Prediction to Industrial Waste Disposal Management by Using Box-Jenkins Method and Created Applications for a Company A and Their Service Providers in Thailand

摘要

The purpose of this study is to develop two sets of forecasting models for four kinds of wastes: AA waste (Absorbents, filtered waste), BB waste (Plastics), CC waste (Discarded organic chemicals) and DD waste (Sludge from treatment process). The first set of forecasting models is developed for Company A, which is a waste generator, and the second set for the four service providers who supply transport and waste disposal services. The output of their forecasting models is performed on an Excel application for planning, implementation and assets control as well as physical facilities and financial investment for both Company A and the four service providers. The method selected uses Box-Jenkins method with data periods from January 2008 to December 2016 (108 series data) for Company A and from January 2008 to December 2017 (120 series data) of their service providers. After studying these data (four types of waste) using Minitab, fitted models for generating best forecasting values of Company A are ARIMA (2, 1, 0) or ARI (2,1) for AA waste, ARIMA (0, 0, 1) or MA (1) for BB waste, ARIMA (3, 2, 2) for CC waste and ARIMA (3, 0, 3) or ARMA (3, 3) for DD waste. The results of forecasting the wastes of Company A had RMSE of 467.61, 518.80, 1,691.16 and 1,102.80, respectively, which is lower than another research paper (11,551.77). Also the forecasting values for service providers are ARIMA (1, 0, 1) for Contaminated waste, ARIMA (1, 0, 0) or AR (1) for Monomer waste, ARIMA (1, 0, 2) or ARMA (1,2) for Used Solvents waste and ARIMA (1, 1, 0) or ARI (1, 1) for Wastewater. The results of forecasting the wastes had RMSE (Root Mean Square Error) (0.388, 0.047, 0.060 and 0.043 respectively) lower than the other research paper (1.305). For reliable forecasting, these models can generate valuable forecasts for the company and its service providers to utilize their budget of money, assets, and facilities in created applications.