Performance evaluation of biodegradable metalworking fluids for machining process

The widely use of metalworking fluids (MWFs) petroleum-based in the industry have a negative impact to the environment and human. Thus, various initiatives have been undertaken to develop bio-based MWFs especially from crude jatropha oil (CJO). However, the main drawback of CJO is that it has low thermal-oxidative stability. Therefore, the objective of this study is to develop a new formulation of CJO-based MWFs. The newly developed modified jatropha oils (MJOs) were formulated using transesterification process at various molar ratios of jatropha methyl ester to trimethylolpropane (JME:TMP) denoted by MJO1 (3.1:1), MJO3 (3.3:1) and MJO5 (3.5:1). Later, the MJOs were blended with hexagonal boron nitride (hBN) particles at various concentrations (0.05 to 0.5wt.%). MJOs with and without hBN particles were analysed based on the physicochemical properties, tribology behaviour test, orthogonal cutting and turning proses. From the results, MJO5 showed an improvement at thermal (high viscosity index) and oxidative stability (lubricant storage). MJO5c (MJO5+0.5wt.% of hBN particles) showed the optimum physicochemical properties. In the contrary, MJO5a (MJO5+0.05wt.% of hBN particles) exhibited excellent tribological behaviour as reduction of friction and wear, with high tapping torque efficiency. In the orthogonal cutting process, MJO5a recorded the lowest machining force and temperature, thus contributed to the formation of thinner chips, small tool-chip contact length and reduction of the specific energy. MJO5a produced an excellent result in the machinability test by reducing the cutting force, cutting temperature and surface roughness stimulated longer tool life and less tool wear. In conclusion, the MJO5a has a potential impact on the lubricant market as a sustainable MWFs for the machining processes

A corpus-based lexical and grammatical error identification: L2 learners academic writing

Writing in English has never been an easy task to many second language (L2) learners. Many of them perform poorly in their English academic writing where numerous lexical and grammatical errors are found in their report. Therefore, this thesis investigates the difficulties faced by UTHM learners involved in academic writing by identifying and analyzing errors made by them with the application of error analysis procedures. This research attempts to find out the types and patterns of errors in which it focuses on the frequency of the lexical and grammatical errors of the L2 learners in their writing. Errors were investigated and identified based on students’ 36 progress and final reports which were assembled from first year engineering students; named as the Learner Corpus Universiti Tun Hussein Onn Malaysia(LCUTHM). The LCUTHM was analyzed by means of linguistics Natural Language Processing tools (NLP) such as CLAWS 5 tag set, Markin Version 4 and categorized by MonoConc Pro II in the form of word lists. Data were also analyzed using Statistical Package for the Social Science (SPSS) software to determine the major errors learners committed in learners’ written work. The findings reveal that the major lexical and grammatical error categories made by learners were “Missing Word”, “Repetition”, and “Verb Form”. Finally, the integration of technology and the linguistics Natural Language Processing (NLP) tools can provide a fast and more effective method in assisting teachers in identifying errors, and designing syllabus in improving the language skills and achievement of L2 learners in their academic writing

Performance evaluation of biodegradable metalworking fluids for machining process

The widely use of metalworking fluids (MWFs) petroleum-based in the industry have a negative impact to the environment and human. Thus, various initiatives have been undertaken to develop bio-based MWFs especially from crude jatropha oil (CJO). However, the main drawback of CJO is that it has low thermal-oxidative stability. Therefore, the objective of this study is to develop a new formulation of CJO-based MWFs. The newly developed modified jatropha oils (MJOs) were formulated using transesterification process at various molar ratios of jatropha methyl ester to trimethylolpropane (JME:TMP) denoted by MJO1 (3.1:1), MJO3 (3.3:1) and MJO5 (3.5:1). Later, the MJOs were blended with hexagonal boron nitride (hBN) particles at various concentrations (0.05 to 0.5wt.%). MJOs with and without hBN particles were analysed based on the physicochemical properties, tribology behaviour test, orthogonal cutting and turning proses. From the results, MJO5 showed an improvement at thermal (high viscosity index) and oxidative stability (lubricant storage). MJO5c (MJO5+0.5wt.% of hBN particles) showed the optimum physicochemical properties. In the contrary, MJO5a (MJO5+0.05wt.% of hBN particles) exhibited excellent tribological behaviour as reduction of friction and wear, with high tapping torque efficiency. In the orthogonal cutting process, MJO5a recorded the lowest machining force and temperature, thus contributed to the formation of thinner chips, small tool-chip contact length and reduction of the specific energy. MJO5a produced an excellent result in the machinability test by reducing the cutting force, cutting temperature and surface roughness stimulated longer tool life and less tool wear. In conclusion, the MJO5a has a potential impact on the lubricant market as a sustainable MWFs for the machining processes

Optimization of RFID network planning for monitoring railway mechanical defects based on gradient-based Cuckoo search algorithm

