# Industrial Engineering

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Item ORE-AGE: AN INTELLIGENT TUTORING SYSTEM MODEL FOR MINING METHOD SELECTION(The International Journal of Mineral Resources Engineering, 2008-07-21) GÜRAY, CenkShow more Mining method selection is a critical decision for an economic, safe productive mining work. Each orebody is unique with its own properties and engineering judgment has a great effect on the decisions. In this study an intelligent assisting and tutoring system for preliminary underground mining method selection is developed. This systems is called Ore-Age, whose goal is making the preliminary mining method selection as effeciently as posssible too while giving them a remarkable education on mining method selection. Due to its semi-autonomous character, Ore-Age determşnes to direct its execution strategy based on the expertise levels od the users. Ore-Age acts as an assisting tool for the experienced engineers during the selection process and continuously looks for the help of its neuro-fuzzy learning algorithm. The reason of Ore-Age to take this learning procedure is to imitate and behave like these experts during his future selections. Besides this ability, Ore-Age tries to act as a tutoring system as efficiently as possible when he faces inexperienced engineers. The regular strategy of teaching process depends on an iterative algorithm checking the decisive concepts one by one to find the point of misconception leading to wrong selection. Furthermore as an alternative strategy, by his error modeling property, Ore-Age can alter hhis strategy and concentrate the users directly to the possible points of misconception, without using the previous "time demanding" algorithm. This system aiming the model thecognitive behaviour of the student is an indication of the reactive characteristic of the system that can alter the strategies based on his own logical decison to achieve a more efficient tutoring procedure. The system that is being developed in this study can be introduced as the first example of dynamic, intelligent assisting and tutoring systems in the mining profession.Show more Item Oyun ve Oyuncak Tasarımı(Herkese Bilim Teknoloji, 2017-07-08) ÜNAL, BülentShow more Çocuklar, çok erken yaştan itibaren çevre hakkında bir şeyler öğrenmek için oyunu birincil araç olarak kullanırlar. Oyun sadece çocukların dünyayı nasıl anladığını yansıtmakla kalmaz, aynı zamanda sosyal, duygusal, fiziksel gelişimlerini ve problem çözme becerilerini artırmak için fırsatlar sağlar (Lopez, 2012). Oyunun avantajları ne olabilir? Pek çok türün gençleri arasında var olan bir davranışın evrimsel bir avantajı olmalıdır, aksi takdirde bu türler 'doğal seleksiyon' yoluyla ortadan kaldırılırdı. Oyun, beyin gelişimini ve büyümesini arttırır, yeni sinir bağlantıları kurar ve bir bakıma oyuncuyu daha akıllı yapar. Başkalarının duygusal durumunu algılama ve değişen koşullara uyum yeteneğini geliştirir. Yetişkin beyinleri de yeni sinir devrelerini geliştirme ve öğrenme yeteneğine sahip olduğu için, yetişkinlerin de oynamaya devam etmesi önerilmektedir (Goldstein, 2012).Show more Article Identifying the cycles in COVID-19 infection: the case of Turkey(Journal of Applied Statistics, 2023) Akdi, Yılmaz; Karamanoğlu, Yunus Emre; Ünlü, Kamil Demirberk; Baş, CemShow more The new coronavirus disease, called COVID-19, has spread extremely quickly to more than 200 countries since its detection in December 2019 in China. COVID-19 marks the return of a very old and familiar enemy. Throughout human history, disasters such as earthquakes, volcanic eruptions and even wars have not caused more human losses than lethal diseases, which are caused by viruses, bacteria and parasites. The first COVID-19 case was detected in Turkey on 12 March 2020 and researchers have since then attempted to examine periodicity in the number of daily new cases. One of the most curious questions in the pandemic process that affects the whole world is whether there will be a second wave. Such questions can be answered by examining any periodicities in the series of daily cases. Periodic series are frequently seen in many disciplines. An important method based on harmonic regression is the focus of the study. The main aim of this study is to identify the hidden periodic structure of the daily infected cases. Infected case of Turkey is analyzed by using periodogram-based methodology. Our results revealed that there are 4, 5 and 62 days cycles in the daily new cases of Turkey.Show more Article A new generalized 𝜹-shock model and its application to 1-out-of-(m + 1):G cold standby system(Reliability Engineering and System Safety, 2023-02-28) Eryılmaz, Serkan; Ünlü, Kamil DemirberkShow more According to the classical 𝜹-shock model, the system failure occurs upon the occurrence of a new shock that arrives in a time length less than 𝜹; a given positive value. In this paper, a new generalized version of the 𝜹-shock model is introduced. Under the proposed model, the system fails if there are m shocks that arrive in a time length less than 𝜹 after a previous shock, m 1. The mean time to failure of the system is approximated for both discretely and continuously distributed intershock time distributions. The usefulness of the model is also shown to study 1-out-of-(m + 1):G cold standby system. Illustrative numerical results are presented for geometric, exponential, discrete and continuous phase-type intershock time distributions.Show more Article Forecasting Air Quality in Tripoli: An Evaluation of Deep Learning Models for Hourly PM2.5 Surface Mass Concentrations(Atmosphere, 2023-02-28) Esager, Marwa Winis Misbah; Ünlü, Kamil DemirberkShow more In this article, we aimed to study the forecasting of