TY - GEN
T1 - Development mathematics model production planning of urea fertilizer to minimize production cost with mixed integer linear programming (MILP)
AU - Hakim, Inaki Maulida
AU - Sari, Givanny Permata
AU - Ardina, Aloysia Elva
N1 - Publisher Copyright:
© 2019 Author(s).
PY - 2019/12/18
Y1 - 2019/12/18
N2 - Food is a necessity that must be met at all times. As it is known that fertilizer is one of the main factors in the success of food security in Indonesia. Currently, the government is targeting food self-sufficiency in 2017 that requires harvesting capability at least twice a year in the area of paddy fields in Indonesia. To meet the fertilizer needs in Indonesia, the whole fertilizer industry must continue to improve its production. In the fertilizer industry studied, there is a problem in the production section, where the industry is not able to meet the demand for urea fertilizer which in fact is the industry's flagship product. The inability to meet this demand resulted in insufficient revenue to be achieved. In this research, urea fertilizer production planning with Material Requirement Planning (MRP) method, Mixed Integer Linear Programming (MILP), and forecasting is planned. The results of this study indicate that the appropriate MRP method to be used as production planning in the fertilizer industry is Lot-For-Lot (LFL) and the most accurate demand forecasting method and according to the demand trend of urea is Artificial Neural Network (ANN). Furthermore, the total cost that is spent by the fertilizer industry is decreasing into Rp. 55.334.120,- or decreased by 5,15% from the previous one.
AB - Food is a necessity that must be met at all times. As it is known that fertilizer is one of the main factors in the success of food security in Indonesia. Currently, the government is targeting food self-sufficiency in 2017 that requires harvesting capability at least twice a year in the area of paddy fields in Indonesia. To meet the fertilizer needs in Indonesia, the whole fertilizer industry must continue to improve its production. In the fertilizer industry studied, there is a problem in the production section, where the industry is not able to meet the demand for urea fertilizer which in fact is the industry's flagship product. The inability to meet this demand resulted in insufficient revenue to be achieved. In this research, urea fertilizer production planning with Material Requirement Planning (MRP) method, Mixed Integer Linear Programming (MILP), and forecasting is planned. The results of this study indicate that the appropriate MRP method to be used as production planning in the fertilizer industry is Lot-For-Lot (LFL) and the most accurate demand forecasting method and according to the demand trend of urea is Artificial Neural Network (ANN). Furthermore, the total cost that is spent by the fertilizer industry is decreasing into Rp. 55.334.120,- or decreased by 5,15% from the previous one.
KW - Artificial Neural Network
KW - Auto-Regressive Integrated Moving Average
KW - demand forecasting
KW - Lot-For-Lot
KW - Material Requirement Planning
KW - Mixed Integer Linear Programming
KW - production planning
UR - http://www.scopus.com/inward/record.url?scp=85077684551&partnerID=8YFLogxK
U2 - 10.1063/1.5139768
DO - 10.1063/1.5139768
M3 - Conference contribution
AN - SCOPUS:85077684551
T3 - AIP Conference Proceedings
BT - 2nd International Conference on Science, Mathematics, Environment, and Education
A2 - Indriyanti, Nurma Yunita
A2 - Ramli, Murni
A2 - Nurhasanah, Farida
PB - American Institute of Physics Inc.
T2 - 2nd International Conference on Science, Mathematics, Environment, and Education, ICoSMEE 2019
Y2 - 26 July 2019 through 28 July 2019
ER -