Pusat Pengajian Kejuruteraan Mekanikal - Tesis

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A Model For The Fuzzy Front End Of New Product Development Process
(2016-01)
Abd Rahman, Md Nizam
In general, New Product Development (NPD) methodology can be broken down into five phases, Strategic Planning. Idea Generation, Pretechnical Evaluation, Technical Development, and Commercialization. The first three steps are known as the front end and the last two are known as the back-end of the NPD methodology. The scope of this research work is limited to the first two steps of the NPD methodology, which are strategic planning and idea generation. The objectives of this research work are I) to piece together the various steps required in executing strategic planning process to ensure its effectiveness and 2) to define guidelines in selecting idea generation techniques that are suitable for a given set of conditions. Through analyzing case studies on thirty cornpapies that have been proven successful in NPD programs, the main factors that have significant impact on the success of NPD strategic planning process are verified and guidelines for selecting suitable idea generation techniques for a given set of conditions are developed.
Analysis of tribological and vibration performance of palm olein-based grease containing molybdenum disulphide additive
(2024-07-01)
Nadiah Aqilahwati, Abdullah
The detrimental effects of the mineral-based lubricants and their non-renewable resource has urged the effort in developing a safe and environmentally friendly lubricants. In this study, the effect of additive concentration and particle size was investigated. Three concentrations (0.25, 0.50 and 0.75 wt.%) micro MoS2 was added to the palm olein grease to find the optimum concentration. Based on the optimum concentration, the MoS2 was added in micro and nanoparticles (1-3 µm and 90 nm). The worn surface was analysed by evaluating their coefficient of friction (COF), wear scar diameter (WSD), wear depth, wear volume, wear micrograph image and elemental distribution after a four-ball test. Next, the greases were evaluated by utilising a small-scale spur gear rig. The performance of the palm grease was compared with commercial grease by measuring the gear mass loss, surface characteristics and vibration level. From the four-ball test, palm grease with 0.50 wt.% MoS2 nanoparticles was the optimal grease where it reduced the COF, WSD, wear depth and wear volume for 18.41%, 25.51%, 22.52% and 61.25% compared to grease without additive, respectively. For the gear test, the palm olein grease had 29.04% lower COF but 2.30% higher WSD. The developed palm grease had the lowest roughness difference, mass loss, vibration, and surface damage compared to dry and commercial grease. The findings shows that the developed grease has a good potential to be utilised as a lubricant for a suitable working condition. The performance of the palm olein grease is also on par with the commercial grease.
Analysis of tribological characteristics and performance of palm olein-based grease containing copper nanoparticles
(2024-04-01)
Arif Izzuddin Bin Muhammad
The harmful environmental effect of commercial mineral greases has been raising concerns in the community. Many had reported on the benefit of mineral grease, however, the toxicity and depletion of mineral grease had led to the interest in developing a more sustainable and environmentally friendly grease lubricants. In addition, without nanoparticles such as copper and graphene in grease lubricants, bearings can be exposed to friction and wear faster. Therefore, the aim of this study is to investigate the tribological characteristics and performance of the developed palm olein-based grease with added copper nanoparticles additive. In this study, palm olein based grease was developed using palm olein as base oil and lithium stearate as a thickener. The copper nanoparticle additive was dispersed in the palm olein grease at concentrations of 0.25 and 0.50 wt% and the optimum concentration with the best performance is investigated. The palm olein grease was produced to NLGI 2 grade consistency, which is widely used and suitable for multipurpose applications. This grease is expected to be suitable for a wide range of industries, including agriculture and forestry applications, where the machineries are subjected to environmental exposure. The tribological tests were conducted using a four-ball tribometer to evaluate the wear and friction characteristics of the formulated grease. Further work has been done to investigate the performance of the developed grease by performing an experimental work using a roller bearing test rig. The performance of the palm olein grease was compared with a commercially available mineral grease lubricant. Surface roughness and wear characteristics of the inner race of the roller bearing were analysed periodically and the vibration level was measured. The formulated palm olein grease with copper nanoparticles additive demonstrated enhanced wear resistance, comparable performance to commercial mineral greases during the four-ball friction test with small friction value and wear, and superior performance to commercial mineral grease during the roller bearing test with reduced vibration levels and lower surface degradation. These findings contribute to the knowledge and understanding of palm grease formulations and their potential applications in tribological systems.
