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Yayın On the sensitivity of desirability functions for multiresponse optimization(American Institute of Mathematical Sciences, 2008-11) Aksezer, Sezgin ÇağlarDesirability functions have been one of the most important multiresponse optimization technique since the early eighties. Main reasons for this popularity might be counted as the convenience of the implementation of the method and it's availability in many experimental design software packages. Technique itself involves somehow subjective parameters such as the importance coefficients between response characteristics that are used to calculate overall desirability, weights used in determining the shape of each individual response and the size of the specification band of the response. However, the impact of these sensitive parameters on the solution set is mostly uninvestigated. This paper proposes a procedure to analyze the sensitivity of the important characteristic parameters of desirability functions and their impact on pareto-optimal solution set. The proposed procedure uses the experimental design tools on the solution space and estimates a prediction equation on the overall desirability to identify the sensitive parameters. For illustration, a classical desirability example is selected from the literature and results are given along with the discussion.Yayın Assortment optimization with log-linear demand: application at a Turkish grocery store(Elsevier Ltd, 2019-09) Hekimoğlu, Mustafa; Sevim, İsmail; Aksezer, Sezgin Çağlar; Durmuş, İpekIn retail sector, product variety increases faster than shelf spaces of retail stores where goods are presented to consumers. Hence, assortment planning is an important task for sustained financial success of a retailer in a competitive business environment. In this study, we consider the assortment planning problem of a retailer in Turkey. Using empirical point-of-sale data, a demand model is developed and utilized in the optimization model. Due to nonlinear nature of the model and integrality constraint, we find that it is difficult to obtain a solution even for moderately large product sets. We propose a greedy heuristic approach that generates better results than the mixed integer nonlinear programming in a reasonably shorter period of time for medium and large problem sizes. We also proved that our method has a worst-case time complexity of O(n 2 )while other two well-known heuristics’ complexities are O(n 3 )and O(n 4 ). Also numerical experiments reveal that our method has a better performance than the worst-case as it generates better results in a much shorter run-times compared to other methods.Yayın A DBN based reactive maintenance model for a complex system in thermal power plants(Elsevier Sci Ltd, 2019-10) Özgür Ünlüakın, Demet; Türkali, Busenur; Karacaörenli, Ayşe; Aksezer, Sezgin ÇağlarThermal power plants consist of several complex systems having many interacting hidden components. Any unexpected failure may lead to prolonged downtime and serious lost profits. Therefore, implementing an effective maintenance policy is crucial for this sector. Although preventive maintenance has become a more popular strategy, it does not completely prevent the need for corrective maintenance. Our aim in this study is to tackle the corrective maintenance implementation problem of a multi-component partially observable dynamic system based on a regenerative air heater in a thermal power plant. We propose eight methods having different efficiency measures with respect to time, effect and probability criteria to minimize the total number of maintenance activities in a given planning horizon. Performances of these methods are evaluated under corrective maintenance strategy using dynamic Bayesian networks. The results show that fault effect methods with best working state probability measure perform better than the others considering both the total amount of maintenance activities and also the solution time. We also point out how the methods can be implemented in real-life and how the results can be used for requirements planning. Furthermore, the proposed methods can be used for the corrective maintenance of all systems having hidden interacting components.Yayın Cost-effective fault diagnosis of a multi-component dynamic system under corrective maintenance(Elsevier Ltd, 2021-04) Özgür Ünlüakın, Demet; Türkali, Busenur; Aksezer, Sezgin ÇağlarMaintenance planning and execution are challenging tasks for every system with complex structure. Interdependent nature of the components that builds up the system may have significant effect on system integrity. While preventive maintenance actions can be carried out in a more planned fashion, corrective actions are more time sensitive as they directly affect the availability of the system. This study proposes a cost-effective dynamic Bayesian network modeling scheme to be used in the planning of corrective maintenance actions on systems having hidden components which have stochastic and structural dependencies. In such context, the regenerative air heater system which is a key element of a power plant is taken into consideration. The proposed maintenance framework offers several methods, each aiming to balance the cost with the probability effect using a normalization procedure. The methodologies are extensively simulated for sensitivity analysis under various downtime cost values. Fault effect methods with worst state probability efficiency measures give the least total cost for all downtime cost values and their distinction becomes significant as this value increases. Further statistical analysis concludes that considerable gains on maintenance costs can be achieved by the proposed approach.Yayın Failure analysis and warranty modeling of used cars(Pergamon-Elsevier Science Ltd, 2011-09) Aksezer, Sezgin ÇağlarReliability is an important aspect of product perception and manufacturers are compelled to take corrective actions on the items failing within the warranty period. Automotive manufacturers are being exposed to significant operating costs as a result of warranty claims affecting an individual unit or mandatory (sometimes voluntary) recalls