ÜRETİM SİSTEMLERİNDE DARBOĞAZ TESPİTİ: LİTERATÜR ARAŞTIRMASI

Year 2022, , 1285 - 1304, 31.12.2022

Nagihan Akkurt , Servet Hasgül

https://doi.org/10.17482/uumfd.1123981

Cited By: 1

Abstract

Üretim sistemleri için darboğaz üretim verimliliğini kısıtlayan en etkili faktörlerden biridir. Darboğaza sebep olan bir süreç daha hızlı çalışır ise tüm hattın üretim hızı artacak ve böylelikle üretim süreçlerinin ve tedarik zincirinin devamlılığı sağlanacaktır. Bu sebeple darboğazın tespit edilmesi ve kontrol altına alınması işletmeler için önem kazanmıştır. Literatürde bu konuda çok sayıda yöntem ve çalışma bulunmaktadır. Bu çalışmanın amacı ise literatürde bulunan darboğaz tespiti çalışmalarının incelenmesi, kullanılan yöntemlerin açıklanması ve analiz edilmesidir. Çalışma kapsamında 2007-2022 yıllarına ait toplam 48 makale incelenmiştir. İncelenen çalışmalardan elde edilen sonuçlara göre darboğaz tespitinde en çok benzetim yönteminin kullanıldığı görülmektedir. Aynı zamanda dönüm noktası yöntemi, aktif dönem yöntemi ve matematiksel yöntemler de darboğaz tespitinde diğer yöntemlere göre daha fazla kullanılmaktadır. Son yıllarda ise artan yapay zeka çalışmaları ile birlikte makine öğrenmesi tabanlı yaklaşımlar kullanılmaya başlanmıştır. Literatürde bu kadar sayıda darboğaz tespit yönteminin açıklandığı ve bu konudaki çalışmaların derlenip analiz edildiği bir çalışma bulunmamaktadır. Bu sebeple yapılan çalışmanın ilgili araştırmacılara yol göstermesi hedeflenmektedir.

Keywords

Üretim Sistemleri, Darboğaz, Darboğaz Tespit Yöntemleri

Thanks

Bu çalışmanın 1. Yazarı TÜBİTAK 2211-A Yurt İçi Doktora Burs Programı tarafından desteklenmektedir. Ancak yayın ile ilgili tüm sorumluluk yayının sahibine aittir. Yayının içeriğinin bilimsel anlamda TÜBİTAK tarafından onaylandığı anlamına gelmez.

Bottleneck Detection in Production Systems: Literature Research

Abstract

For production systems, the bottleneck is one of the most effective factors limiting production efficiency. If a process that causes a bottleneck runs faster, the production speed of the entire line will increase, thus ensuring the continuity of the production processes and supply chain. For this reason, it has become important for businesses to detect and control bottlenecks. There are many methods and studies on this subject in the literature. This study aims to examine the bottleneck detection studies in the literature and to explain and analyze the methods used. Within the scope of the study, a total of 48 articles belonging to the years 2007-2022 were examined. According to the results obtained from the studies examined, it is seen that the simulation method is mostly used in bottleneck detection. At the same time, the turning point method, active period method and mathematical methods are also more used in bottleneck detection than other methods. In recent years, machine learning-based approaches have been used in with increasing artificial intelligence studies. There is no study in the literature in which so many bottleneck detection methods are explained and studies on this subject are compiled and analyzed. For this reason, it is aimed that the study will guide the relevant researchers.

Keywords

Production Systems, Bottleneck, Bottleneck Detection Method

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