Optimisasi Perencanaan Strategis Kapasitas Produksi Pelumas Otomotif Menggunakan Teknik Stokastik Algorithm

Faza, Nuha (2019) Optimisasi Perencanaan Strategis Kapasitas Produksi Pelumas Otomotif Menggunakan Teknik Stokastik Algorithm. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Salah satu industri yang diperkirakan akan mengalami peningkatan setiap tahunnya adalah industri pengolahan pelumas. Beberapa faktor yang mendorong peningkatan permintaan pelumas yaitu peningkatan jumlah kendaraan bermotor, perkembangan infrastruktur (terutama industri otomotif), dan ekonomi. Performansi perusahaan manufaktur dapat diukur berdasarkan efisiensi dan efektivitas pada rantai pasokan perusahaan. Rantai pasokan yang efektif dan efisien diukur dari performansi pengiriman, kualitas produk, backorder dan level persediaan. Rantai pasokan yang kompleks diatur dengan memaksimalkan Net Present Value (NPV) dari arus kas. NPV dipengaruhi oleh biaya investasi dan rantai pasokan perusahaan. Pada tugas akhir ini dilakukan perencanaan strategis kapasitas produksi dengan merancang jaringan syaraf tiruan untuk menentukan prediksi permintaan pelumas 10 tahun kedepan serta melakukan optimalisasi terhadap NPV hasil perencanaan strategis yang telah dilakukan menggunakan metode genetic algorithm. Nilai NPV yang didapatkan setelah optimisasi adalah sebesar Rp. 726.982.256.617 untuk peralatan otomatis dan Rp. 726.074.798.898 untuk peralatan semi-otomatis. Pada perencanaan ini nilai yang sangat memengaruhi besar NPV adalah biaya operasional, investasi dan biaya rantai pasokan. Pada perencanaan semua teknologi yang disarankan memiliki nilai NPV lebih dari nol sehingga pembelian teknologi disarankan untuk dilakukan, namun berdasarkan hasil NPV terbesar penambahan teknologi otomatis lebih disarankan. ================================================================================================ Industry that is expected to increase every year is the lubricant processing industry. There are several factors led to an increase in demand for lubricants, an increase in the number of motorized vehicles, the development of infrastructure (especially the automotive industry), and the economy. Manufacturing company performance can be measured based on efficiency and effectiveness in the company's supply chain. Effective and efficient supply chains are measured by shipping performance, product quality, backorders and inventory levels. NPV is influenced by investment costs and the company's supply chain. In this research, the strategic planning of production capacity by designing the artificial neural network to determine the prediction of lubricant demand 10 years ahead as well as to optimize the NPV of strategic planning result which has been done using genetic algorithm method. The NPV value obtained after the optimization is Rp. 726.982.256.617 for automatic equipment and Rp. 726.074.798.898 for semi-automatic equipment. In this planning, the value that greatly affects the NPV is the cost of operational, investation and the supply chain cost. In planning all the recommended technologies have NPV values of more than zero so purchasing technology is recommended to do but based on the greatest NPV result the addition of automated technology is more preferable.

Item Type: Thesis (Undergraduate)
Additional Information: RSF 658.401 2 Faz o-1 2019
Uncontrolled Keywords: Pelumas, NPV, Jaringan Syaraf Tiruan, Genetic Algorithm
Subjects: H Social Sciences > HD Industries. Land use. Labor > HD30.28 Planning. Business planning. Strategic planning.
Q Science > QA Mathematics > QA273.5 Stochastic geometry
Q Science > QA Mathematics > QA402.5 Genetic algorithms.
Q Science > QA Mathematics > QA76.87 Neural networks (Computer Science)
Q Science > QA Mathematics > QA9.58 Algorithms
T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL210 Automobiles--Lubrication systems.
T Technology > TS Manufactures > TS155 Production control. Production planning. Production management
Divisions: Faculty of Industrial Technology and Systems Engineering (INDSYS) > Physics Engineering > 30201-(S1) Undergraduate Thesis
Depositing User: Faza Nuha
Date Deposited: 06 Jan 2022 08:08
Last Modified: 06 Jan 2022 08:08
URI: https://repository.its.ac.id/id/eprint/61921

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