hourly PM2.5 surface mass concentrations in the city of Tripoli, Libya. We employed three state-of-the-art deep learning models, namely long short-term memory, gated recurrent unit, and convolutional neural networks, to forecast PM2.5 levels using univariate time series methodology. Our results revealed that the convolutional neural networks model performed the best, with a coefficient of variation of 99% and a mean absolute percentage error of 0.04. These findings provide valuable insights into the use of deep learning models for forecasting PM2.5 and can inform decision-making regarding air quality management in the city of Tripoli.Show more Article Reliability of a mixed 𝜹-shock model with a random change point in shock magnitude distribution and an optimal replacement policy(Reliability Engineering and System Safety, 2023-04) Chadjiconstantinidis, Stathis; Eryılmaz, SerkanShow more A mixed 𝛿-shock model when there is a change in the distribution of the magnitudes of shocks is defined and studied. Such a model which is a combination of the 𝛿-shock model and the extreme shock model with a random change point (studied by Eryilmaz and Kan, 2019), is useful in practice since a sudden change in environmental conditions may cause a larger shock. In particular, the reliability and the mean time to failure of the system are evaluated by assuming that the random change point has a discrete phase-type distribution. Analytical results for eval-uating the reliability function of the system for several joint distributions of the interarrival times and the magnitudes of shocks, are also given. The optimal replacement policy that is based on a control limit is also proposed when the number of shocks until the change point follows geometric distribution. The results are illustrated by numerical examples.Show more Article Strategic electricity production planning of Turkey via mixed integer programming based on time series forecasting(Mathematics, 2023-04-14) Yörük, Gökay; Baç, Uğur; Yerlikaya-Özkurt, Fatma; Ünlü, Kamil DemirberkShow more This study examines Turkey’s energy planning in terms of strategic planning, energy policy, electricity production planning, technology selection, and environmental policies. A mixed integer optimization model is proposed for strategic electricity planning in Turkey. A set of energy resources is considered simultaneously in this research, and in addition to cost minimization, different strategic level policies, such as CO2 emission reduction policies, energy resource import/export restriction policies, and renewable energy promotion policies, are also considered. To forecast electricity demand over the planning horizon, a variety of forecasting techniques, including regression methods, exponential smoothing, Winter’s method, and Autoregressive Integrated Moving Average methods, are used, and the best method is chosen using various error measures. The optimization model constructed for Turkey’s Strategic Electricity Planning is obtained for two different planning intervals. The findings indicate that the use of renewable energy generation options, such as solar, wind, and hydroelectric alternatives, will increase significantly, while the use of fossil fuels in energy generation will decrease sharply. The findings of this study suggest a gradual increase in investments in renewable energy-based electricity production strategies are required to eventually replace fossil fuel alternatives. This change not only reduces investment, operation, and maintenance costs, but also reduces emissions in the long term.Show more Article Optimal age replacement policy for discrete time parallel systems(TOP, 2023-10) Eryılmaz, Serkan; Tank, FatihShow more In the case of discrete age replacement policy, a system whose lifetime is measured by the number cycles is replaced preventively after a specific number of cycles or correctively at failure, whichever occurs first. Under the discrete setup, the policy has been mostly considered for single unit systems. In this paper, a discrete time age replacement policy is studied for a parallel system that consists of components having discretely distributed lifetimes. In particular, the necessary conditions for the unique and finite replacement cycle that minimize the expected cost rate are obtained. The theoretical results are illustrated with numerical examples to observe the effect of the cost values and the mean lifetime of the components on the optimal replacement cycle.Show more Article Age based preventive replacement policy for discrete time coherent systems with independent and identical components(Reliability Engineering and System Safety, 2023-11) Eryılmaz, SerkanShow more The paper is concerned with an age based preventive replacement policy for an arbitrary coherent system that consists of components that are independent and have common discrete lifetime distribution. The system having an arbitrary structure is replaced preventively after a specific number of cycles or correctively at its failure time. The necessary conditions for the unique and finite replacement cycle that minimize the expected cost per unit of time are obtained. The policy is studied for some particular system models including the well-known -out-of- structure. The findings of the paper extend the results in the literature from single unit and parallel systems to an arbitrary coherent system. Numerical results are presented for particular discrete component lifetime distributions.Show more Article Computing waiting time probabilities related to (k1, k2, ..., kl) pattern(Statistical Papers, 2023-11-26) Chadjiconstantinidis, Stathis; Eryılmaz, SerkanShow more For a sequence of multi-state trials with l possible outcomes denoted by f1; 