Radio Frequency Identification (RFID) is an increasingly widespread and applied technology of automatic real-time monitoring and control railway assets. For that, the present research has developed an RFID network-planning model that can improve real-time information detection based on the temperature and vibration in the gear and motor of the train bogies. The selected system was Kuala Lumpur railway system, which has been operating in the city of 243 km2 area. It involves three challenges which represent the objectives of this thesis; the first is how to deal with the large�scale area and huge number of stations based on functional features. The second is how to decide which station (or stations) is suitable to be applied with the RFID system to help in monitoring the trains effectively. Finally, the third challenge is how to find the optimal evolutionary method for railway network planning to increase the RFID system performance. The solution strategy started in its initial input and process to find effective stations that can serve the railway monitoring system well. The researcher developed a new clustering model to separate the necessary data from unnecessary data, and specified the suitable primary stations. For the second objective, the Analytic Hierarchy Process (AHP) was used to decide which stations can be used to monitor the railway system optimally. The Gradient-Based Cuckoo Search (GBCS) algorithm was used to achieve the final objective. It solved the multi-objective functions of RNP challenge. In the validation process, the results showed a superior finding compared to the firefly algorithm. It was able to detect more tags by 3%, and a reduced number of readers by 16.6%. In the large-scale area application, the GBCS algorithm achieved 100%, 93.75%, and 98.9% coverage for Maluri, Subang, and TBS stations, respectively. In conclusion, this study presented a novel hybrid evolutionary algorithm based on the combination of AHP with GBCS to specify optimal RFID reader positions and amount based on the working train station domain. The present method has proven its precise performance in RNP of large-scale area based on real-time railway monitoring tasks

Correlation between the golden ratio and nanowire transistor performance

An observation was made in this research regarding the fact that the signatures of isotropic charge distributions in silicon nanowire transistors (NWT) displayed identical characteristics to the golden ratio (Phi). In turn, a simulation was conducted regarding ultra-scaled n-type Si (NWT) with respect to the 5-nm complementary metal-oxide-semiconductor (CMOS) application. The results reveal that the amount of mobile charge in the channel and intrinsic speed of the device are determined by the device geometry and could also be correlated to the golden ratio (Phi). This paper highlights the issue that the optimization of NWT geometry could reduce the impact of the main sources of statistical variability on the Figure of Merit (FoM) of devices. In the context of industrial early successes in fabricating vertically stacked NWT, ensemble Monte Carlo (MC) simulations with quantum correction are used to accurately predict the drive current. This occurs alongside a consideration of the degree to which the carrier transport in the vertically stacked lateral NWTs are complex

Optimization of PEDOT: PSS thin film for organic solar cell application

As a clean and renewable energy source, the development of the organics solar cells is very promising due to the inorganic solar cell inconvenient production process and material shortness. In this work, P3HT: PCBM bulk-heterojunction devices were produced by spin coating organic layers onto ITO coated glass in air, and deposited it with an Au layer as top metal electrode. Inverted devices were fabricated with and without PEDOT:PSS. Then, several attempts have been conducted to improve power conversion efficiency by optimizing different thicknesses of the interlayer between active layer and metal. Power conversion efficiency, short circuit current, open circuit voltage and fill factor were measured on all produced devices. In contrast, the devices with 50 nm thickness of PEDOT: PSS layer showed as better solar cell with 0.0394% efficiency compared to the devices without PEDOT:PSS. As a result, introduction of PEDOT:PSS layer on active layer improves hole collection at the metal / active layer interface

Are foreign multinationals more efficient? A stochastic production frontier analysis of Malaysia's automobile industry

This paper compares the sources of total factor productivity (TFP) growth of foreign (establishments with 51% and above foreign equity ownership) and local establishments in Malaysia’s automotive sector by applying a stochastic production frontier to a panel of 510 plants for the period 2000-2004. The results showed that TFP growth for local automobile plants was minimal at 0.63% and minimally negative at -0.27% for foreign plants. On average,over the study period, technical efficiency changes contributed positively toward TFP growth but scale efficiency changes were negative for both local and foreign establishments. Technical progress was minimally positive for local establishments and minimally negative for foreign establishments.The small size of plants and the lower share of white-collar workers were significant in explaining plant inefficiency in Malaysia’s automobile sector. A higher capital-labour ratio was positively related to plant inefficiency and this may be due to excess capacity in the automobile sector as a result of a small domestic market. Finally, foreign multinationals are significantly more efficient than locally owned plants

The cognitive bases for the design of a new class of fuzzy logic controllers: The clearness transformation fuzzy logic controller

This paper analyses the internal operation of fuzzy logic controllers as referenced to the human cognitive tasks of control and decision making. Two goals are targeted. The first goal focuses on the cognitive interpretation of the mechanisms employed in the current design of fuzzy logic controllers. This analysis helps to create a ground to explore the potential of enhancing the functional intelligence of fuzzy controllers. The second goal is to outline the features of a new class of fuzzy controllers, the Clearness Transformation Fuzzy Logic Controller (CT-FLC), whereby some new concepts are advanced to qualify fuzzy controllers as 'cognitive devices' rather than 'expert system devices'. The operation of the CT-FLC, as a fuzzy pattern processing controller, is explored, simulated, and evaluated

Data Envelopment Analysis (Dea) approach In efficiency transport manufacturing industry in Malaysia

The objective of this study was to measure of technical efficiency, transport manufacturing industry in Malaysia score using the data envelopment analysis (DEA) from 2005 to 2010. The efficiency score analysis used only two inputs, i.e., capital and labor and one output i.e., total of sales. The results shown that the average efficiency score of the Banker, Charnes, Cooper - Variable Returns to Scale (BCC-VRS) model is higher than the Charnes, Cooper, Rhodes - Constant Return to Scale (CCR-CRS) model. Based on the BCC-VRS model, the average efficiency score was at a moderate level and only four sub-industry that recorded an average efficiency score more than 0.50 percent during the period study. The implication of this result suggests that the transport manufacturing industry needs to increase investment, especially in human capital such as employee training, increase communication expenses such as ICT and carry out joint ventures as well as research and development activities to enhance industry efficiency