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008			260223t20252025my a|||fr|||| 000 0 eng d
020			_aTHE0010373 (Local) _qHardback
040			_aUMPSA _beng _cUMPSA _erda
090			_aFTKPM .K43 2025 r Thesis
100	0		_aMohammad Khairil Izhan Bin Anuar, _eauthor.
245	1	0	_aMetric-based assessment of sustainability performance in the silica manufacturing process / _cMohammad Khairil Izhan Bin Anuar
264		1	_aKuantan, Pahang : _bUMPSA, _c2025
264		4	_c© 2025
300			_axvi, 168 pages : _billustrations ; _c30 cm. + _e1 CD-COM.
336			_2rdacontent _atext
337			_2rdamedia _aunmediated
338			_2rdacarrier _avolume
347			_2rda _atext file _bPDF
500			_aFaculty of Manufacturing and Mechatronic Engineering Technology
502			_aThesis (Master of Science) -- Universiti Malaysia Pahang - 2025
504			_aIncludes bibliographical references
520	3		_aContemporary 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.
610	2	0	_aFaculty of Manufacturing and Mechatronic Engineering Technology _xDissertations
650		0	_aUniversities and colleges _xDissertations
942			_2lcc _cTHESIS
999			_c104225 _d104231