Attenuation of humming type noise and vibration in vehicle hvac system using a tuneable dynamic vibration absorber
(2023-06-01)
Muhammad Safwan Bin Abdul Aziz
The purpose of this research is to study the effect of a Tuneable Dynamic Vibration Absorber (TDVA) in reducing the humming type noise and vibration that originating from the Heating, Ventilation and Air Conditioning (HVAC) system of a Proton Exora vehicle. In this study, a lab-scale experimental rig of Proton Exora HVAC system was built to represent the system inside the vehicle. On top of that, the study also been conducted on the Proton Exora vehicle itself for the data comparison. The TDVA was designed and tuned according to the natural frequencies of the Air Conditioning (AC) pipe structure obtained from Experimental Modal Analysis (EMA) of both the system and vehicle level with natural frequency values of 148 Hz and 173 Hz respectively. Two TDVA, with the length of 5.53 cm and 4.98 cm were fabricated and applied at both lab scale test rig and vehicle level, respectively. The humming type noise and vibration characteristics of the HVAC components were recorded and compared, with and without the implementation of TDVA. The implementation of TDVA into the system was found to reduce the vibration level of the AC Pipe by 80 % and subsequently reducing the noise and vibration level of the whole HVAC system inside the cabin area by 1.5 dBA. It also been observed that the applied TDVA has an effective frequency range of 100 – 500 Hz for the vehicle level and 75 – 250 Hz for the lab scale test rig.
Combustion characterization and optimization of mixture biomass producer gas and methane in a constant volume combustion chamber system for fuel combustion efficiency enchancement
(2023-03-01)
Teh Jun Sheng
Most of the world’s energy requirements are still derived from natural resources. This will result in a catastrophic energy crisis with negative environmental consequences. The increased energy supply will result in greater consumption of non-renewable sources. The production of biomass producer gas (BPG) from biomass gasification has received significant attention for reducing global emissions as an alternative fuel because of the depletion of non-renewable resources. The properties of biomass feedstocks significantly influence combustion characteristics. The objective of this experimental study was to determine the combustion characteristics: flame propagation speed, chamber pressure trace and emissions of BPG at different equivalence ratio to obtain the lower chamber peak pressure and greenhouse gas emissions. Using the direct visualization technique, an optical constant volume combustion chamber (CVCC) was developed to measure combustion characteristics. Liquid petroleum gas (LPG) was used to compare chamber pressure and flame propagation speed in the CVCC calibration. In comparison to wood pellet (WP), coconut husk (CH), and palm kernel shell (PKS), the chamber peak pressure at 𝜙 equal to 1 of CH for the combustion of BPG is the lowest at 20.84 bar. At 𝜙 of 0.7, 0.8, 0.9, 1.0, 1.1, 1.2, and 1.3, the chamber peak pressure of CH was discovered to be around 17.77, 18.12, 18.81, 20.84, 20.39, 17.25, and 16.37 bar. Compared to the other two types of BPG, CH produces the lowest emission of CO2 and CO, at 2.03% and 0.02%, respectively. From the literature review, increasing CH4 content in the fuel can increase the mole fraction of H, O2, and OH radicals and reaction rates in the flame, further accelerating the flame of the mixtures. Therefore, an optimization study is needed to determine the higher performance combustion of BPG with an increase in the composition of methane. The combustion experiment study was optimized with 17 designed experiments, 0.9 to 1.1 equivalence ratio, and the 0 to 0.1 mole fraction of methane fuel. The BPG-methane-air mixture, according to optimization analysis, achieves the fastest flame propagation speed and the lower chamber peak pressure at 𝜙 equal to 1 and a mole fraction of methane fuel of 0.083. Compared to the BPG-air mixture (𝜙 equal to 1), which had a chamber peak pressure of 20.84 bar, the average results of the optimum configuration parameters reveal a lower peak pressure was 18.97 bar. Comparison of the chamber peak pressure between BPG-methane-air mixture and BPG-air mixture varied by approximately 9.39%. In this context, the gross heat release rate (HRR) is observed to be around 94.44 kW, which represents a 20% reduction when compared to CH fuel. However, there is a slight increase in the emissions of CO and CO2, with a rise of 0.01% and 5%, respectively. In conclusion, the optimal mixture of BPG and methane fuel provides the optimum flame propagation speed with lower chamber peak pressure than BPG.
