Abstract: This paper focuses on using Six Sigma methodologies to improve the surface roughness of a manufactured part produced by the CNC milling machine. It presents a case study where the surface roughness of milled aluminum is required to reduce or eliminate defects and to improve the process capability index Cp and Cpk for a CNC milling process. The six sigma methodology, DMAIC (design, measure, analyze, improve, and control) approach, was applied in this study to improve the process, reduce defects, and ultimately reduce costs. The Taguchi-based six sigma approach was applied to identify the optimized processing parameters that led to the targeted surface roughness specified by our customer. A L9 orthogonal array was applied in the Taguchi experimental design, with four controllable factors and one non-controllable/noise factor. The four controllable factors identified consist of feed rate, depth of cut, spindle speed, and surface roughness. The noise factor is the difference between the old cutting tool and the new cutting tool. The confirmation run with the optimal parameters confirmed that the new parameter settings are correct. The new settings also improved the process capability index. The purpose of this study is that the Taguchi–based six sigma approach can be efficiently used to phase out defects and improve the process capability index of the CNC milling process.
Abstract: In this project three type of tools, straight cylindrical, taper cylindrical and triangular tool all made of High speed steel (Wc-Co) used for the friction stir welding (FSW) aluminum alloy H20–H20 and the mechanical properties of the welded joint tested by tensile test and vicker hardness test. Besides, mentioned mechanical properties compared with each other to make conclusion. The result helped design of welding parameter optimization for different types of friction stir process like rotational speed, depth of welding, travel speed, type of material, type of joint, work piece dimension, joint dimension, tool material and tool geometry. Previous investigations in different types of materials work pieces; joint type, machining parameter and preheating temperature take placed. In this investigation 3 mentioned tool types that are popular in FSW tested and the results completed other aspects of the process. Hope this paper can open a new horizon in experimental investigation of mechanical properties for friction stir welded joint with other different type of tools like oval shape probe, paddle shape probe, three flat sided probe, and three sided re-entrant probe and other materials and alloys like titanium or steel in near future.
Abstract: Increasing the demand for effectively use of the
production facility requires the tools for sharing the manufacturing
facility through remote operation of the machining process. This
research introduces the methodology of machining technology for
direct remote operation of networked milling machine. The
integrated tools with virtual simulation, remote desktop protocol and
Setup Free Attachment for remote operation of milling process are
proposed. Accessing and monitoring of machining operation is
performed by remote desktop interface and 3D virtual simulations.
Capability of remote operation is supported by an auto setup
attachment with a reconfigurable pin type setup free technology
installed on the table of CNC milling machine to perform unattended
machining process. The system is designed using a computer server
and connected to a PC based controlled CNC machine for real time
monitoring. A client will access the server through internet
communication and virtually simulate the machine activity. The
result has been presented that combination between real time virtual
simulation and remote desktop tool is enabling to operate all machine
tool functions and as well as workpiece setup..
Abstract: One of the main concerns about parallel mechanisms
is the presence of singular points within their workspaces. In singular
positions the mechanism gains or loses one or several degrees of
freedom. It is impossible to control the mechanism in singular
positions. Therefore, these positions have to be avoided. This is a
vital need especially in computer controlled machine tools designed
and manufactured on the basis of parallel mechanisms. This need has
to be taken into consideration when selecting design parameters. A
prerequisite to this is a thorough knowledge about the effect of
design parameters and constraints on singularity. In this paper,
quality condition index was introduced as a criterion for evaluating
singularities of different configurations of a hexapod mechanism
obtainable by different design parameters. It was illustrated that this
method can effectively be employed to obtain the optimum
configuration of hexapod mechanism with the aim of avoiding
singularity within the workspace. This method was then employed to
design the hexapod table of a CNC milling machine.
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.