Nizam Abd Rahman

Effects of Layer Thickness on the Microstructures of TiN/AlTiN Multilayer Coatings

TiN/AlTiN multilayer coatings were deposited on tungsten carbide cutting tool by applying a direct current on a pulsed bias arc ion plating system. The effect of pulsed bias layer thickness on sample properties was investigated. The amount of grain size decreased with increasing layer thickness. The crystal structure of the coatings was determined using a D8 Advance Bruker X-ray diffractometer with CuKa (λ = 1.5405 Å) radiation. TiN/AlTiN multilayer coatings were crystallized with orientations in the (111), (200), (222), and (311) crystallographic planes, and the microstructure was enhanced with preferred orientation in the (111) plane. Compared with the substrate, all the specimens coated with TiN/AlTiN multilayer coatings exhibited better X-ray diffraction properties.

Process and labour utilisation in the electronic industry: A simulation approach

Process utilisation that ensures all workstations are balanced is essential factor for factory productivity. Another important factor that has to be considered is the Man-to-Machine (M-to-M) ratio which provides an answer to how much manpower should be assigned to a machine. This paper reports on a simulation approach that aims to simultaneously provide a solution to the problems of process and M-to-M ratio utilisation. The results of the simulation provide an accurate picture for the system understudy in terms of the bottleneck process, optimal utilisation and M-to-M ratio.

An integrated architecture for lean waste analysis

Lean has become very popular for companies striving towards reducing wastes and improving their efficiency. The fundamental work in Lean implementation includes establishing the standard times for the process under study before the information can be used to determine the resource capacity. The traditional work study methods such as Process Mapping and Man-Machine Charts are no longer suitable to be used in the complicated manufacturing environment such as in the electronics. This paper reports on an integrated architecture for conducting work study and performing lean waste analysis. The developed architecture was implemented at an electronic manufacturing company. The benefits observed from the implementation phase indicate that the proposed architecture has reduced the lengthy time that work-study usually takes, eliminated human error during analysis and improved the accuracy of data.

Optimization of Fluidised Bed Granulation Process Parameters for Urea Granule Manufacturing Using the Response Surface Method

Fluidised bed technology is commonly applied in the pharmaceutical, agricultural and food production technology. The aim of this work is to identify the optimum process parameters in order to gain the best hardness and density values for the urea granules from the fluidised bed granulation. The layout of the experiments are based on Central Composite Design of Response Surface Method. The analyzed data shown that the optimize value for each of these parameter are 0.10MPa, 32.11Hz, 50% w/w, 42.250C for spray pressure, fan speed, urea solution concentration and inlet air temperature with 1.71 kgf/granule hardness and 1.85 g/cm3 density were predicted. Experimentally, using the predicted optimize input parameter, the hardness and density observed were 0.20 kgf/granule and 1.30 g/cm3 respectively.

The impact of the bilayer TaN/Ta barrier at the copper seed and copper electroplating process in semiconductor fabrication

Copper metallization process, using electroplating, in Integrated Circuit interconnect, poses big challenge in semiconductor fabrication. Besides the stringent Dual Damascene requirement, the copper material itself is prone to rapid interface diffusion as well as surface oxidation. Thus the copper metallization process has to be performed within specific time after copper seed deposition process. This study investigated the impact of bilayer TaN/Ta barrier on copper sheet resistance changes at different time intervals. The study was based on 200mm wafer. In addition to that, correlation between sheet resistance to other copper film properties such as reflectance and stress was also investigated. Based on results of this study, bilayer TaN/Ta barrier inclusion in copper seed greatly improved film sheet resistance stability.

Human System Modeling Technique for Semiconductor Assembly and Test

Global competitions are putting pressure on the manufacturing companies to produce products cheaper and faster. Thus, manufacturing operations are urgently exploring methods to reduce cost through improved efficiency in managing the resources. In recent years, there has been growing interest to study human system due to the lack of focus as compared to other resources such as equipment and material. This paper presents the overview and evaluation of the various human issues affecting manufacturing system dynamics and performance. Furthermore, the gap in the current models will be discussed before presenting the development of a proposed model to study human system in semiconductor assembly and test.

