Mühendislik Fakültesi / Faculty of Engineering
Permanent URI for this collectionhttps://hdl.handle.net/11727/1401
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Item The Efficiency of Variance Reduction in Manufacturing and Service Systems: The Comparison of the Control Variates and Stratified Sampling(2009) Eraslan, Erguen; Dengiz, Berna; 0000-0002-5667-0391; AAE-7165-2019There has been a great interest in the use of variance reduction techniques (VRTs) in simulation output analysis for the purpose of improving accuracy when the performance measurements of complex production and service systems are estimated. Therefore, a simulation output analysis to improve the accuracy and reliability of the output is required. The performance measurements are required to have a narrow and strong confidence interval. For a given confidence level, a smaller confidence interval is supposed to be better than the larger one. The wide of confidence interval, determined by the half length, will depend on the variance. Generally, increased replication of the simulation model appears to have been the easiest way to reduce variance but this increases the simulation costs in complex-structured and large-sized manufacturing and service systems. Thus, VRTs are used in experiments to avoid computational cost of decision-making processes for more precise results. In this study, the effect of Control Variates (CVs) and Stratified Sampling (SS) techniques in reducing variance of the performance measurements of M/M/1 and GI/G/1 queue models is investigated considering four probability distributions utilizing randomly generated parameters for arrival and service processes. Copyright (C) 2009 E. Eraslan and B. Dengiz.Item Redesign Of PCB Production Lıine With Simulation And Taguchi Design(2009) Dengiz, BernaThis paper presents the problem of determining the optimum condition of printed circuit board (PCB) manufacturing process in an electronic company in Ankara,. Turkey. In the optimization stage of the study Taguchi method is integrated with simulation model considering minimum total cost under stochastic breakdowns. Using this methodology we investigate the system performance of the current PCB line and determine the optimum working conditions with reduced cost, time and effort.Item Buffer Allocation and Performance Modeling in Asynchronous Assembly System Operations: An Artificial Neural Network Metamodeling Approach(2007) Altiparmak, Fulya; Dengiz, Berna; Bulgak, Akif A.; 0000-0003-1730-4214; AAF-7020-2021This article investigates metamodeling opportunities in buffer allocation and performance modeling in asynchronous assembly systems ( AAS). Practical challenges to properly design these complex systems are emphasized. A critical review of various approaches in modeling and evaluation of assembly systems reported in the recently published literature, with a special emphasis on the buffer allocation problems, is given. Various applications of artificial intelligence techniques on manufacturing systems problems, particularly those related to artificial neural networks, are also reviewed. Advantages and the drawbacks of the metamodeling approach are discussed. In this context, a metamodeling application on AAS buffer design/performance modeling problems in an attempt to extend the application domain of metamodeling approach to manufacturing/assembly systems is presented. An artificial neural network ( ANN) metamodel is developed for a simulation model of an AAS. The ANN and regression metamodels for each AAS are compared with respect to their deviations from the simulation results. The analysis shows that the ANN metamodels can successfully be used to model of AASs. Consequently, one concludes that practising engineers involved in assembly system design can potentially benefit from the advantages of the metamodeling approach. (c) 2006 Elsevier B. V. All rights reserved.Item An International Facility Design Project(2008) Lacksonen, Thomas; Dengiz, BernaThis paper describes an international facilities design project for Manufacturing and Industrial Engineering students. American and Turkish engineering students collaborated to create and implement the re-design of a Turkish wheelchair manufacturing facility. The company needed engineering assistance to improve the efficiency and increase the capacity of their existing factory. Turkish Industrial Engineering students went on-site to collect data and draw the existing facility layout. American Manufacturing Engineering students analyzed the data and developed new layout designs. Four American students traveled to Turkey between semesters to implement the initial phases of their design. In the second semester, the Turkish students simulated the new layout to see the performance improvements, completing their project. Student learning outcomes were positive for both groups of students. The paper explains critical steps in identifying projects and partners. Lessons are shown about successes and shortcomings in planning, operating, and communicating with design teams across cultures.Item Aintshop Production Line Optimization Using Response Surface Methodology(2007) Dengiz, Berna; Belgin, Onder; 0000-0001-6702-2608; K-1080-2019This paper deals with the problem of determining the optimum number of workstations to be used in parallel and workers at some stations using simulation optimization approach in a paint shop line of an automotive factory in Ankara, Turkey. In the optimization stage of the study Response Surface Methodology (RSM) is used to find the optimum levels of considered factors. Simulation model and optimization stage integration is used both to analyse the performance of the current paint shop line and determine the optimum working conditions, respectively, with reduced cost, time and effort.Item A Systematic Approach to Reduce Human and System-related Errors Causing Customer Dissatisfaction in a Production