Yuantoro, Faldy Maulana (2018) Optimasi Multiple Can-Order Level pada Can-Order Policy Menggunakan Algoritma Simulated Annealing (Studi Kasus: Spare Part Inventory PT Indonesia Asahan Aluminium (Persero)). Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
|
Text
02411440000047_Undergraduate_Theses.pdf - Accepted Version Download (6MB) | Preview |
Abstract
Persediaan merupakan stok dari barang-barang yang disimpan dan akan digunakan di masa yang akan datang. Salah satu permasalahan yang terjadi adalah apabila permintaan pada suatu item tergolong permintaan yang intermittent. Kebijakan persediaan pada jenis permintaan tersebut sulit untuk ditentukan karena pola pemintaan yang tidak pasti sehingga tingkat kesalahan prediksinya besar. Permasalahan jenis permintaan tersebut muncul pada kebutuhan spare part di PT Indonesia Asahan Aluminium (Persero). Untuk mengatasinya, model kebijakan can order policy menggunakan multiple can-order level (si, cij, Sij) dapat menyelesaikan permasalahan dengan joint replenishment untuk mengkoordinasikan pesanan antar item. Model tersebut diketahui merupakan integer non-linear programming (INLP) yang dapat digolongkan ke dalam permasalahan NP-Hard. Pendekatan metaheuristik yaitu simulated annealing akan digunakan untuk mendapatkan solusi yang memuaskan dengan waktu penyelesaian yang cepat. Metode Global Criterion juga akan digunakan untuk mendapatkan fungsi multi objective, yaitu meminimasi total biaya persediaan dan meminimasi jumlah carrier supplier. Berdasarkan eksperimen dengan 3 supplier dam 157 item didapatkan hasil yang lebih baik dari kebijakan persediaan di PT INALUM (Persero) dengan adanya penghematan dari kondisi eksisting yang diterapkan perusahaan sebesar 2.6% pada jumlah carrier dan penghematan biaya sebesar 14.43% atau sebesar $81,570.79 (Rp 1,060,420,270). ==================================================================================================== Inventory is the stock of goods that is stored and will be used for the future needs. One of the problems that occurs is when the demand on an item belongs to an intermittent request. Inventory policy on this type of demand is difficult to be determined due to an uncertain demand pattern, so that the predictive error rate is increased. This type of demand problem arises on the needs of spare parts at PT Indonesia Asahan Aluminium (Persero). To overcome this problem, the can order policy model using multiple can-order level (si, cij, Sij) is able to solve joint replenishment problem to coordinate orders between items. The can order policy model built is in the form of integer non-linear programming (INLP) that can be classified into NP-Hard problems. The metaheuristic approach, Simulated Annealing, will be used to obtain a satisfied solution with a fast computation time to solve the model built. The Global Criterion method will also be used to obtain multi-objective functions, which can minimize total inventory cost and supplier carrier quantity. Based on experiments with 3 suppliers and 157 items, a better result of the inventory policy at PT INALUM (Persero) is obtained with savings from existing conditions applied by the company of 2.6% on carrier amount and cost savings of 14.43% or $ 81,570.79 (Rp 1,060,420,270).
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Additional Information: | RSI 658.787 Yua o-1 |
| Uncontrolled Keywords: | multiple can-order level; can order policy; spare part; simulated annealing; metaheuristik; multiple can-order level; can order policy; spare part; simulated annealing; metaheuristics |
| Subjects: | H Social Sciences > HD Industries. Land use. Labor > HD55 Inventory control Q Science > QA Mathematics > QA76.9 Computer algorithms. Virtual Reality. Computer simulation. T Technology > TJ Mechanical engineering and machinery > TJ217.6 Predictive Control T Technology > TS Manufactures > TS167 Costs, Industrial |
| Divisions: | Faculty of Industrial Technology > Industrial Engineering > 26201-(S1) Undergraduate Thesis |
| Depositing User: | Faldy Maulana Yuantoro |
| Date Deposited: | 16 Mar 2018 06:34 |
| Last Modified: | 23 Sep 2020 02:47 |
| URI: | https://repository.its.ac.id/id/eprint/49992 |
Actions (login required)
 |
View Item |