Data mining for service industry: branch classification of a malaysia retail bank
(2023-01-01)
Chong Siu Hou
The on-going customers’ behavioural shifts from assessing physical banking services to virtual banking services have made retail banks continually review their physical banking network strategies. Such exercise allows the retail banks to maintain their competitive advantages over their competitors while balancing their business portfolios between online banking service needs, optimizing physical clientele coverage, and minimizing costs in running a physical branch network. The research objective is to develop a suitable classification model in decision-making that can mimic experts’ opinions on retail bank branch operational status using a case study on a Malaysian retail bank. Seventy-four branch attributes were used to build a classification model in which experts’ opinions are included as an attribute to allow the data mining (DM) application to emulate experts’ decision-making. The research methodology involves collecting the experts’ opinion through an expert survey to determine the feasibility of a branch remaining open or closing permanently as part of the bank’s network rationalization strategy. The value obtained from the survey was converted into a variable termed “aggregate closure possibility” in this study and then discretized into target class datasets. Then ten classification models were constructed, including ZeroR, Decision Tree, Random Forest, Naïve Bayes etc. Next, three experiments were conducted. The first experiment examined the effect of hyperparameter tuning on classification accuracy. The second experiment studied the impact of changes in the number of target classes on classifier accuracy and then highlighted the best-performing classifier. When the number of target classes was optimized, the accuracy of classifiers improved drastically, of which, three classifiers (Decision Table, J48, and JRip) were the most accurate classifiers. The third experiment studied the effect of attribute selection and instance reduction in optimizing classification performance. It was observed that the accuracy of most classifiers improved proportionate to the reduction of numbers of attributes and instances where Decision Table, J48, BayesNet, and JRip were the best performing classifiers in the third experiment. The result shows that JRip was the best performing classifier in all three experiments. Attribute selection and instance reduction optimized the classification accuracy in encompassing efficient datasets. The study also showed that the DM application could emulate expert opinion in decision-making in retail banking sector. In conclusion, the study has successfully achieved its research objectives. The study contributes to research knowledge on how DM capabilities could improve management decision-making in a real-world application.
Development and performance analysis of hydraulic hybrid regenerative braking system for passenger vehicle
(2022-01-01)
Idris, Khairul Anuar
The global fuel consumption of passenger vehicles has been rising dramatically over time. Since fossil fuel is non-renewable energy, there is a need to improve the passenger vehicles efficiency. Therefore, the hydraulic regenerative braking system (HRBS) is introduced to recapture the lost energy during the deceleration. This study aims to develop HRBS and determine its performances. The experimental work involved designing and fabricating a test rig of the HRBS in a parallel configuration. The performance of the developed system was determined in terms of efficiencies of hydraulic motor and pump. The study findings developed a mechanical efficiency map for the hydraulic motor for different pressures. It was found that the efficiency gradually increased with the increase in pressure from 20 to 80 bar, but a slight drop was seen with further increase in pressure above 80 bar. The highest efficiency recorded by pump and motor were 83 % and 74 %, respectively. Meanwhile, hydraulic pump’s mechanical efficiency maps in terms of pressure were determined for four different speeds. The efficiency was steadily increasing from the pressure 20 to 75 bar. The optimum operating pressure was 65 bar for both the pump and motor. The optimum operation also played a crucial role in establishing the higher mechanical efficiency for the motor and pump, subsequently affecting the overall performance of the developed HRBS system.
Effect of cold deformation on properties of aluminium alloy fabricated using wire arc additive manufacturing technique
(2023-04-01)
Muhammad Ajwad Bin Roslee
Additive manufacturing (AM) owns a huge potential in repair and remanufacturing industries due to its advantage of minimizing waste while having the abilities to produce complex shapes without mold. Current technique to obtain net shape is limited due to strength and lead time issues. AM also provides low cost solution for repairs with wire arc additive manufacturing (WAAM) which use common welding technique. However, this method produces parts with lower strength and hardness due to the high heat input and porosity. In this study, WAAM produced parts was constructed using manual TIG welding at different orientation and welding direction and new strategy was proposed, where cold forging process is introduced as a post deposition treatment, where the parts are subjected to different thickness reduction. The main aim of this study is to evaluate the tensile properties and hardness of forged AA4043 wire arc additive manufacturing (WAAM) constructed at different welding orientation and direction. Result discovered that the ultimate tensile strength (UTS) increased by 44%, from average UTS of 160 MPa to 200 MPa, and hardness value increases by 70%, from average hardness of 43 HV to 73 HV. Using SEM analysis, it is discovered that forging reduced the porosity sizes by 90%. Even with the improvement made by forging, upright orientation still suffer from interlayer strength, producing lower UTS compared to other parameters. Keywords: WAAM; AA4043; strain hardening; cold forging; repair
Effect of cold deformation on tribological performance of additive manufactured aluminum alloy er 5356
(2023-09-01)
