Currently, more than 80% of the waste management costs are attributed to the waste collection phase. In order to reduce these costs, one current solution resides in the implementation of waste transfer stations. In these stations, at least 3 collection vehicles transfer their load into a larger hauling truck. This cost reduction is based on the principle of economy of scale applied to the transportation sector. This solution improves the efficiency of the system; nevertheless, it does not optimize it. Recent studies show that the compactor trucks used in the collection phase generate significant economic losses mainly due to the frequent stops and the transportation to transfer stations often far from the collection area. This study suggests the restructuring of the waste collection process by dividing it into two phases: the collection phase, and the transportation to the transfer station phase. To achieve this, a deterministic theory called: “the Constructal Theory” (CT) is used. The results show that starting a certain density threshold, the application of the CT minimizes energy losses in the system. In fact, the collection is optimal if it is done using a combination of low capacity vehicle to collect door to door and transfer their charge into high-capacity trucks. These trucks will then transport their load to the transfer station. To minimize the costs of labor, this study proposes the use of Cybernetic Transport System (CTS) as an automated collection vehicle to collect small amounts of waste. Finally, the optimization method proposed is part of a decentralized approach to the collection and treatment of waste. This allows the implementation of multi-process waste treatment facilities on a territory scale.
| Date | 18 Sept 2012 |
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| Original language | French |
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| Awarding Institution | - École de technologie supérieure
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| Supervisor | Robert Hausler (Supervisor) & Mathias Glaus (Co-supervisor) |
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Al-Maalouf, G. (Author),
Hausler (Supervisor) &
Glaus (Co-supervisor),
18 Sept 2012Student thesis: Master's thesis › Master in Engineering: Engineering