Browsing by Author "Rabothata, Mahlatse Solomon"

Now showing 1 - 2 of 2

Effects of Ni-Mo binder and laser surface engineering of NbC based cutting inserts during face-milling of automotive grey cast iron
(University of the Witwatersrand, Johannesburg, 2024) Rabothata, Mahlatse Solomon; Genga, Rodney; Polese, Claudia
The main aim of this study was to design, develop and produce NbC-Ni cermet based cutting inserts as potential substitutes for conventional WC-Co based inserts for the face-milling machining of automotive grey cast iron (a-GCI), an alloy that plays a critical role in the automotive manufacturing industry. For this purpose, rapid pulsed electric current sintering (PECS), additions of Mo as a partial binder replacement and TiC and TiC 7 N3 as secondary hard phases, and femtosecond laser surface modification (LSM) technique were used in an effort to enhance the NbC-Ni based cutting inserts’ machining capabilities during face-milling of a- GCI. All the sintered samples achieved relative densities of 97% and above, irrespective of the sintering process. Adding Mo, TiC and TiC 7 N3 to the NbC-12Ni (wt%) composition refined the NbC grain size in PECS samples, enhancing hardness and wear resistance. Mechanical impact shock and wear resistance of inserts were further improved via femtosecond LSM, creating pyramid (P) LSM and shark skin (S) LSM based micro-patterns on the surface of the cutting inserts. Face milling machining tests of a-GCI were performed at 200-400 m/min cutting speed (𝑉𝑉𝑐𝑐) and 0.25-1.0 mm depth of cut (ap ). The inserts’ cutting-edge wear and failure were evaluated after every pass using optical microscopy and analysed via high angular annular dark field (HAADF)-scanning electron transmission microscopy (STEM). Machining performance was assessed by technique for order of preference by similarity to ideal solution (TOPSIS) based model using insert tool life (𝐼𝐼𝑙𝑙), specific cutting energy (𝑈𝑈𝑐𝑐) and maximum resultant cutting forces (Fmax ) as criteria and including surface roughness (Ra) during finishing operations. The pyramid LSM PECS NbC-10TiC-12N[Ni/Mo] (wt%) (R2MS-P1) insert was the top performer during semi-finishing, with 20 min 𝐼𝐼𝑙𝑙 , 22 J/mm 3 𝑈𝑈𝑐𝑐 and 1087 N Fmax , obtaining an overall preference score (𝑂𝑂𝑖𝑖) of 0.953. The best inserts during finishing 2 were the blank (B) (i.e. unmodified cutting edge) PECS NbC-10TiC 7 N3 -12Ni (wt.%) (TCN1S-B3) and LPS WC-10TiC-10[Co/Mo] (wt.%) (T1ML-B3) inserts with both inserts obtaining 𝑂𝑂𝑖𝑖s of 0.826, respectively. In general, additions of Mo, TiC, TiC7 N3 , PECS and LSM improved hardness and abrasion wear resistance, resulting in enhanced performance of NbC-Ni based cutting inserts during machining.
Optimum design parameters and mechanical properties of polymeric nanocomposites using NSGA-II optimization method
(2018) Rabothata, Mahlatse Solomon
The aim of this work was to develop a method for optimizing both design parameters and mechanical properties of polymer based nanocomposites using numerical multi-objective optimization (MOO) methods. The main objective was to simultaneously maximize the elastic modulus and the tensile strength of nanocomposites. The rationale behind focusing on these particular properties is that they play a signiﬁcant role in designing of materials for structural applications. Ji and Zare models of determining the elastic modulus and tensile strengths of polymeric nanocomposite materials were respectively used for the formation of the objective functions for numerical optimization. The design variables (i.e major factors aﬀecting the given mechanical properties) were identiﬁed as the diameter of nanoﬁllers, thickness of the interphase region, nanoﬁllers loading as weight fraction, elastic modulus of the interphase, interfacial shear stress and the orientation factor of the nanoﬁllers. The Fast Non-dominated Sorting Genetic Algorithm (NSGA-II) approach in MATLAB was used to maximize the objective functions by obtaining the optimum solutions of the given design variables. The optimization model was able to successfully ﬁnd optimum solutions of the design variables. Furthermore, the overall optimization results were found to be in good agreement with the available experimental results from literature. The proposed optimization model was found to be signiﬁcantly accurate in ﬁnding the optimum values of the design variables for improving the mechanical properties of nanocomposites. The optimum values of the design variables were determined to be 2.12 – 2.96 nm for the thickness of the interphase, 5.41 – 7.01 nm for the diameter of the nanoﬁllers, 2.95 – 4.69 wt.% for the nanoﬁllers loading, and 1 for the nanoﬁllers orientation factor. In addition, the results further showed that nano-reinforcements such as multi-wall car-bonnanotubes(MWCNTs)yields high elastic modulus of the interphase and interfacial shear stress.