Muhammad Faris Akmal Bin Md. Azlin
As a result of severe sliding wear, the automotive parts are often sent to landfills instead of being repaired or remanufactured. Metal additive manufacturing is now an alternative for reconstructing the damaged section. Despite that, the properties of the part may be affected due to heat during welding. Post-weld deformation, like cold deformation, is known as one of the property enhancement methods used to retain mechanical properties. The effect of cold deformation on the wear performance of aluminum alloy ER 5356 was investigated in this study using MIG-based wire arc additive manufacturing (WAAM). The cold forging process was conducted at room temperature and deformed using a 100-ton mechanical press machine. Unforged and forged specimens were compared to obtain specific wear rates for dry and wet sliding. It was observed that forged specimens have a lower specific wear rate than unforged specimens for both dry and wet cases at various speeds with applied loads. The range of the specific wear rate (mm3/Nm) for unforged specimens for dry sliding was 4.25 x 10-5 to 6.29 x 10-5 mm3/Nm, while for wet sliding, the specific wear rate ranges between 8.91 x 10-6 and 1.41 x 10-5 mm3/Nm. On the other hand, for forged specimens, the ranges of the specific wear rate in dry and wet sliding cases were 2.89 x 10-5 to 5.28 x 10-5mm3/Nm and 2.07 x 10-6 to 4.68 x 10-5 mm3/Nm, respectively. The coefficient of friction (COF) for unforged and forged specimens in dry sliding for all speeds and applied loads decreases as the specific wear rate increases. However, COF for wet sliding is lower for both unforged and forged samples. The cold forging process provides a lower specific wear rate and COF for wet and dry cases compared to unforged samples. Based on this study, cold forging shows a good and potential alternative to reverse the properties such as the tribological performance for part repair or remanufacturing.
Effect of fuel injection strategies and intake air supply control on performance, exhaust emission, and combustion characteristics of diesel engine fuelled with biodiesel fuel
(2023-06-01)
Leong Hau
Split injection strategies were generally agreed to be a promising strategy to achieve simultaneous nitrous oxide (NOx) and soot reduction. The air intake channel of a commercial diesel engine is designed for maximum airflow rate under severe load conditions. At medium load, excessive airflow may contribute to NOx formation. Therefore, air intake restriction with exhaust gas recirculation (EGR) might be a viable option to couple with a split injection scheme when the engine operates in part load. The study comprises of three parts. Firstly, an engine test rig has been built, which consists of a dynamometer, exhaust gas analyser, and an engine coupled with an in-house built electronic fuel injection control unit (ECU). Secondly, the effect of biodiesel blend on engine performance and emission has been studied, and the most desired fuel blend and engine operating condition was used in the next step. Thirdly, the effect of the double and triple split injection with different timing and injection ratio coupled with EGR and intake air throttling has been studied. It has been found that B60 POME blend at 2000rpm and 80 Nm were the optimize mid load engine condition. Where 5050 double split injection with 12CA was the optimize split injection strategies. Intake air throttling has been found to enhance EGR's beneficial impact by driving more exhaust gas via the EGR path. A response surface methodology (RSM) study was performed to optimise air control and split fuel injection strategies to maximise engine performance and minimise exhaust emissions The optimum parameter appears at 12 °CA dwell angle, -4°ATDC SOI timing, 40% intake throttle opening, 6.75% EGR, 800 bar fuel injection pressure, and 50% split injection ratio.
Effect of ilu dispensing types on underfill encapsulation for void formation detection using convolutional neural network (cnn)
(2024-09-01)
Muhammad Taufik, Azahari
Underfill is used to establish a mechanical and electrical connection between the ball grid array (BGA) package and the printed circuit board (PCB). Underfilling in BGA chip package is an essential process so that the reliability is ensured. There are three different types of dispensing method such as the I-type, L-type and the U-type which were commonly used in existing researches to fill the chips. Its drawback, however, are voiding which is the presence of empty space within the underfilling. The voiding defect, large in amount will cause reliability issues such as popcorning effect due to expansion of air due to heat when the chip is being used. This study aims to investigate the phenomenon of voiding in the underfilling process of large quantity BGA chips by investigating the correlation between voiding and underfilling parameters using machine learning. As manual inspection becoming less feasible to be done on large-scale manufacturing process, this study will introduce an automated method using convolutional neural network (CNN) to process the uploaded image of the chip in determining the void presence. Its percentage over the total underfilling will then be computed to identify the product can be accepted or rejected based on the Institute for Printed Circuits (IPC) standard. Previous researches applied CNN method for variety of detection purposes, however there is no research on CNN application on underfill voiding detection. In this study, a CNN model is developed using MobileNetV2 to detect underfill voids in BGA chips and the model obtained a mean average precision of 0.533. The model detects that longer dispensing times lead to larger voids, with the I-type dispensed for 3 minutes 48 seconds having a void percentage of 1.116%, compared to 0.136% for the I-type dispensed for 2 minutes 39 seconds. Thirty unique parameters were recorded, and the results revealed that valve pressure is the primary contributor to voiding in this specific setup. Using machine learning, the best-performing model achieved an accuracy of 88.9% and an area under the receiver operating curve (AUC) of 0.722, indicating its high predictive capability.
