OPTIMIZATION FOR STEAM BOILER PRODUCTION RATE WITH REGRESSION LINEAR APPROACH AT PT PUPUK KALIMANTAN TIMUR

• Main Author: Hardiyanto, Firsta
• Format: Theses
• Language: Indonesia
• Subjects: Manajemen umum
• Online Access: https://digilib.itb.ac.id/gdl/view/62906
• Institution: Institut Teknologi Bandung

PT Pupuk Kalimantan Timur is a subsidiary of PT Pupuk Indonesia (Persero) which has a production capacity of 3.43 million tons of urea per year, 2.74 million tons of ammonia per year, and 350 thousand tons of NPK per year. The company was initially managed by the state oil company (Pertamina) with facilities for a floating fertilizer plant or a plant on board ships. However, due to some technical considerations, the plant was transferred to land in accordance with presidential decree No. 43 in 1975 and then through presidential decree No. 39 in 1976, the management was handed over to the Ministry of Industry. In 2021, there are problems, namely the increase in the cost of goods manufactured (COGM) of urea which is quite significant with an increase of 23% compared to the beginning of 2021. After the root cause analysis, it is concluded that some of the contributing factors are the increase in gas prices, the increase in coal prices, and steam boiler production rate setting are not optimal. Because the increase in gas and coal prices is an external factor and cannot be controlled, this final project is carried out as a solution to obtain the most optimal rate setting of steam boiler. There are 8 units of steam boiler at PT Pupuk Kalimantan Timur with a total capacity of 1,130 tons/hour, but the average requirement for all plant is only 937 tons/hour, so a decision is needed for the value of the rate on each steam boiler. Each steam boiler has different characteristics, especially on the effect of the steam boiler rate on the requirement for gas and coal. In this case, using a forecasting method, namely linear regression to predict the amount of gas and coal needs at each steam boiler rate which is directly correlated to the cost of goods manufactured each steam boiler. This method is applied to a simulation that uses a solver to activate the rate of each steam boiler with the lowest target cost of goods manufactured of steam. From the optimization simulation results obtained, when all plants are running normally, it is recommended to minimize the rate on steam boiler which using coal as fuel.