Determining the number of kanbans for dynamic production systems: An integrated methodology

Abstract

Just-in-time (JIT) is a management philosophy that reduces the inventory levels and eliminates manufacturing wastes by producing only the right quantity at the right time. A kanban system is one of the key elements of JIT philosophy. Kanbans are used to authorize production and to control movement of materials in JIT systems. In Kanban systems, the efficiency of the manufacturing system depends on several factors such as number of kanbans, container size etc. Hence, determining the number of kanbans is a critical decision in Kanban systems. The aim of this study is to develop a methodology that can be used in order to determine the number of kanbans in a dynamic production environment. In this methodology, the changes in system state is monitored in real time manner, and the number of the kanbans are dynamically re-arranged. The proposed methodology integrates simulation, neural networks and Mamdani type fuzzy inference system. The methodology is modelled in simulation environment and applied on a hypothetic production system. We also performed several comparisons for different control policies to show the effectiveness of the proposed methodology.

Dinamik üretim sistemleri için kanban sayısının belirlenmesi: Bütünleşik bir yöntem

Öz

Tam zamanında üretim sistemleri (TZÜ), işletmelerin doğru zamanda, müşterinin istediği miktarda üretim yapmalarına olanak sağlayan, böylelikle stoklarını azaltmaya teşvik eden bir yönetim felsefesidir. TZÜ felsefesinin en önemli parçası, malzeme hareketlerini gerçekleştirmek için kullanılan kanban sistemleridir. Kanban sistemlerinde, iş istasyonlarında kullanılacak kanban sayılarının belirlenmesi en temel problem olarak karşımıza çıkmaktadır. Kullanılacak kanban sayıları üretim sisteminin performansı üzerinde etkilidir. Bu çalışmanın temel amacı, Kanban sistemlerinde, kart sayılarının dinamik belirlenebilmesi için kullanılabilecek bir yöntem geliştirmektir. Önerilen yöntemin temelinde, üretim sisteminin anlık veri alınarak izlenmesi ve sistem durum değişkenlerinde meydana gelen farklılıkların dikkate alınarak Kanban sayılarının yeniden düzenlemesi yatmaktadır. Bu amaçla yapılan çalışmada benzetim, yapay sinir ağları ve Mamdani tipi bulanık çıkarsama sistemleri entegre edilerek bütünleşik bir dinamik kanban sayıları belirleme yöntemi geliştirilmiştir. Önerilen yöntem, benzetim ortamımda modellenen hipotetik bir üretim sistemine uygulanmıştır. Elde edilen sonuçlar, önerilen yöntemin verimliliğini ve etkinliğini göstermiştir.

Anahtar Kelimeler

• Kanban üretim sistemleri, Benzetim, Yapay sinir ağları, Bulanık çıkarsama sistemleri

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