Effect of ternary fuel blends of bio -ethanol / propanol, diesel and palm biodiesel on engine performance, emissions and combustion characteristics of a compression -ignition engine
(2023-10-01)
B Navaneetha Krishnan
Malaysia, one of the key palm oil producers in the southeast Asian region, currently uses palm biodiesel mixed with diesel and it aims provide a higher palm biodiesel concentration in diesel fuel. Prior studies on biodiesel fueled compression ignition engines show a higher oxides of nitrogen emission formation when compared to engine operation with diesel fuel. In order to control this particular pollutant formation without any physical modifications to the powertrain, alcohol-based fuels such as ethanol and propanol can be added to the existing palm biodiesel – diesel fuel blend. The test was done on a Kirloaksar TV1 engine having rated power of 5.2 kW at 1500 rpm. The initial test phase was carried out using reference fuels such as Diesel, B100 and B40D60 and later continued with ethanol and propanol based ternary blends namely B40D50E10, B40D40E20 and B40D30E30 and B40D50P10, B40D40P20 and B40D30P30. Analysis of test results revealed that Diesel possessing the highest CV amongst all tested fuels resulted in giving the highest BTE value of 29.9% and in the case of alcohol based ternary blends, utilizing B40D50P10 and B40D50E10 as fuels were seen to result in 27.8% and 27.3% BTE respectively. Similar to the trend of BTE, fuelling CI engine using Diesel fuel gave CP of 71.91 bar which was observed to be the highest among the tested fuels. Using ternary blends B40D50E10 and B40D50P10 resulted in CP value of 69.29 bar and 69.80 bar which in comparison is lower than diesel but higher than ternary blends having more alcohol content. For the tested fuels, the trend for both BSCO and BSHC are observed to be similar and in it the lowest emission BSCO and BSHC values were observed for B100 at 0.132 g/kWh and 0.069 g/kWh respectively. Whereas for alcohol based ternary blends, the lowest BSCO and BSHC values were recorded for B40D50E10 at 0.131 g/kWh and 0.110 g/kWh while for B40D50P10 at 0.119 g/kWh and 0.100 g/kWh respectively. When comparing emission results obtained with ternary fuel blends, the lowest SM and BSNOX emissions value of 60.1% and 4.672 g/kWh for B40D30P30 and 63.6% and 4.504 g/kWh for B40D30E30 were recorded respectively. Among the ternary blends, the fuel type designated as B40D50P10 and B40D50E10 are seen to be more suitable for utilization in CI engines they show enhanced performance and lower emission characteristics in comparison to ternary fuel blend with higher alcohol concentration.
Effects of pitch size, cu pillar diameter, and height during reflow soldering using thermal fluid-structure interaction analysis
(2023-07-01)
Lee Jing Rou
The copper (Cu) pillar with solder cap interconnection has been introduced as an alternative for the solder bump interconnection in electronic packaging. This is because of their ability to tackle limitations such as the collapsing nature and larger pitch size of the solder bump. However, the thermal and mechanical performances of Cu pillar bumps are a concern for achieving reliable electronic products. Hence, this study aims to develop a one-way fluid-structure interaction (FSI) thermal coupling method to model the reflow soldering process of the Cu pillar bumps, and study their thermal and mechanical behaviours. The experimental work was used as a benchmark for developing the numerical model, then the simulated reflow temperature was compared with the experiment result, which was in good agreement. When comparing the reflow temperature profiles, the Cu pillar bumps were found to have comparable thermal performance to solder bumps, showing that Cu pillar bumps are an alternative option. Furthermore, the fluid and thermal analysis were conducted in ANSYS FLUENT, whereas the structural analysis was performed in ANSYS STATIC STRUCTURAL. The thermal loads obtained from the FLUENT were applied on the STATIC STRUCTURAL using one-way FSI thermal coupling method. The simulated flow field also showed that radiation is the dominant heat transfer mode in the oven. The heat transfer was affected by the airflow circulation and leaded to uneven temperature distribution, causing temperature deviation between each bump. Besides, an in-depth study using the simulation approach revealed that the thermal and mechanical performances of the Cu pillar bumps were dependent on several parameters, which were pitch size, Cu pillar diameter and Cu pillar height. From the parametric studies, the simulation result revealed that the overall reflow temperature, the temperature difference between the coldest and hottest bumps, deformation, and stress and strain distribution, influenced the Cu pillar bump reliability. Based on the results of these parametric studies, the suggested configuration for the Cu pillar bump was proposed, with 0.40 mm pitch size, 0.20 mm diameter and 0.09 mm height. Thus, this study provides a comprehensive guide for monitoring the temperature distributions on Cu pillar bumps and its capability to resist deformation and stress, which are crucial criteria for achieving high-quality bonding and reliable electronic products.
