Büyük Veriyle Kaynak ve Kapasite Kısıtları Altında Üretim Planlama ve Çizelgeleme

Abstract

Büyük veri, işletmelerin iç yapısında biriken veya çeşitli dış kaynaklardan toplanan verilerin derlenmesi, depolanması, düzenlenmesi ve analiz edilmesiyle anlamlı bilgiler ortaya çıkararak, işletmeler için fayda yaratabilmektedir. İşletmenin fonksiyonlarından biri olan üretim alanında veri derlemek bu verileri yapısal hale getirerek değer yaratmak büyük avantaj yaratmaktadır. Büyük veri setlerinin analiz edilerek üretim planlamasında kullanılması hammaddelerin başarılı bir şekilde çıktılara dönüşebilmesinde önemli rol oynamaktadır. Madencilik sektörü içinde birçok belirsizliği barındırması, sermaye yoğun bir iş olması nedeniyle uzun vadeli üretim planlamasına ihtiyaç duyan sektörlerden biridir. Öte yandan gelişen teknolojiyle beraber maden sahaları hakkında büyük veri setlerinin derlenebilmesi mümkün hale gelmektedir. Bu çalışma kapsamında açık ocak madenciliği yapan orta büyüklükte bir firmanın sahip olduğu kömür ocağında yaşanan sorunların çözülebilmesi amacıyla maden sahasından gerekli veri toplanarak uzun vadeli üretim planlaması ve çizelgelemesi yapılmıştır. Firmanın üretimini etkileyen kaynak ve kapasite kısıtları ve sahip olduğu cevherin özellikleri, literatürde yer alan tam sayılı üretim planlanma ve çizelgeleme matematiksel modellerine uyarlanmıştır. Kurulan matematiksel model Python programlama diliyle çözülmüştür. Çalışmanın sonucunda firmanın ilgili kömür ocağındaki 5 yıllık üretiminin çizelgesine ve toplamda elde edeceği kârın net bugünkü değerine ulaşılmıştır. Çalışma yararlandığı büyük veri setleri ve matematiksel model sayesinde ortaya çıkardığı plan ile firmaya gelecek için politikalar geliştirebilme imkânı sunmuştur.

Keywords

• Üretim yönetimi
• büyük veri
• kapasite kısıtı
• kaynak kısıtı
• üretim planlama ve çizelgeleme
• doğrusal programlama

Production planning and scheduling with big data under resource and capacity constraints

Abstract

Big data creates value and gains insight into knowledge via collecting, warehousing, organizing and analyzing the data that obtained from operations or external resources. Make benefit of big data analysis while production planning and management are essential to process raw materials in successful outputs. An effective production system avails to company and to society as a whole. All production processes need planning to improve productivity. One of those processes is mining. Mining which has two methods, as open pit mining and underground mining, is a capital intense production process and contains lots of uncertainty. However, advancing technology provides getting more information about the mining areas and helps to enable collecting and analyzing big data. In this study, mine planning and scheduling models applied to a medium sized company which faces results of their unplanned production method in coal mine, most of the times. According to firm’s operational constraints and features of orebody, a mine planning and scheduling problem is designed and as solution method integer programming is used. That integer programming model is run by Python programming language and Gurobi optimizer. The optimizer showed the result of company’s net present value of total profit and information about mine scheduling for five years. Production plan which is a result of mathematical model driven by big data, provides the ability of generating strategies for future to company.

Keywords

• Production management
• big data
• planning
• scheduling
• capacity constraint
• resource constraint
• linear programming

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