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WhoWe Are

Stochastics and Engineering Research Group (SERG) aims to advance in the fields of stochastic mathematical models and applications in supply chain management and service logistics. Our research was co-founded in 2017 by Dr. Mustafa Hekimoğlu, Industrial Engineer in Kadir Has University and Dr. Deniz Karlı, Mathematics in Işık University. Our research lab is located in Istanbul, Turkey. SERG continuously grows with post-graduate and graduate researchers all the time. We employ undergraduate students, graduate and post-graduate fellows in our projects.

Check for any available positions and job opennings below.

Job Openings
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What We Focus On

We mainly focus on stochastic models and their applications in control policies of spare parts inventory, maintenance policies for capital products. Our research demonstrates opportunity for significant improvement of the dynamics of maintenance activities and spare parts management. Determination of optimal control policies for capital products that are either at different stages of their life cycles is a challenging tasks in the field of service logistics. This challenge intensified by the introduction of online trading platforms, a.k.a. secondary markets. Secondary markets are effective in re-distribution of excess inventory and recovered components from retired products.

Predictive maintenance by utilizing data mining techniques and stochastic modeling is another focus area of our research. We aim to develop empirical models and maintenance policies that can be combined with classical corrective and preventive maintenance control systems.

From a methodological perspective, we utilize stochastic modeling and dynamic optimization for developing applicable solutions for problems. In addition, we employ linear and nonlinear mathematical programming, statistical inference and data mining techniques, to develop rigorous solutions and to create applications of our theoretical models in practice.

For current and past projects on these subjects check Projects section.

Projects
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What Is Our Experience

Our research group was cofounded by two successful academicians who have remarkable international experience. Dr. Mustafa Hekimoğlu has been a member of Erasmus Research Institute of Management (ERIM), Erasmus University, Rotterdam, the Netherlands, for 5 years. Dr. Deniz Karlı has been a member of University of Connecticut, United States, and a member of the University of British Columbia, Vancouver, Canada for 7 years. They published in respected journals many times.

Despite the fact that it has been recently founded, our research group managed to receive significant research grants from Turkey (TUBITAK). Under the roof of these grants, we employed several undergraduate and graduate students and provided them research experience.

In addition to these significant research experience, researchers in our group had been involved with research and consulting projects that aim to develop optimum solutions for spare parts management problems at Fokker Services in the Netherlands for five years. Moreover, we work as the scientific expert and consultant in a spare parts optimization projects at Turkish Technic, which is a Maintenance Repair Organization providing service for Turkish Airlines in Istanbul.

For published and working papers, check our papers section.

Publications

We Have Creative Researchers

Stochastics and Engineering Research Group

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Dr. Mustafa Hekimoğlu

Cofounder of SERG

About

Expertise

Industrial Engineering

Institute

Kadir Has University

Email

mustafa.hekimoglu@khas.edu.tr

Previous Institutes

Bogazici University, Istanbul

Erasmus Research Institute of Management (ERIM), Erasmus University, Rotterdam, the Netherlands

Işık University, Istanbul

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Dr. Deniz Karlı

Cofounder of SERG

About

Expertise

Mathematics

Institute

Işık University

Email

deniz.karli@isikun.edu.tr

Previous Institutes

Bogazici University, Istanbul

University of Connecticut, CT, United States

The University of British Columbia, Vancouver, Canada

Işık University, Istanbul

3+

Projects

5+

Published Papers

10+

Citations

1+

PhD Graduates

2+

Ms Graduates

4+

Undergraduate Sclolarships

3+

Collaborated Academic Institutes

1+

Collaborated Private Institutions

200000+

Funding Recieved

Team Stats

STOCHASTICS AND ENGINEERING RESEARCH GROUP

Research Projects

Stochastics and Engineering Research Group

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Optimum Spare Parts Inventory Control With Installed Base Information In Existence of Secondary Markets

(Funded by Tübitak)