Encapsulation process of polymer for led packaging
(2021-12-01)
Alim, Md. Abdul
Several developments and innovations have reported strengthening the reliability and efficiency of these devices to speed up the LED packaging industry for the past few years. To develop a sustainable LED packaging process, die attachment and encapsulation shape are key factors. Epoxy based non-conductive adhesive (NCA) is popular die attachment material. Though NCA have many benefits so, an investigation on the suitable shear strength, adhesive thickness, and adhesion area are essential for die attachment process. Normally, high viscous epoxy resin is used as encapsulation material. A proposed low viscosity epoxy encapsulation shape can represent a new milestone for low-cost LED fabrication. In this work, the relationship between adhesive thickness and shear strength developed in chip and substrate joint is evaluated by using different adhesive applicator. Surface morphology of chip and substrate are also studied by using the SEM, EDS, and image processing software. The result indicated that the suitable shear strength 37.42 N/mm2 obtains at 24 µm thickness of the adhesive layer. A new moldless dispensing method for forming dome shaped encapsulation is studied. Luminous intensity of LED is determined by mixing verity of weight % of phosphor with the epoxy and variation in shape of encapsulation The results show that this method can produce the lenses with high aspect ratio (height over radius) on substrates of different sizes. The improvement of light output was found about 2.37% for dome shaped (average H/R value 0.71) encapsulation. This experimental work is a good guideline to master the geometric shape of encapsulation for further development and to choose technological criteria for LED packaging.
Experimental study on macro voiding minimization in solder joint thermal pad of qfn package
(2023-02-01)
Muhammad Syahir Bin Mahyuddin
Voiding in solder joints is a common problem that occur in electronic packaging, specifically for bottom terminated component (BTC). Quad Flat No-Lead (QFN) is a good example of BTC component that susceptible to void. Thus, QFN component thermal pads were used as the test vehicle in this voiding assessment. The objectives of this study are to analyze the influence of the variables from every parameter evaluated in the experiment on voiding area in QFN thermal pad solder joint and obtain the best combination of variables that can minimize the total void area percentage inside QFN thermal pad solder joint down to below 5%. In this study, several variables and their impacts on voiding based on the literature review were studied. No clean lead-free solder paste of SAC305 composition was employed in this experiment. Various stencil patterns were tested, including Window-Pane, Round, and Triangle/Polygon. The influence of pad surface finishing of the test board on the voiding reduction was analyzed in this study. The effects of convection reflow of various profiles and atmospheres were also considered. All the variables were setup for the experiment execution which begins by solder paste printing, solder paste inspection, component pick & place, convection reflow soldering, Xray inspection, void data extraction & analysis, and finally void results compilation. The results shown that reflow profile Ramp-To-Spike (RTS) Long Reflow Time High Peak Temperature gave lesser void area % than Ramp-Soak-Spike (RSS) Long Soak and RTS Normal profiles. Reflow with nitrogen atmosphere found to yield lesser void area % than air. It was shown that Organic Solder Preservatives (OSP) and Immersion Silver (Im-Ag) PCB pad finishes gave much lesser void area % than Electroless Nickel Immersion Gold (ENIG) finish. The stencil designs of window-pane, round and triangle/polygon shown that all three of them have insignificant difference of impact on void area %. From the results, it can be proposed that combining the pad finishing with OSP and Im-Ag, RTS Long Reflow time high peak temperature reflow profile, and nitrogen atmosphere can significantly reduced the void, regardless of the stencil design used.