affecting a batch. Underlying principles of warranty modeling are built by considering both subjective issues and objective constraints such as competition, quality, and performance under the goal of achieving desired levels of reliability and cost in a balanced manner. This paper reviews the warranty cost models with an emphasis on the failure analysis of used vehicles. Expected warranty costs are calculated by taking into account the age, usage, and maintenance data of the product in question. Failure intensities and characteristics are identified in order to propose a policy that highlights the trade-off between the cost and the warranty length. A case study on a popular brand's initiation of factory certified pre-owned program for the local automobile market of Turkey is presented in detail. (C) 2011 Elsevier Ltd. All rights reserved.Yayın Dynamic frontier estimation for monitoring team performances: A case on Turkish first division football league(Emerald Group Publishing Limited, 2019-06-10) Yılmaz, Melike; Aksezer, Sezgin Çağlar; Atan, Sabri TankutPurpose: This paper aims to investigate how predictions of football league standings and efficiency measures of teams, obtained through frontier estimation technique, evolve compared to actual results. Design/methodology/approach: The study is based on data from the Turkish first division football league. Historical data for five seasons, from 2011 to 2016, are used to compare weekly estimates to de facto results. Data envelopment analysis efficiency measures are used to estimate team performances. After each week, a data envelopment analysis is run using available data until then, and final team standings are estimated via computed efficiencies. Estimations are improved by using a data envelopment analysis model that incorporates expert knowledge about football. Findings: Results indicate that deductions can be made about the league’s future progress. Model incorporating expert knowledge tends to estimate the performance better. Although the prediction accuracy starts out low in early stages, it improves as the season advances. Scatter of individual teams’ performances show fluxional behaviour, which attracts studying the impact of uncontrollable factors such as refereeing. Originality/value: While all previous studies focus on season performance, this study handles the problem as a combination of weekly performance and how it converges to reality. By tracking weekly performance, managers get a chance to confront their weak performance indicators and achieve higher ranking by improving on these inefficiencies.Yayın Multiresponse optimisation of powder metals via probabilistic loss functions(Inderscience Enterprises Ltd, 2013) Aksezer, Sezgin Çağlar; Benneyan, James C.Quadratic loss functions have been used extensively within the context of quality engineering and experimental design for process and product optimisation and robust design. In general, this approach determines optimal parameter settings based on minimising the sum of individual or mean loss of the associated response(s) of interest in a defined response surface. While the method is neat and handy, it totally neglects the effect of deviations on the desirable value of loss function. This paper utilises variance and probability distribution of loss functions for developing an in depth optimisation scheme that balances mean and variance of loss in a Pareto optimal manner. Since losses are usually defined in financial terms, this model then further improved to handle the user determined risk levels so that financial losses are being restricted within a certain region of interest. Application of the model is illustrated on a multiresponse optimisation problem from powder metallurgy industry.Yayın Assessing the efficiency of hospitals operating under a unique owner: a DEA application in the presence of missing data(Inderscience Publishers, 2010-05) Aksezer, Sezgin Çağlar; Benneyan, James C.Originally developed in the late 1970s to assess the efficiency of comparable operating units, Data Envelopment Analysis (DEA) has since been used in a variety of contexts. Although incomplete data sets are often encountered in practice, the best approach in such situations is unclear in general. This paper explores methods such as multiple imputation, bootstrapping and smart dummy variable replacement, borrowed from similar missing data problems in regression analysis. Each missing data method is tested on a library of DEA problems that are gathered from the DEA literature. These problems are selected in such a way as to represent a thorough cross-section of problem sizes (small, medium, large) and types (type of DEA model, number of decision-making units, number of inputs, number of outputs, etc.). The results are illustrated by comparing the solutions of complete data sets against the simulated versions of the same data sets with missing data. The sensitivity of each method on the efficiency scores and ranking of the decision-making units is presented.Yayın Reliability evaluation of healthcare services by assessing the technical efficiency(Routledge Journals, Taylor & Francis Ltd, 2011) Aksezer, Sezgin ÇağlarClassical reliability analysis techniques of manufacturing and defence industries are not a perfect fit for the assessment of the reliability of services. This is partly due to the lack of proper and valid reliability testing procedures in service systems and complications faced in identifying critical service parameters. Since most prominent performance indicators of a system can be associated with the maximum overall reliability it achieves, then factors that degrade the reliability can be identified with respect to its superior peers. This study utilizes the data envelopment analysis for the evaluation of reliability in service systems with a focus on healthcare. This approach comparably evaluates the performance of a service provider over a period of time by means of failure rates and identifies the factors affecting unreliable time phases. Application of the proposed method is illustrated with a private Turkish hospital along with an example of failure mode and effect analysis for inpatient treatment.
