Achieving the Minimum Roughness of Laser Milled Micro-Impressions on Ti 6Al 4V, Inconel 718, and Duralumin.

Titanium-aluminium-vanadium (Ti 6Al 4V) alloys, nickel alloys (Inconel 718), and duraluminum alloys (AA 2000 series) are widely used materials in numerous engineering applications wherein machined features are required to having good surface finish. In this research, micro-impressions of 12 µm depth are milled on these materials though laser milling. Response surface methodology based design of experiment is followed resulting in 54 experiments per work material. Five laser parameters are considered naming lamp current intensity (I), pulse frequency (f), scanning speed (V), layer thickness (LT), and track displacement (TD). Process performance is evaluated and compared in terms of surface roughness through several statistical and microscopic analysis. The significance, strength, and direction of each of the five laser parametric effects are deeply investigated for the said alloys. Optimized laser parameters are proposed to achieve minimum surface roughness. For the optimized combination of laser parameters to achieve minimum surface roughness (Ra) in the titanium alloy, the said alloy consists of I = 85%, f = 20 kHz, V = 250 mm/s, TD = 11 µm, and LT = 3 µm. Similarly, optimized parameters for nickel alloy are as follows: I = 85%, f = 20 kHz, V = 256 mm/s, TD = 8 µm, and LT = 1 µm. Minimum roughness (Ra) on the surface of aluminum alloys can be achieved under the following optimized parameters: I = 75%, f = 20 kHz, V = 200 mm/s, TD = 12 µm, and LT = 3 µm. Micro-impressions produced under optimized parameters have surface roughness of 0.56 µm, 2.46 µm, and 0.54 µm on titanium alloy, nickel alloy, and duralumin, respectively. Some engineering applications need to have high surface roughness (e.g., in case of biomedical implants) or some desired level of roughness. Therefore, validated statistical models are presented to estimate the desired level of roughness against any laser parametric settings.

Minimizing the Micro-Edge Damage at Each Constituent Layer of the Clad Composite during AWJM.

The development of layered/clad composites with a blend of desired characteristics has emerged as a valuable substitute for expensive materials. The inherent heterogeneity offers challenges whenever the cutting of cladded plates/sheets is to be done. The conventional means of cutting such as gas/plasma arc yield a poor cut quality and heat-affected zones. Abrasive waterjet machining (AWJM) is a valuable alternative to mitigate the aforesaid cutting issues. However, the intrinsic attribute of edge damage during AWJM poses a limitation on its use, especially for precision applications. Specifically, it is challenging to control the edge damage in terms of pit depth at both the constituent clad layers and addressing this challenge is the novelty of this work. The said cutting accuracy issues have been thoroughly investigated herein. Four key control parameters of AWJM have been selected for evaluating their impact during machining of stainless-clad steel using L18 Taguchi design. Experimental results have been thoroughly examined using statistical and microscopical evidence. The optimal parametric combination resulting in the minimum magnitude of pit depth at both the clad layers has been developed and experimentally validated. The magnitude of pits depth realized at stainless steel layer (SSL) and mild steel layer (MSL) significantly reduced to 5 µm and 4 µm respectively, at the optimal parametric combination.

Comparison of Laser Milling Performance against Difficult-To-Cut Alloys: Parametric Significance, Modeling and Optimization for Targeted Material Removal.

During laser milling, the objective is not always to maximize the material removal rate (MRR). Milling of new material with targeted MRR is challenging without prior knowledge and established sets of laser parameters. The laser milling performance has been evaluated for three important aerospace alloys, i.e., titanium alloy, nickel alloy and aluminum alloy using the response surface method experimental plan (54 experiments for each alloy). Parametric effects of five important laser parameters, statistical analysis (main effects, interaction effects, strength and direction of effects), mathematical modeling and optimality search is conducted for the said alloys. Under the non-optimized laser parameters, the actual MRR significantly varies from the targeted MRR. Variation in the aluminum alloy is at the top as compared to the other two alloys. Among other significant terms, three terms have the largest effect on MRR in the case of TiA, two terms in the case of NiA, and five terms in the case of AlA. Under the optimized sets of laser parameters, the actual material removal highly close to the desired level (100%) can be achieved with minimum variation in all the three alloys. Mathematical models proposed here have the capability to well predict material removal prior to the actual machining of Ti6Al4V, Inconel 718 and AA 2024.