Solid Waste Processing Facility Improvement Using Lean Principles and Simulation Modeling

• Author / Creator

  Ramadan, Mohamad

• Municipal solid waste (MSW) management presents a significant challenge, as current practices often lead to inefficiencies and substantial variability in waste processing. This variability contributes to increased downtime, reduced productivity, and higher operational costs. While previous research has targeted specific areas of waste management optimization, there remains a need for a comprehensive approach that addresses these challenges holistically across the entire waste processing system.

  This thesis introduces a framework aimed at analyzing and optimizing the operations of a municipal solid waste processing facility, grounded in Lean Thinking and Theory. The study utilized historical data from a solid waste management facility (SWMF), specifically its refuse-derived fuel (RDF) process, to test and validate the proposed framework.

  Using Lean tools such as Value Stream Mapping and Simulation Modelling, the study evaluated the current state of operations at the SWMF. These tools helped identify inefficiencies, and a base-case scenario was developed to serve as a benchmark for testing potential improvements. Key metrics such as downtime percentage, total runtime, and total throughput were analyzed. The study proposed three main interventions: implementing preventive maintenance, reducing repair times through better inventory management, and optimizing the use of the facility's dual processing lines to mitigate the impact of equipment breakdowns.

  In conclusion, the study provided a detailed analysis of the waste processing system at both micro and macro levels. Simulation modelling demonstrated that combining the proposed interventions could significantly reduce downtime, increase throughput, and improve overall operational efficiency. This case study offers a foundation for future research and the adoption of Lean practices in waste management facilities, with the potential to enhance sustainability and operational performance.

• Subjects / Keywords

  • Lean Interventions
  • Lean Manufacturing
  • Waste Processing
  • Simulation Modeling
  • Value Stream Map

• Graduation date

  Fall 2024

• Type of Item

  Thesis

• Degree

  Master of Science

• DOI

  https://doi.org/10.7939/r3-j0rp-hn26

• License

  This thesis is made available by the University of Alberta Library with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.