000			03241nam a22003377a 4500
003			MY-KuUP
005			20260101130319.0
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007			ta
008			260101t20252025my a|||fr|||| 000 0 eng d
020			_aTHE0010206 (Local) _qHardback
040			_aUMPSA _beng _cUMPSA _erda
090			_aFTKPM .A97 2025 r Thesis
100	0		_aMuhammad Nor Azril Bin Zulkafli, _eauthor.
245	1	0	_aInvestigation of materials for components of brushed DC machine using vikor method for a thermal performance / _cMuhammad Nor Azril Bin Zulkafli
264		1	_aKuantan, Pahang : _bUMPSA, _c2025
264		4	_c© 2025
300			_axii, 125 pages : _billustrations (some color) ; _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		_aSmall brushed DC motors are widely used in low-power applications due to their simplicity and affordability. However, thermal inefficiencies such as insulation failure and magnet demagnetization remain a key challenge, often leading to reduced lifespan and increased electronic waste. Addressing these issues is crucial for improving motor reliability and sustainability. While design and topology modifications have been explored, they are often costly and complex. As an alternative, this study proposes a cost-effective framework focused on optimizing material selection to enhance thermal performance. The VIKOR (VIšekriterijumsko KOmpromisno Rangiranje) multi-criteria decision-making method was applied to evaluate and rank different material combinations based on thermal, mechanical, magnetic, and cost criteria. VIKOR’s compromise-ranking approach enables balanced decision-making under conflicting objectives. To assess thermal performance, a Lumped Parameter Thermal Network (LPTN) model was developed and experimentally validated. LPTN models heat transfer in the motor using simplified thermal resistances and capacitances, providing efficient and accurate simulations. The model, tailored to the MY1016 motor, achieved a maximum temperature prediction error of just 3.5%. Results showed a significant reduction in winding temperature by 20°C during a 5A copper loss test using the optimized material combination. The selected materials were: Ferrite magnets, Al 356-T6 casing, Chrome steel bearings, metal graphite brushes, and Nylon insulation. This configuration improved thermal performance without compromising magnetic properties or increasing costs. In conclusion, this study demonstrates that systematic material selection using the VIKOR method, combined with LPTN modeling, offers a practical and scalable approach to improving the thermal efficiency of small brushed DC motors, without the need for major design changes.
610	2	0	_aFaculty of Manufacturing and Mechatronic Engineering Technology _xDissertations
650		0	_aUniversities and colleges _xDissertations
650		0	_aTheses _xDissertations
942			_2lcc _cTHESIS
999			_c103824 _d103830