Hekimoğlu, Mustafa

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Name Variants
Hekimoğlu, Mustafa
M.,Hekimoğlu
M. Hekimoğlu
Mustafa, Hekimoğlu
Hekimoglu, Mustafa
M.,Hekimoglu
M. Hekimoglu
Mustafa, Hekimoglu
Hekimoglu,M.
Hekimoglu, M.
Hekimoğlu, M.
Job Title
Doç. Dr.
Email Address
Mustafa.hekımoglu@khas.edu.tr
Main Affiliation
Industrial Engineering
Status
Former Staff
Website
ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
Scholarly Output

30

Articles

21

Citation Count

0

Supervised Theses

3

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2021 - 20234
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Author: Yücekaya, Ahmet Deniz

Scholarly Output Search Results

Now showing 1 - 4 of 4
  • Thumbnail Image
    Conference Object
    Citation - WoS: 2
    Citation - Scopus: 3
    The Implementation of Smart Contract via Blockchain Technology in Supply Chain Management: A Case Study from The Automotive Industry in Turkey
    (IEEE, 2021) Hekimoğlu, Mustafa; Yücekaya, Ahmet Deniz; Bozkurt, Hayreddin; Yucekaya, Ahmet; Hekimoglu, Mustafa
    Blockchain Technology, underlined as the most revolutionizing innovation after the internet, is still in the growth phase and waits for the practitioners to enlighten its productivity promises. In the current environment, volatile profits require a more digitalized work experience and competitive advantages to get ahead in such a highly competitive automotive industry and innovative applications that lead to more simplified operation management. Accordingly, this paper aims to present a case study via use cases in which Blockchain has been used and smart contract as the sought-out innovation and its application for the digitized spare parts disposal legal process. Blockchain Technology in the automotive sector is discussed by focusing on the supply management process of an automotive company's processes in Turkey. Blockchain technology is expected to develop and simplify spare parts-related transactions in the automotive industry, which deals with more than 500K stock keeping units per company. Paper presents the current, future, and ideal states of spare parts transactions with Blockchain adoption. The implemented application enables the development of an enterprise-level blockchain platform with hyper-ledger fabric as an open-source. The distributed ledger technology provides a smart contract system between actors of the existed supply chain process. The study aims to show the potential of Blockchain Technology in delivering a high degree of competitive advantage especially for automotive service providers with regards to its features related to providing security, transparency, traceability, cost reduction, more efficient data storage in dense supply based industries.
  • Thumbnail Image
    Article
    Citation - Scopus: 12
    Optimization of Wastewater Treatment Systems for Growing Industrial Parks
    (Elsevier B.V., 2023) Savun-Hekimoğlu, B.; Yücekaya, Ahmet Deniz; İşler, Z.; Hekimoğlu, Mustafa; Hekimoğlu, M.; Burak, S.; Karlı, D.; Yücekaya, A.; Akpınar, E.
    Wastewater treatment is one of the crucial functions of industrial parks as wastewater from industrial facilities usually contains toxic compounds that can cause damage to the environment. To control their environmental loads, industrial parks make investment decisions for wastewater treatment plants. For this, they need to consider technical and economic factors as well as future growth projections as substantial construction and operational costs of wastewater treatment plants have to be shared by all companies in an industrial park. In this paper, we consider the long-term capacity planning problem for wastewater treatment facilities of a stochastically growing industrial park. By explicitly modeling randomness in the arrival of new tenants and their random wastewater discharges, our model calculates the future mean and variance of wastewater flow in the industrial park. Mean and variance are used in a Mixed Integer Programming Model to optimize wastewater treatment plant selection over a long planning horizon (30 years). By fitting our first model to empirical data from an industrial park in Turkey, we find that considering the variance of wastewater load is critical for long-term planning. Also, we quantify the economic significance of lowering wastewater discharges which can be achieved by water recycling or interplant water exchange. © 2023 Elsevier B.V.
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    Article
    Citation - Scopus: 5
    Forecasting Hourly Electricity Demand Under Covid-19 Restrictions
    (Econjournals, 2022) Kök, A.; Yücekaya, Ahmet Deniz; Yükseltan, E.; Bilge, Ayşe Hümeyra; Hekimoğlu, M.; Hekimoğlu, Mustafa; Aktunc, E.A.; Yücekaya, A.; Bilge, A.
    The rapid spread of the COVID-19 pandemic has severely impacted many sectors including the electricity sector. The restrictions such as lockdowns, remote-working, and-schooling significantly altered the consumers’ behaviors and demand structure especially due to a large number of people working at home. Accurate demand forecasts and detailed production plans are crucial for cost-efficient generation and transmission of electricity. In this research, the restrictions and their corresponding timing are classified and mapped with the Turkish electricity demand data to analyze the impact of the restrictions on total demand using a multiple linear regression model. In addition, the model is utilized to forecast the electricity demand in pandemic conditions and to analyze how different types of restrictions impact the total electricity demand. It is found that among three levels of COVID-19 restrictions, age-specific restrictions and the complete lockdown have different effects on the electricity demand on weekends and weekdays. In general, new scheduling approaches for daily and weekly loads are required to avoid supply-demand mismatches as COVID-19 significantly changed the consumer behavior, which appears as altered daily and weekly load profiles of the country. Long-term policy implications for the energy transition and lessons learned from the COVID-19 experience are also discussed. © 2022, Econjournals. All rights reserved.
  • Thumbnail Image
    Article
    Citation - WoS: 11
    Optimization of Wastewater Treatment Systems for Growing Industrial Parks
    (Elsevier, 2023) Savun-Hekimoglu, Basak; Hekimoğlu, Mustafa; Isler, Zulal; Yücekaya, Ahmet Deniz; Hekimoglu, Mustafa; Ediger, Şevket Volkan; Burak, Selmin; Karli, Deniz; Yucekaya, Ahmet; Ediger, Volkan S.
    Wastewater treatment is one of the crucial functions of industrial parks as wastewater from industrial facilities usually contains toxic compounds that can cause damage to the environment. To control their environmental loads, industrial parks make investment decisions for wastewater treatment plants. For this, they need to consider technical and economic factors as well as future growth projections as substantial construction and operational costs of wastewater treatment plants have to be shared by all companies in an industrial park. In this paper, we consider the long-term capacity planning problem for wastewater treatment facilities of a stochastically growing industrial park. By explicitly modeling randomness in the arrival of new tenants and their random wastewater discharges, our model calculates the future mean and variance of wastewater flow in the industrial park. Mean and variance are used in a Mixed Integer Programming Model to optimize wastewater treatment plant selection over a long planning horizon (30 years). By fitting our first model to empirical data from an industrial park in Turkey, we find that considering the variance of wastewater load is critical for long-term planning. Also, we quantify the economic significance of lowering wastewater discharges which can be achieved by water recycling or interplant water exchange.