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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 The economic lot-sizing problem with perishable items and consumption order preference(Elsevier Science BV, 2015-08-01) Önal, Mehmet; Romeijn, H. Edwin; Sapra, Amar; Van den Heuvel, WilcoWe consider the economic lot-sizing problem with perishable items (ELS-PI), where each item has a deterministic expiration date. Although all items in stock are equivalent regardless of procurement or expiration date, we allow for an allocation mechanism that defines an order in which the items are allocated to the consumers. In particular, we consider the following allocation mechanisms: First Expiration, First Out (FEFO), Last Expiration, First Out (LEFO), First In, First Out (FIFO) and Last In, First Out (LIFO). We show that the ELS-PI can be solved in polynomial time under all four allocation mechanisms in case of no procurement capacities. This result still holds in case of time-invariant procurement capacities under the FIFO and LEFO allocation mechanisms, but the problem becomes NP-hard under the FEFO and LIFO allocation mechanisms.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 A mathematical model for perishable products with price- and displayed-stock-dependent demand(Elsevier Ltd, 2016-12) Önal, Mehmet; Yenipazarlı, Arda; Kundakçıoğlu, Ömer ErhunWe introduce an economic order quantity model that incorporates product assortment, pricing and space-allocation decisions for a group of perishable products. The goal is to maximize the retailer's profit under shelf-space and backroom storage capacity constraints. We assume that the demand rate of a product is a function of the selling prices and the displayed stock levels of all the products in the assortment. We propose a Tabu Search based heuristic method to solve this complex problem.Yayın Tractable supply chain production planning, modeling nonlinear lead time and quality of service constraints(Elsevier Ltd, 2007) Anlı, Osman Murat; Caramanis, Michael C.; Paschalidis, Ioannis Ch.This paper addresses the task of coordinated planning of a supply chain (SC). Work in process (WIP) in each facility participating in the SC, finished goods inventory, and backlogged demand costs are minimized over the planning horizon. In addition to the usual modeling of linear material flow balance equations, variable lead time (LT) requirements, resulting from the increasing incremental WIP as a facility's utilization increases, are also modeled. In recognition of the emerging significance of quality of service (QoS), that is control of stockout probability to meet demand on time, maximum stockout probability constraints are also modeled explicitly. Lead time and QoS modeling require incorporation of nonlinear constraints in the production planning optimization process. The quantification of these nonlinear constraints must capture statistics of the stochastic behaviour of production facilities revealed during a time scale for shorter than the customary weekly time scale of the planning process. The apparent computational complexity of planning production against variable LT and QoS constraints has long resulted in MRP-based scheduling practices that ignore the LT and QoS constraints has long resulted in MRP-based scheduling practices that ignore the LT and QoS impact to the plan's detriment. The computational complexity challenge was overcome by proposing and adopting a time-scale decomposition approach to production planning where short-time-scale stochastic dynamics are modeled in multiple facility-specific subproblems that receive tentative targets from a deterministic master problem and return statistics to it. A converging and scalable iterative methodology is implemented, providing evidence that significantly lower cost production plans are achievable in a computationally tractable manner.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 Maintenance policy analysis of the regenerative air heater system using factored POMDPs(Elsevier Ltd, 2022-03) Kıvanç, İpek; Özgür Ünlüakın, Demet; Bilgiç, TanerMaintenance optimization of multi-component systems is a difficult problem. Partially Observable Markov Decision Processes (POMDPs) are powerful tools for such problems under uncertainty in stochastic environments. In this study, the main POMDP solution approaches and solvers are surveyed. Then, based on experimental models with different complexities in the size of the system space, selected POMDP solvers using different representation patterns for modeling and different procedures for updating the value function while solving are compared. Furthermore, to show that factored representations are advantageous in modeling and solving the maintenance problem of multi-component systems where there exist also stochastic dependencies among the components, the maintenance problem of the one-line regenerative air heater system available in thermal power plants is modeled and solved with factored POMDPs. In-depth sensitivity analyses are performed on the obtained policy. The results show that factored POMDPs enable compact modeling, efficient policy generation and practical policy analysis for the tackled problem. Furthermore, they also motivate the use of factored POMDPs in the generation and analysis of maintenance policies for similar multi-component systems.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 Challenges in the CO2 emissions of the Turkish power sector: Evidence from a two-level decomposition approach(Elsevier Ltd, 2021-06) Işık, Mine; Ari, İzzet; Sarıca, KemalDecarbonization of the energy system is urgent to avert the disruptions in the climate. Considering its share, the low carbon transition of the power sector is pivotal. Growing electricity demand poses unique challenges for Turkey to enact deep decarbonization. It is vital to uncover the contributing causes of emissions to provide strategic oversight for carbon management activities. This study investigates key drivers of CO2 emissions from the power sector using the Logarithmic Mean Divisia Index decomposition method. While efficiency improvement contributes to sustainable yet minor mitigation, changes in the fossil-fuel share indicate a cycling but significant overall impact.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.
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