Statistical Analysis of Determinant Factors and Framework Development for the Optimal and Sustainable Design of Municipal Solid Waste Management Systems in the Context of Industry 4.0

摘要

Municipal Solid Waste (MSW) generated by various natural and manmade products consumed by humans and other living creatures is amongst the most critical issues that often lead to environmental and health concerns. Within the waste management industry, there are several factors that have to be considered when a particular city needs to develop an optimal system for the collection, treatment and dispo sal of its MSW; and these factors differ from one city to another. Reflecting on the current trend of thinking with the Industry 4.0 in line with internet of things (IOT), Artificial Intelligence (AI), Big Data, etc. designing an optimal and sustainable Municipal Solid Waste Management System (MSWMS) has become even more challenging and city-specific. The aim of this paper is to statistically analyze demographic, geographic, economic and technical parameters that substantially affect the design of an optimal and sustainable MSWMS in the context of the fourth Industrial Revolution. South Africa is considered as a case study, and a statistical analysis methodology was applied using Microsoft Excel 2016. The analysis generated the regression equation as well as the correlation between municipal waste production and the economic, demographic and geographic variables. Finally, the paper presents a conceptual framework for the design of an optimal MSWMS for a developing city, in the context of Industry 4.0. The paper makes mainly use of secondary data collected from previous articles, official governmental reports, and Census to conduct the statistical analysis. The literature review revealed that the quantity of waste generated, available air space, city roads traffic, the distance between municipal waste production nodes and different waste treatment (disposal) facilities, the capacity of waste transportation vehicles are among the most critical parameters for the optimal design of MSWMS; and the results of this study showed that the most determinant factors impacting these parameters are the city's Gross Domestic Product contribution and its population density.