Akıllı SERU sistemleri: DeJong öğrenme etkisi ile çok dönemli üretim planlaması yeniliği

Yıl 2026, Cilt: 41 Sayı: 1 , 565 - 578 , 31.03.2026

Çağdaş Yıldız

https://doi.org/10.17341/gazimmfd.1745136

https://izlik.org/JA88XS67TR

Öz

Bu çalışma, dönen SERU üretim sistemlerinde DeJong öğrenme etkilerinin çok dönemli üretim planlaması optimizasyonuna entegrasyonunu araştırmaktadır. İşçi maliyetleri, kurulum masrafları ve kurulum süreleri için farklı öğrenme parametreleri (α₁,α₂,α₃) kullanarak üç boyutlu bir DeJong modeli geliştirilmiştir. Karma tamsayılı doğrusal programlama yöntemiyle oluşturulan model, 27 eşitlik ve 15 dönemlik planlama sürecini kapsamaktadır. 2, 3 ve 4 farklı SERU konfigürasyonu, 8 işçi ve 2 ürün tipi modellenerek, Analitik Hiyerarşi Süreci (AHP) ile objektif işçi yetkinlik matrisi oluşturulmuştur. Türkiye buzdolabı sektöründen elde edilen gerçek verilerle kalibre edilen model, LINGO optimizasyon yazılımıyla çözülmüştür. On DeJong senaryosunun 2-SERU ve 3-SERU konfigürasyonlarında tamamında, 4-SERU'da dokuzunda pozitif sonuçlar elde edilmiş, kurulum maliyet odaklı öğrenme senaryosu %18,03 (808,150 TL) tasarruf sağlayarak en yüksek performansı göstermiştir. 3-SERU konfigürasyonunun başarı oranı ve hesaplama performansı dengesinde optimal nokta olduğu kanıtlanmıştır. Sonuçlar, tek boyutlu öğrenme stratejilerinin çok boyutlu yaklaşımlardan daha etkili olduğunu ve kurulum süreçlerinde uzmanlaşmanın kritik başarı faktörü olduğunu ortaya koymaktadır.

Anahtar Kelimeler

Dönen SERU üretim sistemi , DeJong öğrenme etkisi , çok dönemli planlama , karma tamsayılı programlama , maliyet optimizasyonu

Smart SERU systems: multi-period production planning innovation with DeJong learning effect

https://izlik.org/JA88XS67TR

Öz

This study investigates the integration of DeJong learning effects into multi-period production planning optimization in rotating SERU production systems. A three-dimensional DeJong model is developed using different learning parameters (α₁,α₂,α₃) for worker costs, setup expenses, and setup times. The model, formulated using mixed-integer linear programming, encompasses 27 equations and a 15-period planning process. 2, 3, and 4 different SERU configurations with 8 workers and 2 product types are modeled, with an objective worker competency matrix created using Analytical Hierarchy Process (AHP). The model, calibrated with real data from Turkey's refrigerator sector, is solved using LINGO optimization software. Positive results are obtained in all scenarios for 2-SERU and 3-SERU configurations, and in nine of ten scenarios for 4-SERU, with the setup cost-focused learning scenario achieving the highest performance with 18.03% (808.150 TL) savings. The 3-SERU configuration is proven to be the optimal point in the success rate and computational performance balance. Results reveal that single-dimensional learning strategies are more effective than multi-dimensional approaches and that specialization in setup processes is a critical success factor.

Anahtar Kelimeler

Rotating SERU production system , DeJong learning effect , multi-period planning , mixed integer programming , cost optimization

Kaynakça

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