Big Data Analytics of a Waste Recycling Simulation Logistics System

Abstract

Our paper is focused on data evaluation about the full recycling of waste by special statistical software and by using the principles of logistics. The paper goes further than the paper entitled "Environmental assessment of waste recycling based on principles of logistics and computer simulation design," which outputs a number of data that need to be reviewed and evaluated separately. Data, representing 15 types of waste for 5 years, enter the analysis. There were the types of waste that make up the most important part of the total waste production by means of descriptive statistics. Thanks to this, they were identified as the most important (from the production point of view) plastic granules with an average of 755.05 t/month, glass with an average of 672.233 t/month and paper with the average of 645.25 t/month. The persistence of particular waste type generation was examined by the variation coefficient in order to reduce the risk of supply of these secondary raw materials in the downstream supply chain. Selected waste elements can be considered relatively stable with a variation coefficient in the range 2.4-4.1%; the least stable type is electronic dust with a coefficient of variation of up to almost 23%.

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