000			03951nam a22003377a 4500
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008			260216t20252025my a|||fr|||| 000 0 eng d
020			_aTHE0010342 (Local) _qHardback
040			_aUMPSA _beng _cUMPSA _erda
090			_aFTKPM .N39 2025 r Thesis
100	1		_aMohd Nazir Bin Mat Nawi, _eauthor.
245	1	0	_aEffect of waterjet cleaning parameters on mild steel surface during paint removal operation / _cMohd Nazir Bin Mat Nawi
264		1	_aKuantan, Pahang : _bUMPSA , _c2025
264		4	_c© 2025
300			_axix, 155 pages : _billustrations ; _c30 cm. + _e1 CD-ROM
336			_2rdacontent _atext
337			_2rdamedia _aunmediated
338			_2rdacarrier _avolume
347			_2rda _atext file _bPDF
500			_aFaculty of Manufacturing & Mechatronics Engineering Technology
502			_aThesis (Doctor of Philosophy) -- Universiti Malaysia Pahang - 2025
504			_aIncludes bibliographical references
520	3		_aAchieving efficient paint removal without damaging the surface is one of the primary areas of focus for paint removal operations in paint restoration. Traditional cleaning techniques, such as chemical and mechanical cleaning, are widely used to remove paint because they are convenient and affordable. However, these methods pose environmental risks and substrate damage, which may limit their future use. As a result, waterjet technology, an eco-friendly and non-traditional technique, has gained traction in the industry for its effectiveness and minimal impact on substrates. Research on waterjet cleaning input parameters mainly focuses on pressure, traverse rate, and standoff distance. The present study attempts to investigate the effect of new parameters, namely the number of cleaning passes and overlap rate during waterjet cleaning of the mild steel painted surface. Also, the impact of other typical parameters, such as hydraulic pressure and abrasive mass flow rate, was further analyzed using Response Surface Methodology (RSM). The quality of cleaned surfaces was investigated regarding surface roughness, topography, microstructure, material removal rate, and cleaning efficiency. Empirical models were developed to predict surface roughness, cleaning efficiency, and Material Removal Rate (MRR), with ANOVA confirming their consistency. These models showed strong correlations between measured and anticipated responses, with desirability functions providing optimal parameters, resulting in reliable surface roughness, cleaning rate, and MRR predictions. It became evident that neither the number of passes nor the overlap rate resulted as the primary parameters in optimizing the paint cleaning efficiency from the analysis of variance (ANOVA) and Pareto chart. The analysis of RSM identified that the optimal parameters for effective cleaning with minimal surface damage using abrasive waterjet cleaning are a pressure of 62 MPa, a single pass, and a 25% overlap rate with surface roughness of 3.557 μm, MRR of 0.189613 g/min and cleaning efficiency of 25 %. It was also observed that increasing the number of passes and overlap rate yielded only a slight decrease in surface roughness. This highlighted the complexity of the waterjet cleaning process in determining the efficacy of paint removal operation. This underscores the necessity for a comprehensive study of various parameters and their interactions to enhance the efficiency of the paint removal process for practical application which can be applied in improving process design and reducing cost. Keywords: paint removal, overlap rate, waterjet, surface roughness, surface topography, cleaning efficiency, microstructure.
610	2	0	_aFaculty of Manufacturing & Mechatronics Engineering Technology _xDissertations
650		0	_aUniversities and colleges _xDissertations
650		0	_aTheses _xDissertations
942			_2lcc _cTHESIS
999			_c104196 _d104202