Environment(2009) Pakdil, Fatma; Oezkoek, Onur; Dengiz, Berna; Kara, Imdat; Selvi, Nilay; Karg, Alper; ABH-1078-2021In this study, a systematic methodology for business process improvement, which aims to eliminate human and system-related errors resulting in customer dissatisfaction in a production environment, is presented. The proposed methodology consists of problem identification and analysis, preventing human-related errors and system-related error steps respectively. The methodology was also implemented in a real-life organisation. Current and proposed systems are compared via a simulation model to examine the results of process improvements. The case study shows that the proposed methodology works exceedingly well and yields considerable improvement in the process under study. The most important and impressive difference of this paper from the previous literature is that process improvement needs are derived directly from customer dissatisfaction reasons and solved by the proposed systematic methodology. In this way human-related and system-related errors were perceived opportunities for improvement.Item A Local Search Heuristic with Self-tuning Parameter for Permutation Flow-Shop Scheduling Problem(2009) Dengiz, Berna; Alabas-Uslu, Cigdem; Sabuncuoglu, IhsanIn this paper, a new local search metaheuristic is proposed for the permutation flow-shop scheduling problem. In general, metaheuristics are widely used to solve this problem due to its NP-completeness. Although these heuristics are quite effective to solve the problem, they suffer from the need to optimize parameters. The proposed heuristic, named STLS, has a single self-tuning parameter which is calculated and updated dynamically based on both the response surface information of the problem field and the performance measure of the method throughout the search process. Especially, application simplicity of the algorithm is attractive for the users. Results of the experimental study show that STLS generates high quality solutions and outperforms the basic tabu search, simulated annealing, and record-to-record travel algorithms which are well-known local search based metaheuristics.Item A Hybrid Simulated Annealing For A Multi-Objective Stochastic Assembly Line Balancing Problem(2008) Cakir, Burcin; Dengiz, Berna; Altiparmak, Fulya; Xia, GP; Deng, XQ; 0000-0003-1730-4214; AAF-7020-2021Asssembly line balancing is the problem of assigning tasks to the workstations, while optimizing one or more objectives without violating restrictions imposed on the line. In practice, task times may be random due to the worker fatigue, low skill levels, job dissatisfaction, poorly maintained equipment, defects in raw material, etc. When stochastic task times are taken consideration in assembly lines, balancing procedure is more complex due to the probability of incompleteness of stations times in a given cycle time. In this study, a multi-objective simulated annealing algorithm (m_SAA) is proposed for single-model, stochastic assembly line balancing problem with the aim of minimizing of smoothness index and total design cost. To obtain Pareto-optimal solutions, m_SAA implements tabu list and a multinomial probability mass function approach. The effectiveness of the proposed m_SAA is comparatively investigated using another SA using weight-sum approach on the test problems. Computational results show that m_SAA with multinomial probability mass function approach is more effective than SA with weight-sum approach in terms of quality of Pareto-optimal solutions.Item A General Neural Network Model for Estimating Telecommunications Network Reliability(2009) Altiparmak, Fulya; Dengiz, Berna; Smith, Alice E.; 0000-0003-1730-4214; 0000-0001-8808-0663; AAF-7020-2021; AAK-2318-2021This paper puts forth a new encoding method for using neural network models to estimate the reliability of telecommunications networks with identical link reliabilities. Neural estimation is computationally speedy, and can be used during network design optimization by an iterative algorithm such as tabu search, or simulated annealing. Two significant drawbacks of previous approaches to using neural networks to model system reliability are the long vector length of the inputs required to represent the network link architecture, and the specificity of the neural network model to a certain system size. Our encoding method overcomes both of these drawbacks with a compact, general set of inputs that adequately describe the likely network reliability. We computationally demonstrate both the precision of the neural network estimate of reliability, and the ability of the neural network model to generalize to a variety of network sizes, including application to three actual large scale communications networks.Item A cross entropy approach to design of reliable networks(2009) Dengiz, Berna; Altiparmak, Fulya; 0000-0003-1730-4214; AAF-7020-2021One of the most important parameters determining the performance of communication networks is network reliability. The network reliability strongly depends on not only topological layout of the communication networks but also reliability and availability of the communication facilities. The selection of optimal network topology is an NP-hard problem so that computation time of enumeration-based methods grows exponentially with network size. This paper presents a new solution approach based on cross-entropy method, called NCE, to design of communication networks. The design problem is to find a network topology with minimum cost such that all-terminal reliability is not less than a given level of reliability. To investigate the effectiveness of the proposed NCE, comparisons with other heuristic approaches given in the literature for the design problem are carried out in a three-stage experimental study. Computational results show that NCE is an effective heuristic approach to design of reliable networks. (C) 2008 Elsevier B.V. All rights reserved.