Yazar "Ozcan, Ugur" seçeneğine göre listele

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    Balancing and sequencing mixed-model just-in-time U-lines with multiple objectives
    (ELSEVIER SCIENCE INC, 2007) Kara, Yakup; Ozcan, Ugur; Peker, Ahmet
    This study deals with the mixed-model U-lines utilized in just-in-time (JIT) production systems. Successful implementations of mixed-model U-lines requires solutions to two important problems called line balancing and model sequencing. In terms of some balance-dependent performance measures the effectiveness of a mixed-model U-line can be increased by solving line balancing and model sequencing problems simultaneously. However, this may lead to inefficient values of sequence-dependent performance measures. Hence, increasing the effectiveness of a mixed-model U-line requires balancing and sequencing problems that be dealt with multiple objectives. Balancing and sequencing mixed-model U-lines with multiple objectives has not been considered in the literature to date. In this study, a multi-objective approach for balancing and sequencing mixed-model U-lines to simultaneously minimize the absolute deviations of workloads across workstations, part usage rate, and cost of setups is presented. To increase the performance of the proposed algorithm, a newly developed neighbourhood generation method is also employed. Since the performance measures considered in the study are conflicting with each other, the proposed algorithm suggests much flexibility and more realistic results to decision makers. Solution methodology is illustrated using an example and a two-stage comprehensive experimental study is conducted to determine the effective values of algorithm parameters and investigate the relationships between performance measures. Results show that the proposed approach is more realistic than the limited number of existing methodologies. The proposed approach is also extended to consider the stochastic completion times of tasks. (C) 2006 Elsevier Inc. All rights reserved.
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    Balancing of mixed-model two-sided assembly lines
    (PERGAMON-ELSEVIER SCIENCE LTD, 2009) Ozcan, Ugur; Toklu, Bilal
    This paper presents a new mathematical model and a simulated annealing algorithm for the mixed-model two-sided assembly line balancing problem. The proposed mathematical model minimizes the number of mated-stations (i.e., the line length) as the primary objective and minimizes the number of stations (i.e., the number of operators) as a secondary objective for a given cycle time. In the proposed simulated annealing algorithm, two performance criteria are considered simultaneously: maximizing the weighted line efficiency and minimizing the weighted smoothness index. The proposed approach is illustrated with an example problem, and its performance is tested on a set of test problems. The experimental results show that the proposed approach performs well. (c) 2008 Elsevier Ltd. All rights reserved.
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    A genetic algorithm for the stochastic mixed-model U-line balancing and sequencing problem
    (TAYLOR & FRANCIS LTD, 2011) Ozcan, Ugur; Kellegoz, Talip; Toklu, Bilal
    Mixed-model assembly lines are widely used to improve the flexibility to adapt to the changes in market demand, and U-lines have become popular in recent years as an important component of just-in-time production systems. As a consequence of adaptation of just-in-time production principles into the manufacturing environment, mixed-model production is performed on U-lines. This type of a production line is called a mixed-model U-line. In mixed-model U-lines, there are two interrelated problems called line balancing and model sequencing. In real life applications, especially in manual assembly lines, the tasks may have varying execution times defined as a probability distribution. In this paper, the mixed-model U-line balancing and sequencing problem with stochastic task times is considered. For this purpose, a genetic algorithm is developed to solve the problem. To assess the effectiveness of the proposed algorithm, a computational study is conducted for both deterministic and stochastic versions of the problem.
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    Multiple-criteria decision-making in two-sided assembly line balancing: A goal programming and a fuzzy goal programming models
    (PERGAMON-ELSEVIER SCIENCE LTD, 2009) Ozcan, Ugur; Toklu, Bilal
    Two-sided assembly lines are especially used at the assembly of large-sized products, such as trucks and buses. In this type of a production line, both sides of the line are used in parallel. In practice, it may be necessary to optimize more than one conflicting objectives simultaneously to obtain effective and realistic solutions. This paper presents a mathematical model, a pre-emptive goal programming model for precise goals and a fuzzy goal programming model for imprecise goals for two-sided assembly line balancing. The mathematical model minimizes the number of mated-stations as the primary objective and it minimizes the number of stations as a secondary objective for a given cycle time. The zoning constraints are also considered in this model, and a set of test problems taken from literature is solved. The proposed goal programming models are the first multiple-criteria decision-making approaches for two-sided assembly line balancing problem with multiple objectives. The number of mated-stations, cycle time and the number of tasks assigned per station are considered as goals. An example problem is solved and a computational study is conducted to illustrate the flexibility and the efficiency of the proposed goal programming models. Based on the decision maker's preferences, the proposed models are capable of improving the value of goals. (C) 2008 Elsevier Ltd. All rights reserved.
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    A SIMULATED ANNEALING APPROACH FOR PARALLEL ASSEMBLY LINE BALANCING PROBLEM
    (GAZI UNIV, FAC ENGINEERING ARCHITECTURE, 2009) Cercioglu, Hakan; Ozcan, Ugur; Gokcen, Hadi; Toklu, Bilal
    Production systems which has more than one assembly line is widely seen in industry. These lines produce same or similar products, and their cycle times are generally considered similar. So, Gokcen et al. (2006) suggested to combine workload of some stations on parallel consecutive lines, in a convenient way, for improving the resource utilization and the efficiency of the production system. This common balancing of more than one assembly line is named Parallel Assembly Line Balancing Problem (PALBP). The major aim of PALBP is to obtain minimum number of stations (or operators). In this paper, a simulated annealing (SA) based approach is developed for PALBP. This paper is built directly on the study of Gokcen et al. (2006). The proposed approach is illustrated with a numerical example and its performance is tested on data set taken from Gokcen et al. (2006). In the computational studies, for 95 test problems, the proposed approach found 47 proven optimal solutions and 6 solutions superior to Gokcen et al. (2006).
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    A tabu search algorithm for two-sided assembly line balancing
    (SPRINGER LONDON LTD, 2009) Ozcan, Ugur; Toklu, Bilal
    Two-sided assembly lines are often used at the assembly of large-sized high-volume products, such as cars, trucks, and buses. In this type of a production line, the left side and the right side of the line are used in parallel. This paper presents a tabu search algorithm for two-sided assembly line balancing. The line efficiency and the smoothness index are considered as the performance criteria. The proposed algorithm is illustrated with two numerical example problems, and its performance is tested on a set of test problems taken from literature. The performance of the proposed algorithm is compared to the existing approaches. The computational results show that the proposed algorithm performs well.