Bakım için makine öğrenme tekniklerinin analizi ve bir uygulama

Abstract

Bakım, her üretim kuruluşunda olması gerekli bir faaliyet olarak kabul edilirken, günümüzde ise ilave olarak şirketin gelir ve giderlerini etkileyen
kritik bir işletme fonksiyonu olarak tanımlanmaktadır. Makine öğrenmesi kavramı, makinelerin karşılaştıkları durumlar karşısında kendini eğiterek
daha iyi kararlar verebilmesini sağlayan algoritmaların geliştirilmesi olgusudur. 1950 yıllarından itibaren bakım planlaması tahminleme
çalışmasında makine öğrenmesi teknikleri kullanılmaktadır. Savunma sanayi firmasında yapılan bu çalışmada makinelerin aniden ve plansız
yapılan bakımlardan kaynaklı maliyeti yüksek olan parçaların hurda olması ve sevkiyatlarda meydana gelen gecikmelerden dolayı firmanın
müşterilere yüksek miktarda ceza ödemesi problemi ele alınmıştır. Bu çalışmadaki amaç gelişen bilim ve teknoloji kullanılarak, yapılacak olan
bakım planlamalarını, arızaları önceden tahmin etmek, üretimde durmayı, maliyet kaybını en aza indirgemek veya tamamen engelleyebilmektir.
Makine Öğrenmesi tekniklerinden denetimli öğrenme tekniği savunma sanayi firmasındaki en kritik kimyasal boya makinesinde uygulanarak
bakım planlaması tahmini çalışması yapılmıştır. 

Keywords

• Makine öğrenmesi
• Kestirimci bakım
• Bakım planlaması

Analysis of machine learning techniques for maintenance and an application

Abstract

While maintenance is considered a necessary activity in every production establishment, it is defined as a critical business function that
affects the income and expenses of the company today. The concept of machine learning is the phenomenon of developing algorithms that enable
machines to make better decisions by educating themselves in the face of the situations they encounter. Machine learning techniques have been used
in maintenance planning estimation studies since the 1950s. In this study conducted by a defense industry firm, the problem of the fact that
the parts with high costs due to sudden and unplanned maintenance of the machines are scrap and the company pays a high amount of fines to
customers due to delays in shipments. The purpose of this study is to predict the maintenance planning and malfunctions to be made by using
developing science and technology, to minimize the cost loss and completely prevent stopping in production, in addition, the supervised
learning technique, one of the Machine Learning techniques, was applied in the most critical chemical paint machine in the defense industry
company, and maintenance planning was estimated.

Keywords

• Machine learning
• Precdictive maintenance
• maintenance planning

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