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Reliability analysis for multiple-stage solid waste management systems.

Cheng Cheng1, Rui Zhu1, Russell G Thompson2

  • 1Future Urban Mobility IRG, Singapore-MIT Alliance for Research and Technology, 1 CREATE Way, #09-02 CREATE Tower, Singapore 138602, Singapore.

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|November 27, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces a reliability analysis method to manage uncertainties in solid waste management (SWM) systems. The approach optimizes waste treatment allocation to enhance system reliability and reduce risks.

Keywords:
Event-tree analysisOptimisationReliability analysisSolid waste management

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Area of Science:

  • Environmental Engineering
  • Operations Research
  • Sustainability Science

Background:

  • Solid waste management (SWM) is crucial for sustainable development and environmental protection.
  • Waste collection and transportation (WCT) are vital steps in SWM.
  • Optimizing waste transfer stations (WTSs) and final disposal facilities (FDFs) is critical for effective SWM.

Purpose of the Study:

  • To propose a reliability analysis method for managing uncertainties in multi-stage SWM systems.
  • To develop an optimization model for maximizing SWM system reliability.
  • To analyze failure modes and assess policy impacts on SWM reliability.

Main Methods:

  • Application of reliability analysis to SWM systems.
  • Development of an optimization model for waste treatment allocation.
  • Utilizing an event-tree to analyze system failure modes.
  • Case study in Hong Kong to validate the methodology.

Main Results:

  • The proposed method effectively estimates the risk level of SWM systems.
  • It provides solutions to improve system reliability and reduce risks.
  • The approach can analyze policy contributions to reliability and identify critical facilities.

Conclusions:

  • Reliability analysis is a valuable tool for managing uncertainties in SWM.
  • The optimization model enhances SWM system performance and resilience.
  • The methodology offers practical insights for SWM planning and policy-making.