Metric-based assessment of sustainability performance in the silica manufacturing process / Mohammad Khairil Izhan Bin Anuar
Material type:
TextPublisher: Kuantan, Pahang : UMPSA, 2025Copyright date: © 2025Description: xvi, 168 pages : illustrations ; 30 cm. + 1 CD-COMContent type: - text
- unmediated
- volume
- THE0010373 (Local)
| Item type | Current library | Call number | Status | Date due | Barcode | |
|---|---|---|---|---|---|---|
Thesis
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UMPLIB PEKAN | FTKPM .K43 2025 r Thesis (Browse shelf(Opens below)) | Not for loan | T000004040 | ||
Thesis
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UMPLIB PEKAN | CD13932 (Browse shelf(Opens below)) | Final Processing | T000004041 |
Faculty of Manufacturing and Mechatronic Engineering Technology
Thesis (Master of Science) -- Universiti Malaysia Pahang - 2025
Includes bibliographical references
Contemporary manufacturing practices profoundly influence environmental, economic, and societal aspects of sustainability. Despite various sustainability assessment methodologies, few address all three dimensions comprehensively. Moreover, scarce methods account for both stochastic and fuzzy uncertainties simultaneously, particularly in the context of the silica manufacturing sector. In Malaysia, while manufacturing holds significance in economic and technological realms, its adoption of sustainability practices remains lacking. Thus, this research aims to devise a robust stochastic-fuzzy sustainability assessment framework tailored for the silica manufacturing sector. The methodology involves a structured four-step process. First, an extensive literature review identified research gaps and informed the development of sustainability indicators. Using the Delphi method, 43 weighted sustainability indicators across environmental, economic, and social dimensions were validated through two rounds of expert consensus, with a 75% agreement threshold. The framework integrates both quantitative and qualitative metrics by employing Monte Carlo simulation for stochastic uncertainties and fuzzy logic (using a Mamdani inference system) for fuzzy uncertainties. Quantitative indicators were modeled using Monte Carlo simulation, while qualitative indicators were assessed through fuzzy logic, combining outputs to generate a comprehensive Triple Bottom Line (TBL)-based sustainability index. Case studies within the manufacturing domain, including real-world data collected through site visits, interviews, and documentation reviews, validated the method’s robustness. The application of the framework to a representative case company yielded a sustainability index of 1.95, demonstrating its practicality in assessing sustainability performance amidst complex uncertainties. This integrated approach facilitates internal decision-making within manufacturing entities and offers a practical tool for benchmarking and improving sustainability practices. Ultimately, this research advances understanding of sustainable silica manufacturing and provides actionable insights for enhancing sustainability performance in silica manufacturing organizations.