Kaynak atölyesi çizelgeleme probleminin değişken iş istasyonu kısıtlaması altında optimizasyonu: Arena simülasyonu tabanlı genetik algoritma ile endüstriyel bir uygulama

Öz

İş atölyesi planlaması, 'emek yoğun proje tipi üretim' için zor bir konudur. Çünkü bu tür bir üretimde, gerçek işlem süreleri üretim bitene kadar tam olarak bilinmez ve bu işlem süreleri siparişin teknik özelliklerine göre değişir. İşlem sürelerini tahmin etmek için olasılık dağılımlarını kullanmak uygun bir yöntemdir. Bu makale, emek-yoğun proje tipi çalışan kaynak atölyesinin değişken iş istasyonu kısıtlamaları altında planlanması için endüstriyel bir uygulama sunmaktadır. Bu kısıt, ürünlerin boyuna bağlı olarak ortaya çıkan özel bir üretim şeklinin sonucudur. Amaç, bir grup bekleyen iş emrinin tamamlanma süresini en aza indirmektir. Genetik algoritma (GA) bu amaçla, atölyeye girmeyi bekleyen iş emirlerinin atölyeye giriş sırasını oluşturmak ve bunları 6 özdeş kaynak istasyonuna göndermek için kullanılır. Atölyenin dinamik koşulları, Arena simülasyon programı ile simüle edilir. Algoritmanın girdi verileri olarak stokastik işlem süreleri kullanılır. Kaynak iş istasyonu çizelgeleme için değişken iş istasyonu kısıtlaması altında stokastik işleme sürelerinin kullanılması daha önce araştırılmamıştır. Deneysel sonuçlara göre, GA ve Arena simülasyonu birlikte, değişken iş istasyonu kısıtlaması altında bu tür problemlerde bir grup işin toplam tamamlanma zamanını etkili bir şekilde azaltmaktadır. GA destekli Arena çizelgesi, bu sorun için GA kullanmadan önerilen çizelgeden daha iyi performans gösterir. Simülasyon sonuçları, bekleyen siparişlerin toplam üretim süresinin, GA kullanılmadan önerilen çizelgelerle karşılaştırıldığında yaklaşık % 9,25 oranında azaldığını göstermektedir

Anahtar Kelimeler

• Arena simülasyonu
• Genetik algoritma
• Emekyoğun proje tipi üretim
• Tamamlanma zamanı minimizasyonu
• Değişken iş istasyonu kısıtı
• Kaynak atölyesi çizelgeleme problemi

Optimization of welding job-shop scheduling problem under variable workstation constraint: an industrial application with Arena simulation based genetic algorithm

Abstract

Job-shop scheduling is a difficult issue for 'labor-intensive project type manufacturing'. Because in this type of production, the actual processing times are not exactly known until the production is finished and these processing times vary depending on the order’s technical specifications. It is an appropriate method to use probability distributions to forecast the processing times. This paper provides an industrial application for the scheduling of a labor-intensive project type working welding job-shop under variable workstation constraints. This constraint is consequence of a special production type that is depending on the length of the products. The aim is minimizing the makespan of a group of waiting orders. Genetic algorithm (GA) is used for this purpose to establish the entry sequence of the job-shop's waiting orders and dispatching them to the 6 identical welding stations. The dynamic conditions of the job-shop are simulated by the Arena simulation program. Stochastic processing times are used as the input data of the algorithm. Using stochastic processing times under variable workstation constraint for welding job-shop scheduling is not investigated previously. According to the experimental results, GA and Arena simulation together effectively reduces the makespan in this type of problem under variable workstation constraint. The GA aided Arena schedule outperforms the schedules proposed without using GA for this problem. Simulation results indicate that the total manufacturing time of pending orders is nearly 9.25% reduced when compared with the schedules proposed without using GA.

Keywords

• Arena simulation
• Genetic algorithm
• Labor-intensive project type production
• Makespan minimization
• Variable workstation constraint
• Welding shop scheduling problem

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