadata only An enhanced analytical model for residual stress prediction in machining(Elsevier, 2008) Ulutan, D.; Engin, S.; Kaftanoglu, B.; Department of Mechanical Engineering; Department of Mechanical Engineering; Lazoğlu, İsmail; Alaca, Burhanettin Erdem; Faculty Member; Faculty Member; Department of Mechanical Engineering; College of Engineering; College of Engineering; 179391; 115108The predictions of residual stresses are most critical on the machined aerospace components for the safety of the aircraft. In this paper, an enhanced analytic elasto-plastic model is presented using the superposition of thermal and mechanical stresses on the workpiece, followed by a relaxation procedure. Theoretical residual stress predictions are verified experimentally with X-ray diffraction measurements on the high strength engineering material of Waspaloy that is used critical parts such as in aircraft jet engines. With the enhanced analytical model, accurate residual stress results are achieved, while the computational time compared to equivalent FEM models is decreased from days to secends.Publication Metadata only Contributions to stochastic models of manufacturing and service operations(Taylor & Francis, 2018) Liberopoulos, George; Heavey, Cathal; Helber, Stefan; Matta, Andrea; Department of Industrial Engineering; Karaesmen, Fikri; Faculty Member; Department of Industrial Engineering; College of Engineering; 3579N/APublication Metadata only Dynamic pricing of durable products with heterogeneous customers and demand interactions over time(Pergamon-Elsevier Science Ltd, 2013) N/A; Department of Industrial Engineering; Kaya, Onur; Faculty Member; Department of Industrial Engineering; College of Engineering; 28405In this study, we analyze a dynamic pricing problem in which the demand is interdependent over time and the customers are heterogeneous in their purchasing decisions. The customers are grouped into different classes depending on their purchase probabilities and the customer classes evolve over time depending on the demand realizations at every period, which are a function of the prices set by the company. To decide on the optimal prices at every period, we model this problem using a stochastic dynamic program (SDP) and we develop several approximation algorithms to solve this SDP since the size of the state space of the SDP makes the optimal solution almost impossible to find. We present the efficiencies of the heuristics and provide managerial insights through a computational study in which we compare the revenues obtained with each heuristic with an upper bound value that we find on the optimal revenues.Publication Metadata only Improving cycle time in sculptured surface machining through force modeling(Elsevier, 2004) Budak, E.; Department of Mechanical Engineering; N/A; Lazoğlu, İsmail; Güzel, Birhan Ufku; Faculty Member; Master Student; Department of Mechanical Engineering; College of Engineering; Graduate School of Sciences and Engineering; 179391; N/AIn this paper, an enhanced mathematical model is presented for the prediction of cutting force system in ball end milling of sculptured surfaces. This force model is also used as the basis for off-line feed rate scheduling along the tool path in order to decrease the cycle time in sculptured surface machining. As an alternative for setting a constant feed rate all along the tool path in rough machining of sculptured surfaces, resultant cutting forces are aimed to be kept under a pre-set threshold value along the tool path by off-line scheduled piecewise variable feed rates. In this paper, it is shown that machining time, depending on complexity of sculptured surfaces, can be decreased significantly by scheduling feed rate along the tool path. The model is tested under various cutting conditions and some of the results are also presented and discussed in the paper.Publication Open Access Integrating gene set analysis and nonlinear predictive modeling of disease phenotypes using a Bayesian multitask formulation(BioMed Central, 2016) Department of Industrial Engineering; Gönen, Mehmet; Faculty Member; Department of Industrial Engineering; College of Engineering; 237468Identifying molecular signatures of disease phenotypes is studied using two mainstream approaches: (i) Predictive modeling methods such as linear classification and regression algorithms are used to find signatures predictive of phenotypes from genomic data, which may not be robust due to limited sample size or highly correlated nature of genomic data. (ii) Gene set analysis methods are used to find gene sets on which phenotypes are linearly dependent by bringing prior biological knowledge into the analysis, which may not capture more complex nonlinear dependencies. Thus, formulating an integrated model of gene set analysis and nonlinear predictive modeling is of great practical importance. In this study, we propose a Bayesian binary classification framework to integrate gene set analysis and nonlinear predictive modeling. We then generalize this formulation to multitask learning setting to model multiple related datasets conjointly. Our main novelty is the probabilistic nonlinear formulation that enables us to robustly capture nonlinear dependencies between genomic data and phenotype even with small sample sizes. We demonstrate the performance of our algorithms using repeated random subsampling validation experiments on two cancer and two tuberculosis datasets by predicting important disease phenotypes from genome-wide gene expression data. We are able to obtain comparable or even better predictive performance than a baseline Bayesian nonlinear algorithm and to identify sparse sets of relevant genes and gene sets on all datasets. We also show that our multitask learning formulation enables us to further improve the generalization performance and to better understand biological processes behind disease phenotypes.Publication Open Access Machining forces and tool deflections in micro milling(Elsevier, 2013) Department of Mechanical Engineering; Mamedov, Ali; Khavidaki, Sayed Ehsan Layegh; Lazoğlu, İsmail; Researcher; Faculty Member; Department of Mechanical Engineering; Manufacturing and Automation Research Center (MARC); Graduate School of Sciences and Engineering; College of Engineering; N/A; N/A; 179391The analysis of cutting forces plays an important role for investigation of mechanics and dynamics of cutting process. The importance of force analysis is due to its major role in surface quality of machined parts. Presented force model calculates instantaneous chip thickness by considering trajectory of the tool tip while tool rotates and moves ahead continuously. The model also takes plowing force component into consideration relating it to elastic recovery based on interference volume between tool and workpiece. Based on the mathematical model, distribution of the force acting on the tool is calculated. It is known that this force will create deflection of the tool during cutting, which will result in imperfections of the final part. From this point of view, it is important to predict tool deflections in order to control the cutting process and to avoid failure of the tool. Both force and deflection models are validated on Aerospace Aluminum Alloy (Al-7050), through micro end milling experiments for a wide range of cutting conditions using micro dynamometer and laser displacement sensors. (C) 2013 The Authors. Published by Elsevier B.V.