Bekli, Rahime Şeyma

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Profile URL
https://hdl.handle.net/20.500.12573/2887
Name Variants
Bekli, Rahime Şeyma
Bekli, Seyma
Job Title
Dr. Öğr. Üyesi
Email Address
seyma.bekli@agu.edu.tr
Main Affiliation
02.02. Endüstri Mühendisliği
Status
Current Staff
Website
ORCID ID
0000-0002-1844-2304
Scopus Author ID
57244022900
Turkish CoHE Profile ID
196916
Google Scholar ID
DcaIFmIAAAAJ
WoS Researcher ID
FZP-0741-2022

Sustainable Development Goals

13

CLIMATE ACTION
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0

Research Products

15

LIFE ON LAND
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0

Research Products

8

DECENT WORK AND ECONOMIC GROWTH
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0

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10

REDUCED INEQUALITIES
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0

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2

ZERO HUNGER
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0

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6

CLEAN WATER AND SANITATION
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0

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14

LIFE BELOW WATER
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0

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11

SUSTAINABLE CITIES AND COMMUNITIES
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16

PEACE, JUSTICE AND STRONG INSTITUTIONS
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0

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5

GENDER EQUALITY
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0

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9

INDUSTRY, INNOVATION AND INFRASTRUCTURE
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1

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7

AFFORDABLE AND CLEAN ENERGY
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0

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4

QUALITY EDUCATION
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0

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1

NO POVERTY
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17

PARTNERSHIPS FOR THE GOALS
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0

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3

GOOD HEALTH AND WELL-BEING
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12

RESPONSIBLE CONSUMPTION AND PRODUCTION
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1