2; :::; lg, let E be the event that at least k1 consecutive 1s followed by at least k2 consecutive 2s,..., followed by at least kl consecutive ls. Denote by Tr the number of trials for the rth occurrence of the event E in a sequence of multi-state trials. This paper studies the distribution of the waiting time random variable Tr when the sequence consists of independent and identically distributed multi-state trials. In particular, distributional properties of Tr are examined via matrix-geometric distributions.Show more Article Statistics and probability theory in renewable energy: Teaching and research(Applied Stochastic Models in Businesss and Industry, 2023-12-03) Eryılmaz, Serkan; Kateri, Maria; Devrim, YılserShow more In this paper, the key-role and utility of statistics and probability theory in the field of renewable energy are emphasized and illustrated via specific examples. It is demonstrated that renewable energy is a very suitable field to effectively teach and implement many statistical and probabilistic concepts and techniques. From a research point of view, statistical and probabilistic methods have been successfully employed in evaluating renewable energy systems. These methods will continue to be of core interest for the renewable energy sector in the future, as new and more complex renewable energy systems are developed and installed. In this context, some future research directions in relation to the evaluation of renewable energy systems are also presented.Show more Article cmaRs: A powerful predictive data mining package in R(SoftwareX, 2023-12-15) Yerlikaya-Özkurt, Fatma; Yazıcı, Ceyda; Batmaz, İnciShow more Conic Multivariate Adaptive Regression Splines (CMARS) is a very successful method for modeling nonlinear structures in high-dimensional data. It is based on MARS algorithm and utilizes Tikhonov regularization and Conic Quadratic Optimization (CQO). In this paper, the open-source R package, cmaRs, built to construct CMARS models for prediction and binary classification is presented with illustrative applications. Also, the CMARS algorithm is provided in both pseudo and R code. Note here that cmaRs package provides a good example for a challenging implementation of CQO based on MOSEK solver in R environment by linking R to MOSEK through the package Rmosek.Show more Article Age replacement policy for heterogeneous parallel systems(Journal of Computational and Appleid Mathematics, 2024-03-01) Bulanık Özdemir, İrem; Kılıçoğlu, Sevval; Eryılmaz, SerkanShow more The optimization policy on age replacement mostly focuses on systems comprised of identical components. In this paper, both discrete and continuous time age replacement policies are considered by relaxing the assumption of identical components and working with heterogeneous parallel system, i.e. system with not necessarily identical components. In particular, necessary conditions are obtained for the existence and uniqueness of optimal replacement cycle/time for the parallel system with two nonidentical components under the proposed policy. The extension of the results to a system with more than two components is also presented.Show more Article On 𝜹-shock model with a change point in intershock time distribution(Statistics & Probability Letters, 2024-06-25) Chadjiconstantinidis, Stathis; Eryılmaz, SerkanShow more In this paper, we study the reliability of a system that works under 𝛿-shock model. That is, the system failure occurs when the time between two successive shocks is less than a given thresh old 𝛿. In a traditional setup of the 𝛿 shock model, the intershock times are assumed to have the same distribution. In the present setup, a change occurs in the distribution of the intershock times due to an environmental effect. Thus, the distribution of the intershock times changes after a random number of shocks. The reliability of the system is studied under this change point setup.Show more Item A new extended δ-shock model with the consideration of shock magnitude(Applied Stochastic Models in Business and Industry, 2024-07-14) Lorvand, Hamed; Eryılmaz, SerkanShow more In this article, a new -shock model that takes into account the magnitude of shocks is introduced and studied from reliability perspective. According to the new model, the system breaks down if either a shock after non-critical shock occurs in a time length less than or a shock after a critical shock occurs in a time length less than where . The distribution of the system's lifetime is studied for both discrete and continuous intershock time distributions. It is shown that a new model is useful to describe a certain cold standby repairable system.Show more Article Reliability and performance evaluation of weighted k-out-of-n:G system consisting of components with discrete lifetimes(Reliability Engineering and System Safety, 2024-08-31) Eryılmaz, SerkanShow more For the k-out-of-n system consisting of components that have di§erent weights, the system is in a good state if the total weight of working components is at least k. Such a system is known to be weighted k-out-of-n:G system. Although the weighted k-out-of-n system that has continuously distributed componentsílifetimes has been extensively studied, the discrete weighted k-out-of-n:G system has not been consid ered yet. The present paper Ölls this gap by modelling and analyzing the weighted k-out-of-n:G system that consists of discretely distributed componentsílifetimes. In particular, the behavior of the total capacity/weight of the system with respect to the component failures is evaluated. An optimization problem that is concerned with the determination of optimal number of spare components is also formulated by utilizing the mean lost capacity of the system.Show more