Feasibility of 3d scanner based on infra-red ranging sensor
(2024-08-01)
Tian, Kailai
In an era marked by rapid advancements in science and technology, the proliferation of digital and electronic products has greatly enhanced everyday convenience. Within this context, the 3D scanning market presents significant opportunities for development and application in various fields. Current market offerings of traditional laser 3D scanners and photogrammetry-based 3D scanners commonly face limitations due to lighting conditions. Scanning outcomes in outdoor or bright light environments are often suboptimal. Furthermore, traditional laser 3D scanners require the application of a developer for scanning objects with high refractive or transmittance rates, such as glass products or metal materials. This requirement poses restrictions for objects with fragile surfaces or those under cultural heritage conservation. The study evaluates the strengths and weaknesses of current 3D scanning methods, including camera-based and radar-based scanners, with the goal of creating a scanning approach that improves data acquisition speed and offers a universal, streamlined structure for daily use. The research introduces a novel 3D scanning sensor that leverages infrared ranging and point cloud processing to overcome the limitations of traditional photo-based scanners, which require time-consuming captures from multiple angles. By employing infrared ranging and point cloud analysis, our approach accelerates the data collection process. We designed and tested a 3D scanning system utilizing infrared sensors, proposing the elimination of complex rotating mechanical components in favour of a simpler, more user-friendly design. A key feature of our research is the use of cost-effective and stable sensors, significantly reducing the overall cost. This system solves the problem of poor scanning results of traditional laser 3D scanners and camera-based 3D scanners outdoors or in strong light conditions. The error between outdoor and indoor point cloud results is only 1.7%. At the same time, it also solves the problem that laser 3D scanners need to spray developer for objects with high refractive index or light transmittance. The data reliability of wooden scans using this system is 94.63%. This overall cost of this system is less than 2% of the price of the EinScan-S3D scanner. If a higher-precision infrared scanner is used to improve the accuracy of this design system, the price is still less than 50% of the price of the EinScan-S3D scanner. This highlights the practicality and affordability of our proposed 3D scanning sensor, making it a viable solution for everyday applications
Finite element analysis of deformation and fracture of cortical bone in vibration-assisted bone cutting
(2024-11-01)
Du, Qianrui
The use of vibration-assisted cutting (VAC) technology has made its way from industrial applications to the medical field, particularly in bone cutting for orthopaedic surgery. Nevertheless, the bone cutting process can be quite complex because of the bone’s anisotropic properties, which contribute to its intrinsic toughening mechanism and vulnerability to surface damage. Therefore, it is important to take into account the impact of microstructure on the efficiency of the bone cutting process, which can be accurately evaluated using the finite element method. Yet, simulating tool-bone contact is seldom done because of the large deformation of the bone model, which can cause convergence issues, thereby adding complexity to the analysis. Hence, to simplify the modelling process, this study creates Python code for building a bone micro-model that includes bone microstructure considerations. The code allows for creating a micro-model with a user-defined distribution of bone microstructure constituents, enabling adjustable porosity. Two bone models with different microstructure properties and porosity are created using the code to represent young and aged bones. The models have been validated through a comparison of the stress intensity factor with the analytical results for a single-edge notch bending (SENB) specimen, revealing a deviation of just 4.5%. By incorporating the extended finite element method (XFEM), these models are utilised to analyse how amplitude and cutting depth impact the performance of vibration-assisted bone cutting. This analysis involves quantitatively assessing the resulting cutting force, stress, strain rate, crack initiation and propagation, and comparing them to conventional cutting methods. According to the results, VAC consistently decreases cutting force and stress in both models for various cutting depths and shows improved control of crack extension direction with smoother crack curves. It has been noted that the impact of amplitude variation on the resulting cutting force varies between the two models. In aged bones, increasing the amplitude decreases the cutting force, whereas in young bones, it has a negligible effect. In terms of bone strain rate, vibration-assisted cutting can significantly increase the cutting strain rate, thus reducing toughness damage and cumulative damage. VAC temperature is observed to be higher than conventional cutting. At the area of high temperature, which is near the tool, the cutting chips are smaller.