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Scholarly Output

4

Articles

0

Views / Downloads

4/0

Supervised MSc Theses

1

Supervised PhD Theses

0

WoS Citation Count

0

Scopus Citation Count

3

WoS h-index

0

Scopus h-index

1

Patents

0

Projects

0

WoS Citations per Publication

0.00

Scopus Citations per Publication

0.75

Open Access Source

2

Supervised Theses

1

JournalCount
Eurasia Proceedings of Science, Technology, Engineering and Mathematics2
Eurasia Proceedings of Science, Technology, Engineering and Mathematics -- 7th International Conference on Research in Engineering, Technology and Science, ICRETS 2025 -- 2025-07-10 through 2025-07-13 -- Peja -- 3439191
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Now showing 1 - 4 of 4
  • Thumbnail Image
    Conference Object
    Citation - Scopus: 1
    Incorporating Worker Heterogeneity in Flexible Flow Shop Environment
    (ISRES Publishing, 2025) Ozpacaci, Kubra; Bekli, Seyma; Kayisoglu, Betul
    We study the flexible flow shop scheduling problem with the heterogeneous worker assignment. In many real-life manufacturing systems with flow shop environments, one of the fundamental scheduling challenges that needs to be addressed is job sequences across multiple workers. In addition, the manufacturing system may require workers to have different skills at various stages during their assignment. Therefore, worker availability at each stage may vary during the scheduling horizon. Unlike traditional flexible flow shop scheduling problem, where homogeneous workers are assumed, we consider workers with different skill levels, capabilities, and capacities. We present a mixed integer linear programming model to find the optimal sequence of job assignments, guaranteeing that jobs follow their predefined operation sequence while assigning workers with various skill sets in a flexible flow shop environment. The proposed model is tested at a battery manufacturing company. By analyzing the solution, we confirm its capability to represent the problem accurately. The proposed model offers a systematic scheduling approach for a flexible flow shop environment with a heterogeneous workforce and can be implemented in other industries. © 2025 Elsevier B.V., All rights reserved.
  • Thumbnail Image
    Master Thesis
    Belirsiz İşlem Süresine Tabi Paralel Makine Çizelgelemeleri
    (Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2017) Bekli, Rahime Şeyma; Gören, Selçuk
    Günümüz dünyasında iş ve üretim rekabeti, firmaların verimlilik artıran ve imalat maliyetini düşüren çizelgeler üretmesine yol açmıştır. Ancak, üretilen çizelgeler beklenmedik aksaklıklar yüzünden, genellikle amaçlandığı şekilde uygulanamamaktadır. Bu aksaklıklar makine arızalanması, sipariş iptali gibi örneklendirilebilir. Aksaklıklara duyarsız çizelge olan gürbüz çizelgeleme, son yıllarda araştırmacılar arasında önem kazanmıştır. Bu çalışmada, belirsiz işlem süresine tabi paralel makine ortamı ele alınmıştır. Performans ölçütü son işin bitiş süresi olarak alınmıştır. Belirsizlik, ayrık senaryolar olarak modellenmiş ve küçük boyuttaki problemleri çözebilen bir tam sayılı programlama oluşturulmuştur. Bu model büyük problemleri çözmede sıkıntılıdır. Bu sebeple senaryo sayısını azaltma yaklaşımı denenmiştir. Daha sonra eşiz ayrıştırma yöntemi ile büyük problemlerin çözümü amaçlanmıştır. Bu yöntemi kullanmadaki amaç büyük bir problem çözmek yerine, küçük ama çok sayıda problem çözerek sonuca ulaşmaktır. Ancak bu yöntem de büyük problemlerde istenilen sonuçları vermemiştir. Bu sebeple senaryo sayısı azaltılarak eşiz ayrıştırma yöntemi kullanılmış ve yeni bir sezgisel önerilmiştir. Aynı zamanda bir tabu arama algoritması oluşturulmuştur. Sonuçlar, önerilen sezgisel algoritmalardan senaryo azaltılması ve tabu arama algoritmalarının paralel makine ortamında iyi sonuçlar verdiğini göstermektedir.
  • Thumbnail Image
    Conference Object
    Scheduling in Flexible Flow Shop Environments with Re-Entrant Jobs and Heterogeneous Workers
    (ISRES Publishing, 2025) Bekli, S.; Kayisoglu, B.
    In many industries, manufacturing is organized as a flexible flow shop (FFS), which has gotten the researchers' attention. The scheduling studies, particularly those on FFS scheduling, are concerned with homogeneous workers with the same skill set or heterogeneous workers who can only perform one specific type of operation on the production lines. Moreover, jobs are mainly assumed to go through an operation once. Yet, in real-life production, workers might have different skill sets with varying processing times. Furthermore, certain jobs may require revisiting the same machine multiple times, i.e., re-entrant jobs. We study an FFS environment with re-entrant jobs, considering worker flexibility. We propose a mixed integer linear programming model to find the optimal sequences of jobs to be processed by the multiskilled workers assigned to the production system, ensuring each re-entrant job waits for a predefined time window before reprocessing on the same operation. The objective of the model is to minimize makespan. We tested the proposed model on a dataset taken from a real production system of a PVC windows and doors production facility. © 2025 Published by ISRES Publishing.
  • Thumbnail Image
    Conference Object
    Citation - Scopus: 2
    Parallel Machine Scheduling With Re-Entrant Jobs With Consideration of Set Up Times
    (ISRES Publishing, 2024) Kayisoglu, Betul; Bekli, Seyma; Sahin, Ayse Sena; Akyurek, Gamze Gul; Aydinli, Ruveyda; Copur, Sevda Nur; Ekinci, Tugba
    We study the identical parallel machine problem with re-entrant jobs. Re-entrant jobs require to pass through the processing line multiple times. In many real-life manufacturing systems with parallel machine environments, one of the scheduling problems that needs to be addressed is the order of jobs on each machine with re-entrant jobs. In addition, manufacturing systems may require periodic maintenance, systematic manufacturing equipment cleaning, or predetermined upper limits on the overtime. Therefore, machine availability may vary during the scheduling horizon. We propose an integer programming model to find the optimal sequence of the re-entrant jobs at parallel machines with consideration of machine availability. The model aims to reduce setup times and maximize capacity utilization by scheduling tasks with similar set up requirements consecutively. We tested the proposed model at a panel line manufacturing company located in Turkey. The order of the panels is scheduled optimally by the proposed model for 3 different instances on the identical parallel machines for the coating process. We also provided relevant information on the user interface we developed to make the proposed scheduling model usable to by the company. The proposed model and interphase offer a systematic approach to panel line planning and can also be implemented in other industries. © 2025 Elsevier B.V., All rights reserved.