Cutting Parameters Optimization of Mild Steel via AIS Heuristics Algorithm

. The minimum cost and high productivity of the recent industrial renaissance are its main challengers. Selecting the optimum cutting parameters play a significant role in achieving these aims. Heat generated in the cutting zone area is an important factor affecting workpiece and cutting tool properties. The surface finish quality specifies product success and integrity. In this paper, the temperature generated in the cutting zone (shear zone and chip-tool interface zone) and workpiece surface roughness is optimized using an artificial immune system (AIS) intelligent algorithm. A mild steel type (S45C) workpiece and a tungsten insert cutting tool type (SPG 422) is subjected to dry CNC turning operation are used in experiments. Optimum cutting parameters (cutting velocity, depth of cut, and feed rate) calculated by the (AIS) algorithm are used to obtain the simulated and ideal cutting temperature and surface roughness. An infrared camera type (Flir E60) is used for temperature measurement, and a portable surface roughness device is used for roughness measurement. Experimental results show that the ideal cutting temperature (110°C) and surface roughness (0.49 μm) occur at (0.3 mm) cut depth, (0.06 mm) feed rate, and (60 m/min) cutting velocity. The AIS accuracy rates in finding the ideal cutting temperature and surface roughness are (91.70 %) and (90.37 %) respectively. Analysis shows that the predicted results are close to the experimental ones, indicating that this intelligent system can be used to estimate cutting temperature and surface roughness during the turning operation of mild steel.

Influence of Surface Treatment on the Surface Energy of Tungsten Carbide Inserts

The effect of substrate cleaning using ultrasonic cleaner on tungsten carbide was investigated. The surface energy of the substrate was measured using two liquids with dominant polar and dominant dispersion components which were distilled water (DI) and methylene iodide. Owens-Wendt method was carried out to calculate the surface energy of the substrate. The result showed that the cleaning process using solvent B (alkaline, DI, acid, DI, DI, alcohol) for 20 minutes without the wiping process led to the highest surface energy of 126.3399 dyne/cm with the polar component of 80.538 dyne/cm. Findings from this research suggested that type of solvent, cleaning time, and interactions among solvent type, cleaning time, and wiping process significantly influenced surface energy of the substrate.

Modeling of TiN coating thickness using RSM approach

In this paper, modeling of Titanium Nitrite (TiN) coating thickness using Response Surface Method (RSM) is implemented. Insert cutting tools were coated with TiN using Physical Vapor Deposition (PVD) sputtering process. N2 pressure, Argon pressure and turntable speed were selected as process variables while the coating thickness as output response. The coating thickness as an important coating characteristic was measured using surface profilometer equipment. Analysis of variance (ANOVA) was used to determine the significant factors influencing TiN coating thickness. Then, a polynomial linear model represented the process variables and coating thickness was developed. The result indicated that the actual validation data fell within the 90% prediction interval (PI) and the percentage of the residual errors were low. Findings from this study suggested that Argon pressure, N2 pressure and turntable speed influenced the TiN coating thickness.

Application of Fuzzy Rule-Based Model to Predict TiAlN Coatings Roughness

In this work, an approach for predicting the roughness of Titanium Aluminum Nitride (TiAlN) coatings using fuzzy ruled-based model was discussed. TiAlN coatings were produced using magnetron sputtering process. Tungsten carbide (WC) was selected as the substrate and titanium alloy was used as the material to coat the cutting tool. The sputtering power, substrate bias voltage and substrate temperature were selected as the input variables while roughness of the TiAlN coatings was considered as the response variable. A statistical design of experiments method known as centre cubic design (CCD) was selected to collect the data for developing the fuzzy rules. The prediction performances of the fuzzy rule-based model with respect to percentage error, mean squared error (MSE), co-efficient determination (R2) and model accuracy were compared with the response surface regression model (RSM). The result shown that the fuzzy rule-based model has much better predicting capability compared to the RSM.