Finite element modeling of warpage molded printed circuit board in a reflow process
(2022-05-01)
Sek, Chun Hei
A printed circuit board (PCB) consists of multi-layer materials that allow electrical current flow. Each material layer has its own specific coefficient thermal expansion (CTE), such as Young’s modulus, Poisson’s ratio, etc. A conventional PCB board consists of polymer, silicon, copper, and dielectric. With each layers having different CTE values, this causes PCB to warp.In the semiconductor industry, PCB warpage has greatly impacted assembly process yield and solder joint reliability. The present study explores the warpage changes of molded PCB during the reflow process. Warpage behavior on molded PCB models has been investigated experimentally and numerically. Experimental set-up employs Shadow Moiré technique to measure real-time warpage measurement for a benchmark model with the size of 10 × 10 ×1 mm. Temperature profile with progressive heating from 25 ℃ to 300 ℃ with an interval of 50 ℃ is employed. Then, the sample undergoes a cooling process until it reaches the room temperature. Numerically, ANSYS FEA simulation was carried out to investigate the warpage on different sizes of PCB models. In addition, thermal stress induced by CTE mismatch is studied to understand its impact on PCB warpage. The results revealed that the experiment and the FEA simulation results are in a good agreement, in particularly at the peak temperature of 300 ℃, with less than 5 % deviation between both results. Moreover, the overall package warpage had also been influenced by package size in the reflow temperature. In addition, the results lead to the suggestion that the thermal stress exerted on the contact surface between different material types could lead to PCB warpages. The present research has established FEA that obtaining good warpage prediction model. The insights attained from this study would be beneficial for PCB design improvement, by optimizing materials and dimensions of PCB, in the attempt to minimize the warpage occurrence.
Ginger seed growth recognition using mask region based convolutional neural network (mask r-cnn)
(2023-01-01)
Tong Yin Syuen
As a plant that poses unique culinary and medical uses, ginger has emerged as a valuable commodity in Asia. Among the critical processes in the production of ginger is ginger seed preparation. It is particularly important to monitor the growth and quality of ginger seeds before they are being sown in growing media to ensure germination. However, to date, the ginger seed monitoring process remains manual and is reliant on human experts, despite the growing demand for more effective and accurate monitoring. In this work, a total 1,746 images consisting 2,230 sprout instances were collected from 282 ginger seed samples. In order to realize the automatic monitoring of ginger seeds, deep learning architectures were employed to detect the ginger seed sprouts in three stages from the digital images. This work assessed and compared the instance segmentation task using end-to-end Mask R-CNN models built by different strategies. Then, a two-stage hybrid detector-classifier model was also proposed to benefit from model task specialization concept. Specifically, an end-to-end binaryclass Mask R-CNN and multi-class classifier were combined to be compared to an end-to-end multi-class Mask R-CNN. The experimental results indicate that the use of the hybrid detector-classifier model developed in this work achieved mAP0.50 of 84.27% at inference time of 0.383 second per image in the detection of 402 images consisting of 514 sprout instances. Besides, substantial confusion between object classes in the model was also observed to be in line with the human expert’s perception in data annotation.
Hole quality assessment of drilled carbon fiber reinforced polymer (cfrp) panel using three type of drill bit
(2024-08-01)
Muhammad Faris Shauqi, Kamaruzaman
Drilling carbon fiber reinforced polymer (CFRP) is essential for maintaining thrust force and hole quality through multiple drilling processes. The aerospace industry demands excellent hole quality for its drilling procedures involving highly abrasive CFRP. While many twist drills exhibit good hole quality performance, this research explores three different unique twist drill bit geometries like tapered web, burnishing drill bit, and subland reamer which focusing on helix angle, primary clearance, point angle, and chisel angle. These drill bits, made of powder tungsten carbide undergoing the sintering process, are used to drill CFRP panels. The main objective of this research is to optimize drilling parameters to minimize thrust force, hole surface roughness, hole diameter error, and hole delamination across all unique drill bit designs. The study considers spindle speed (ranging from 1500 rev/min to 4500 rev/min) and feed rate (ranging from 0.05 mm/rev to 0.1 mm/rev). The results are then evaluated using analysis of variance (ANOVA) to determine the impact of different drilling parameters on the maximum thrust force and hole integrity. The findings suggest that the best drilling parameters are observed with R1 (1500 rev/min and 0.05 mm/rev) for tapered web, R1 (1500 rev/min and 0.05 mm/rev) for burnishing, and R2 (1500 rev/min and 0.075 mm/rev) for subland reamer drill bit designs, showing the least thrust force, lowest hole surface roughness, minimal hole diameter error, and least hole delamination. In conclusion, thrust force is directly proportional to hole surface roughness, hole diameter, and hole delamination when drilling CFRP in a single shot operation. Higher drilling parameters for each drill bit design result in increased values for all responses, emphasizing the need to improve twist drill designs in terms of geometries for optimal performance in all attempts.

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