Abstract: Utilizing MATLAB to develop graphical user interface in modeling of machining responses is a very rare case among researchers, especially for the complex and non-linear machining processes. Since it is more complicated and time consuming for one to explore artificial intelligent tools to model a process or response using MATLAB due to unfamiliarity and phobia of programming, a new approach is ventured to model using graphical interface. In this paper, how GUI is developed and integrated to model laser machining process using Adaptive Network-based Fuzzy Inference System (ANFIS) together with GUI’s ability in generating the model output for laser responses are presented. Laser cutting machine is widely known for having the most number of controllable parameters among the advanced machine tools and it becomes more difficult for the process to be engineered into desired responses such as surface roughness and kerf width especially for precision machining settings. Knowing laser processing and ANFIS programming are both difficult and fears modelers, a novel GUI is developed and used as an interface to model laser processing using ANFIS with various setting capabilities where, numeric and graphical output can be printed. On the other hand, the GUI can also be used to predict the responses to conduct comparative analysis. To validate the accuracy of the ANFIS modeling, the deviations are calculated through Root Mean Square Error (RMSE) and Average Percentage Error. The RMSE values are compared with various types of trained variables and settings on ANFIS platform, so that the best ANFIS model can be finalized before prediction and validation. The developed GUI is currently being tested by a pressure vessel manufacturing industry for an operator to optimize the best machine setting before it is operated. Thus, the industry could reduce the production cost and down time by off-hand setting as compared to the traditional way of trial and error method.

Abstract: Monte Carlo (MC) simulation is extensively used for solving thermal radiation problems in high-temperature environments, such as combustion chambers and furnaces, and irregular-geometry enclosures containing participative media such as combustive gases. The quantities of interest are surface radiosities and subsequent radiative heat fluxes which have been accurately determined by MC in configurations which are challenging for deterministic formulations. The attractiveness of MC schemes becomes more prominent in mixed-mode and coupled thermo-fluid problems, where the non-linearity, spectral characteristics and geometrical complexity may render deterministic treatments largely ineffective. This work deals with thermal radiative estimates for hot grey diffuse surfaces and grey participative media. Simple test-configurations are considered for which exact solutions are available and MC simulation is used to make validation comparisons. We also consider the analog simulation process to compute sensitivities of independent parameter variations, such as material density, in a single simulation. Such a capability increases the applicability of MC methods to optimization studies as easily as deterministic methods based on variational schemes.

Abstract: The injection molding process of fiber reinforced composite products involves flow of fiber suspensions in cavities with various sizes and shapes. The study of the flow of fiber-filled polymers in such cavities is quite complex due to the fact that the flow of fiber filled thermoplastics in the molten state is modified by the presence of fibers. Since the filling stage of injection molding process has important effects on the determination of the orientation of the fiber, accurate analysis of the flow field for the mold filling stage becomes a necessity. The aim of the paper is to develop a Computational Fluid Dynamics (CFD) model to simulate and characterise the fiber suspension flow in two dimensional mold cavities. The model is intended to describe the velocity profile and to predict the fiber orientation. The flow was considered to be incompressible, non-isothermal, transient and behave as non-Newtonian fluid containing suspensions of short-fibers. The numerical model for determination of velocity profile and fiber orientation during mold-filling stage of injection molding process was solved using finite difference method. The orientations of the fibers are represented by a second-order orientation tensor. The evolution equation for the second order orientation tensor is solved via Runge-Kutta method. The governing equations, in addition to the continuity, momentum, energy and second order orientation, contain a fourth order orientation tensor which is approximated in terms of second order tensor through the use of appropriate closure rules. To check the numerical method, test cases were modelled for different fiber-polymer matrices using both power law and cross models. The numerical results were compared with available experimental findings. A good agreement between the numerical results and the experimental data was achieved.

Abstract: Numerous operations in manufacturing industries require a length-to-diameter ratio greater than 5 times tool diameter. These types of operations, known as deep drilling, normally need the use of special tools and devices. The deep drilling is a process of high complexity due to its special difficulties such as cutting in a closed and limited space, high cutting temperature and the difficulty of chip formation and removal. Such conditions involve the chip formation and the flow difficulty, the tool overhang length, the surface quality and the hole geometric and form tolerances. This work presents an experimental and an analysis of the performance of carbide drill geometry in drilling of GG25 gray cast iron. The experiments have been carried out in line of production and laboratory, using tungsten carbide drills with straight flutes and internal cutting fluid. The aim of this experimental and analytical research is to identify the parameters which enable the prediction of surface roughness in drilling by integrating expert system. Fuzzy expert system were used to analyze the best fit model in predicting the quality of the deep drilled holes. With the results obtained in this work it was possible to acquire a major knowledge on the deep drilling process of gray cast iron, which allow improvements in the production of pieces in industrial scale.