KAPASİTELİ BİR KEÇE ÜRETİM SİSTEMİNDE MAKİNE HIZI EN İYİLEME PROBLEMİ

Year 2025, Volume: 33 Issue: 2, 1780 - 1795, 22.08.2025

Banu Kabakulak

https://doi.org/10.31796/ogummf.1475020

Abstract

Bu çalışmada, kimyasal reaksiyonların başarılı bir şekilde gerçekleşmesini sağlamak için makine hızlarının belirli sınırlar içinde tutulması gibi kendine özgü gereksinimlere sahip bir keçe üretim sistemi ele alınmıştır. Makine hızı kısıtları ve hem yarı mamul (YM) hem de nihai ürün stok sınırlamaları dikkate alınarak, her keçe türü için en iyi üretim miktarlarının ve ilgili makine hızlarının belirlenmesi amaçlanmaktadır. Amaç, makine kurulum ve üretim maliyetleri ile YM ve nihai ürün stok tutma maliyetlerini en küçüklemektir. Bu doğrultuda, Makine Hızı En İyileme (MHE) problemi tanımlanmış ve İstanbul, Türkiye'de faaliyet gösteren bir keçe üretim firmasının gereksinimlerine uyarlanmıştır. MHE problemi, en iyi üretim kararlarının bulunmasının NP-zor olduğu karma-tamsayılı doğrusal programlama modeli olarak ifade edilmiştir. Önerilen MHE modelinin üretim planlaması ve makine hız kararlarının otomasyonu konusunda etkinliği keçe üretim firmasının beş dönemlik verileri üzerinde doğrulanmıştır. 5 günlük planlama ufku için yapılan simülasyonlar, firmanın mevcut uygulamasına kıyasla toplam maliyette 3853 TL azalma, YM stoklarında %24 düşüş ve makine kullanım oranında %15’e varan iyileşme sağlandığını göstermektedir. Ayrıca, MHE modeli ile en iyilenen makine hızları, sistemin üretim kapasitesini %11 arttırmıştır. MHE modelinin karmaşıklığına dair deneysel analizler, modelin makine hızlarını içeren 6 aylık bir üretim planını bir saatten daha kısa sürede en iyileyebildiğini ortaya koymuştur.

Keywords

Keçe Üretimi , Parti Büyüklüğü , Makine Hızı , Karma-Tamsayılı Programlama

A MACHINE SPEED OPTIMIZATION PROBLEM IN A CAPACITATED FELT PRODUCTION SYSTEM

Abstract

In this study, we analyze a felt production system with unique requirements, such as maintaining machine speeds within specific limits to facilitate successful chemical reactions. By incorporating machine speed constraints and restrictions on both work-in-process (WIP) and end-product inventories, we aim to determine the optimal production quantities for each felt type and the corresponding machine speeds over a defined planning horizon. The objective is to minimize total costs, including machine setup and production costs as well as WIP and end-product inventory holding costs. To achieve this, we introduce the Machine Speed Optimization (MSO) problem and adapt it to the specific requirements of a felt manufacturing company operating in Istanbul, Türkiye. The MSO problem is formulated as a mixed-integer linear programming (MILP) model, which is NP-hard to solve for optimal production decisions. We validate the MSO model using the felt manufacturing company's case over five periods, demonstrating its effectiveness in automating production planning and machine speed decisions. The simulations for a 5-day planning horizon demonstrate a cost reduction of 3853 TL, a 24% decrease in WIP inventory, and up to a 15% improvement in machine utilization compared to the current practices of the felt manufacturing company. Additionally, the optimized machine speeds achieved through the MSO model enable the system to increase throughput by 11%. Experimental analysis of computational complexity reveals that the MSO model can generate an optimal 6-month production plan, including machine speeds, in under one hour.

Keywords

Felt Production , Lot Sizing , Machine Speed , Mixed-Integer Programming

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