In this project, it is aimed to address the study the optimal purchasing policy in existence of secondary markets and a regular supplier. Secondary markets will be considered as a cheap and fast supplier with random capacity whereas the regular supplier has no capacity but it is more expensive and it delivers with a longer lead time. In a multi-period setting, it is aimed to obtain an analytic characterization of the inventory control policy. Later, we will develop an algorithm that can optimize parameters of the control policy in a polynomial time. In the demand side, we consider installed base dependency of spare parts. Therefore, the demand distribution will be assumed to be nonstationary as the size of installed base changes in different phases of the life cycle of a capital product. For instance in the introduction phase, new capital products are sold by the OEM and the size of the installed base gets larger. Conversely in the final phase, called out-of-product or end-of-life, the installed base shrinks which causes decreasing spare parts demand. The output of this project will shed light on the problem of spare parts inventory control in existence of secondary markets with varying size of installed base.

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Development of Mathematical Models for the Optimum Utilization of 3D Printers in Spare Parts Inventory Management

(Funded by Tübitak)

The aim of this project is to develop inventory control models considering the four fundamental factors affecting the usage of 3D printers for spare parts: quality difference between original and printed parts, blueprint cost, OPS lead time and existence of laser polishing. The scope of project focuses on effect of using parts in different quality levels with different blueprint licencing techniques on the optimum cost and supply decisions. Furthermore, we will analyze how increasing quality levels with laser polishing by changing its laser energy density affects optimum policy.

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Our Publications

Stochastics and Engineering Research Group

All
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Journal Papers
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Conference Papers
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Preprints
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In Preperation

Markov-modulated analysis of a spare parts system with random lead times and disruption risks

European Journal of Operational Research

Spare parts supply chains are highly dependent on the dynamics of their installed bases. A decreasing number of capital products in use increases the nonstationary supply-side risk especially towards the end-of-life of capital products. This supply-side risk appears to present itself through varying lead times coupled with supply disruptions. To model the nonstationary supply-side risk, we consider an exoge- nous Markov chain that modulates random lead times and disruption probabilities. Assuming that order crossovers do not occur, we prove the optimality of a state-dependent base stock policy. Later, we conduct an impact study to understand the value of considering stochastic lead times and supply disruption risk in spare parts inventory control. Our results indicate that the coupled effect of random lead times and disruptions can be larger than the summation of individual effects even for moderate lead time variances. Also, the effect of nonstationarity on total cost can be as large as the summation of all risk factors com- bined. In addition to this managerial insight we present a procedure for supply risk mitigation based on an empirical model and our mathematical model. Experiments on a real business case indicate that the procedure is capable of reducing costs while making the inventory system more prepared for disruptions.

 

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Spare Parts Management In Existence of Dynamic Installed Base

Preprint

In this paper, we provide an analytic characterization of time-dependent distribution of random spare parts demand distribution. This finding is useful for OEMs who seek to plan their operations and spare parts inventory for planning of their medium and long-term operations. These theoretical findings are applied to the following practical problems:

1. Spare parts inventory control in case of growing and declining installed bases: Our method creates savings up-to 1%.

2. Lifetime extension investment of manufacturers for their existing products: Optimum time of investment and installed base size is derived for a given investment cost.

3. Remanufacturers’ availability of used products.

 

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Jobs and Positions We Offer

Stochastics and Engineering Research Group

Researcher

Positions

Open Researcher positions

Post-Doc

Positions

Open Post-Doc positions

Graduate Student(Phd&Msc)

Positions

Available positions for graduate students

Our Blog

Stochastics and Engineering Research Group

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Connect

with SERG.

Mustafa HEKİMOĞLU, Ph.D

  • mustafa.hekimoglu@khas.edu.tr
  • Department of Industrial Engineering
  • Kadir Has University

Deniz KARLI, Ph.D.

  • deniz.karli@isikun.edu.tr
  • Department of Mathematics
  • Işık University

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