Abstract: Fused deposition modelling (FDM) is one of the most prominent rapid prototyping (RP) technologies which is being used to efficiently fabricate CAD 3D geometric models. However, the process is coupled with many drawbacks, of which the surface quality of the manufactured RP parts is among. Hence, studies relating to improving the surface roughness have been a key issue in the field of RP research. In this work, a technique of modelling the surface roughness in FDM is presented. Using experimentally measured surface roughness response of the FDM parts, an ANFIS prediction model was developed to obtain the surface roughness in the FDM parts using the main critical process parameters that affects the surface quality. The ANFIS model was validated and compared with experimental test results.
Abstract: In this current era of competitive machinery productions, the industries are designed to place more emphasis on the product quality and reduction of cost whilst abiding by the pollution-preventing policy. In attempting to delve into the concerns, the industries are aware that the effectiveness of existing lubrication systems must be improved to achieve power-efficient and pollution-preventing machining processes. As such, this research is targeted to study on a plausible solution to the issue in grinding titanium alloy (Ti-6Al-4V) by using nanolubrication, as an alternative to flood grinding. The aim of this research is to evaluate the optimum condition of grinding force and surface roughness using MQL lubricating system to deliver nano-oil at different level of weight concentration of Silicon Dioxide (SiO2) mixed normal mineral oil. Taguchi Design of Experiment (DoE) method is carried out using a standard Taguchi orthogonal array of L16(43) to find the optimized combination of weight concentration mixture of SiO2, nozzle orientation and pressure of MQL. Surface roughness and grinding force are also analyzed using signal-to-noise(S/N) ratio to determine the best level of each factor that are tested. Consequently, the best combination of parameters is tested for a period of time and the results are compared with conventional grinding method of dry and flood condition. The results show a positive performance of MQL nanolubrication.
Abstract: Rapid Prototyping (RP) technologies enable physical
parts to be produced from various materials without depending on the
conventional tooling. Fused Deposition Modeling (FDM) is one of
the famous RP processes used at present. Tensile strength and
compressive strength resistance will be identified for different sample
structures and different layer orientations of ABS rapid prototype
solid models. The samples will be fabricated by a FDM rapid
prototyping machine in different layer orientations with variations in
internal geometrical structure. The 0° orientation where layers were
deposited along the length of the samples displayed superior strength
and impact resistance over all the other orientations. The anisotropic
properties were probably caused by weak interlayer bonding and
interlayer porosity.
Abstract: The capability of CNC gantry milling machines in
manufacturing long components has caused the expanded use of such
machines. On the other hand, the machines’ gantry rigidity can
reduce under severe loads or vibration during operation. Indeed, the
quality of machining is dependent on the machine’s dynamic
behavior throughout the operating process. For this reason, these
types of machines have always been used widely and are not
efficient. Therefore, they can usually be employed for rough
machining and may not produce adequate surface finishing. In this
paper, a CNC gantry milling machine with the potential to produce
good surface finish has been designed and analyzed. The lowest
natural frequency of this machine is 202 Hz corresponding to 12000
rpm at all motion amplitudes with a full range of suitable frequency
responses. Meanwhile, the maximum deformation under dead loads
for the gantry machine is 0.565*m, indicating that this machine tool
is capable of producing higher product quality.
Abstract: Nowadays, the demand for high product quality
focuses extensive attention to the quality of machined surface. The
(CNC) milling machine facilities provides a wide variety of
parameters set-up, making the machining process on the glass
excellent in manufacturing complicated special products compared to
other machining processes. However, the application of grinding
process on the CNC milling machine could be an ideal solution to
improve the product quality, but adopting the right machining
parameters is required. In glass milling operation, several machining
parameters are considered to be significant in affecting surface
roughness. These parameters include the lubrication pressure, spindle
speed, feed rate and depth of cut. In this research work, a fuzzy logic
model is offered to predict the surface roughness of a machined
surface in glass milling operation using CBN grinding tool. Four
membership functions are allocated to be connected with each input
of the model. The predicted results achieved via fuzzy logic model
are compared to the experimental result. The result demonstrated
settlement between the fuzzy model and experimental results with the
93.103% accuracy.