Endüstri Mühendisliği Bölümü / Department of Industrial Engineering

Permanent URI for this collectionhttps://hdl.handle.net/11413/6819

Browse

Now showing 1 - 3 of 3

Metadata only
An integrated approach to the one-dimensional cutting stock problem in coronary stent manufacturing
(Elsevier Science Bv, Po Box 211, 1000 Ae Amsterdam, Netherlands, 2009-07-16) Özdemir, Rifat Gürcan; AKTİN, AYŞE TÜLİN; TR109203; TR141173
This paper presents a two-stage approach for pattern generation and cutting plan determination of the one-dimensional cutting stock problem. Calculation of the total number of patterns that will be cut and generation of the cutting patterns are performed in the first stage. On the other hand, the second stage determines the cutting plan. The proposed approach makes use of two separate integer linear programming models. One of these models is employed by the first stage to generate the cutting patterns through a heuristic procedure with the objective of minimizing trim loss. The cutting patterns obtained from Stage I are then fed into the second stage. In this stage, another integer linear programming model is solved to form a cutting plan. The objective of this model is to minimize a generalized total cost function consisting of material inputs, number of setups, labor hours and overdue time: subject to demand requirements, material availability, regular and overtime availability, and due date constraints. The study also demonstrates an implementation of the proposed approach in a coronary stent manufacturer. The case study focuses on the cutting phase of the manufacturing process followed by manual cleaning and quality control activities. The experiments show that the proposed approach is suitable to the conditions and requirements of the company. (C) 2008 Elsevier B.V. All rights reserved.
Metadata only
Evaluating Machine Tool Alternatives Through Modified TOPSIS And Alpha-Cut Based Fuzzy ANP
(Elsevier Science Bv, Po Box 211, 1000 Ae Amsterdam, Netherlands, 2012-12) Ayağ, Zeki; Özdemir, Rifat Gürcan; TR8785; TR141173
The problem of machine tool selection among available alternatives has been critical issue for most companies in fast-growing markets for a long time. In the presence of many alternatives and selection criteria, the problem becomes a multiple-criteria decision making (MCDM) machine tool selection problem. Therefore, most companies have utilized various methods to successfully carry out this difficult and time-consuming process. In this work, both of the most used MCDM methods, the modified TOPSIS and the Analytical Network Process (ANP) are introduced to present a performance analysis on machine tool selection problem. The ANP method is used to determine the relative weights of a set of the evaluation criteria, as the modified TOPSIS method is utilized to rank competing machine tool alternatives in terms of their overall performance. Furthermore, in this paper, we use a fuzzy extension of ANP, a more general form of AHP, which uses uncertain human preferences as input information in the decision-making process, because AHP cannot accommodate the variety of interactions, dependencies and feedback between higher and lower level elements. Instead of using the classical eigenvector prioritization method in AHP, only employed in the prioritization stage of ANP, a fuzzy logic method providing more accuracy on judgments is applied. The resulting fuzzy ANP enhances the potential of the conventional ANP for dealing with imprecise and uncertain human comparison judgments. The proposed approach is also applied for a real-life case in a company. (C) 2012 Elsevier B.V. All rights reserved.
Metadata only
T-Copula Generation For Control Variates
(Elsevier Science Bv, Po Box 211, 1000 Ae Amsterdam, Netherlands, 2010-12) Hormann, Wolfgang; Sak, Halis
The standard method for generating multi-t vectors is simple and convenient but it has the disadvantage that the generated multi-normal and multi-t vectors are not similar. For t-copula models this destroys much of the variance reduction when using the result of the multi-normal model as external control variate. Therefore we develop a new generation method for multi-t vectors. It is based on the polar method and numerical inversion, and generates multi-normal and multi-t vectors that are very similar. Numerical experiments with simple functions of the weighted sum of t-copula vectors and with pricing European basket options with a t-copula model confirm that the obtained variance reduction factors of the new method are high; 2-100 times higher than when using the standard generation method. (C) 2010 IMACS. Published by Elsevier B.V. All rights reserved.

Browse

Browsing Endüstri Mühendisliği Bölümü / Department of Industrial Engineering by Publisher "Elsevier Science Bv, Po Box 211, 1000 Ae Amsterdam, Netherlands"