Application of Fourier grey model (FGM) for demand forecasting and Markov chain method for inventory planning

Based on the original Grey Model GM(1,1), the forecast accuracy of GM(1,1) have been modified using Fourier Series called FGM(1,1) to predict the demand of air compressor of compressor manufacturing industry. Markov Chain method have also been adopted to determine the optimal inventory with the mini...

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Bibliographic Details
Main Authors: Puspitasari, F., Saraswati, D., Shabrina, Z.
Format: Conference Proceeding
Language:English
Subjects:
Accuracy
Air compressors
Demand
Forecasting
Fourier series
Markov analysis
Markov chains
Mathematical models
Minimum cost
Time series
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Summary:Based on the original Grey Model GM(1,1), the forecast accuracy of GM(1,1) have been modified using Fourier Series called FGM(1,1) to predict the demand of air compressor of compressor manufacturing industry. Markov Chain method have also been adopted to determine the optimal inventory with the minimum cost. The first step in this research is to determine the forecast value of demand for July 2020- December 2020 based on time series data in August 2019-June 2020. The calculation results showed that Fourier Series Grey Model (FGM) works better than the original GM(1,1), as evidenced by the better level accuracy of FGM(1,1) which are 9.66% of MAPE and 10.14% of RMSPE, while GM(1,1) gives 18.83% of MAPE and 23.64% of RMSPE. The next step is using time series data in August 2019-June 2020 and FGM forecasting results for inventory planning using Markov Chain Method. The results of the optimal inventory level can reduce the cost by 23%-64% of the company's current inventory cost.
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0105234