Application of Fuzzy Time Series (FTS) Algorithm in Production Planning of Indonesia’s Oil Refining Company

Zakka Ugih Rizqi, Tommy Kurniawan, A. Khairunisa
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引用次数: 1

Abstract

Forecasting and aggregate planning are crucial phases in production planning especially for oil refining company that takes expensive production cost. Accurate forecasting greatly influences the success of production planning since it is the starting point of production planning. Whereas aggregate planning becomes important because it functions to bridge between the demand or production target with the existing resource requirements. Seeing the importance of accurate forecasting and aggregate planning, this research emphasizes the use of Fuzzy Time Series  (FTS) Algorithm to forecast Premium sales in Indonesia’s oil refining company. The comparison is also done between FTS with the other classical techniques in time series forecasting to test the reliability of algorithm and FTS outperforms the others based on the lowest MAPE value as much as 0.87%. FTS result is then used as an input in the aggregate planning by using heuristics method and comparing 3 strategies which are Level Strategy, Chase Strategy, and Hybrid Strategy. The result shows that Hybrid Strategy is the most efficient one because it produces the lowest production cost for three months production period as much as Rp 3,272,000,000.
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模糊时间序列(FTS)算法在印尼炼油公司生产计划中的应用
预测和总体规划是生产计划的关键环节,特别是对于生产成本较高的炼油企业而言。准确的预测是生产计划的起点,直接关系到生产计划的成功与否。而总体规划之所以重要,是因为它在需求或生产目标与现有资源需求之间起着桥梁的作用。鉴于准确预测和总体规划的重要性,本研究强调使用模糊时间序列(FTS)算法来预测印尼炼油公司的溢价销售。并将FTS与其他经典时间序列预测方法进行了比较,验证了算法的可靠性,在最小MAPE值为0.87%的基础上,FTS优于其他方法。然后使用启发式方法将FTS结果作为总体规划的输入,并比较3种策略,即水平策略,追逐策略和混合策略。结果表明,混合策略在三个月的生产周期内生产成本最低,为32.72亿卢比,是最有效的混合策略。
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