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Stochastic Inventory Management of Circular Supply Chain in Indonesia Waste-Processing Company using Monte Carlo Simulation
Abstrak (Bhs. Indonesia)
In the production process of waste products called holzewig and batasip, an Indonesia Waste-Processing Company requires inorganic waste raw materials and defective holzewig products. However, in reality, the arrival of these waste raw materials cannot be precisely determined in terms of quantity per day and is mixed between organic and inorganic. As a result, the control of inventory for organic and inorganic waste raw materials, as well as defective Holzewig products, becomes more complex. Inventory management of these waste raw materials will be conducted using Monte Carlo Simulation to obtain forecasting results for the arrival of organic and inorganic waste, as well as the quantity of defective products in the following periods. Based on the simulation results, the company should eliminate at least 64 kg of organic waste per day, produce 43 kg of Holzewig per day, and produce 34 kg of defective Holzewig products per day. With these targets, the company can maintain inventory capacity to avoid overstocking or even understocking. A simple application using Python programming with the PyQt module has also been created to predict the arrival of waste and defective products based on Monte Carlo Simulation. With this application, the company only need to input the necessary historical data to perform simulations.
Abtrak (Bhs. Inggris)
In the production process of waste products called holzewig and batasip, an Indonesia Waste-Processing Company requires inorganic waste raw materials and defective holzewig products. However, in reality, the arrival of these waste raw materials cannot be precisely determined in terms of quantity per day and is mixed between organic and inorganic. As a result, the control of inventory for organic and inorganic waste raw materials, as well as defective Holzewig products, becomes more complex. Inventory management of these waste raw materials will be conducted using Monte Carlo Simulation to obtain forecasting results for the arrival of organic and inorganic waste, as well as the quantity of defective products in the following periods. Based on the simulation results, the company should eliminate at least 64 kg of organic waste per day, produce 43 kg of Holzewig per day, and produce 34 kg of defective Holzewig products per day. With these targets, the company can maintain inventory capacity to avoid overstocking or even understocking. A simple application using Python programming with the PyQt module has also been created to predict the arrival of waste and defective products based on Monte Carlo Simulation. With this application, the company only need to input the necessary historical data to perform simulations.
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