Simulation of ant colony optimization on hole making performance

Hole making operation one of machining process widely used in industrial industry. One of the main criteria in determining the efficiency of machining performance in hole making operation is shortest machining time. In this paper, simulation approach based on Ant colony optimization (ACO) has been done on hole making operation in order to minimize the machining time. The result based on ACO has been compared with the result obtain based on Genetic Algorithm (GA). Based on the simulation results, the ACO is enhance the performance of hole making process by reducing 13.5% of machining time. The results show that ACO is capable to minimize the machining time of hole making procees

Pengoptimuman jarak laluan mata alat menggunakan algoritma koloni semut untuk proses pengisaran poket

Pada masa kini, proses pemesinan kisar poket menggunakan mesin Kawalan Komputer Berangka (CNC) banyak digunakan dalam pemotongan logam. Terdapat dua langkah pemesinan di dalam proses pengisaran poket iaitu pemesinan kasar dan kemasan. Pemesinan kasar mengambil masa lebih 50 % dari keseluruhan masa pemotongan kerana sejumlah besar bahan kerja dipotong sehingga hampir menyerupai bentuk yang dikehendaki. Oleh itu, adalah penting untuk mempercepatkan masa pemesinan kasar. Pemesinan kontur selari dapat menghasilkan masa pemesinan kasar yang lebih rendah berbanding zigzag dan satu hala. Walau bagaimanapun, terdapat satu masalah di dalam pemesinan kontur iaitu berlaku bahagian lebihan tidak terpotong pada bahagian bucu dan tengah. Kawasan lebihan tidak terpotong ini berlaku kerana penetapan nilai selang antara kontur (ω) yang melebihi jejari mata alat (r). Salah satu cara untuk memotong kawasan lebihan ini adalah dengan menambahkan satu laluan mata alat tambahan (Llt) ke atas laluan asal, iaitu laluan kontur selari. Kaedah penghasilan laluan mata alat tambahan yang diperkenalkan kajian terdahulu berjaya untuk memotong keseluruhan kawasan lebihan ini. Namun, laluan yang dihasilkan oleh kajian sebelum ini tidak mempertimbangkan pergerakan mata alat yang menyumbang kepada peningkatan jarak laluan mata alat dan masa pemesinan kasar. Oleh itu, objektif kajian ini adalah untuk mengoptimumkan laluan mata alat bagi menentukan jarak laluan mata alat yang minimum di dalam proses pengisaran poket berdasarkan pemesinan kontur selari menggunakan kaedah cerdik buatan (AI). Algoritma kontur selari (Algo-KS) dibina bagi menghasilkan laluan mata alat secara kontur selari dan untuk menentukan kawasan lebihan tidak dipotong. Algoritma Koloni Semut berdasarkan aturan peralihan baru (ACO-PB) telah diperkenalkan untuk menentukan pergerakan mata alat bagi memotong kawasan lebihan berdasarkan aturan peralihan dan jarak minimum di antara dua kawasan lebihan. ACO-PB telah diuji keberkesanannya ke atas dua model iaitu model pertama dan model kedua bagi menentukan masa pemesinan kasar (Tmk). Seterusnya, Tmk yang diperoleh ini disahkan keputusannya menggunakan proses uji kaji pemesinan. Uji kaji dilakukan dengan mempraktikkan laluan mata alat yang dihasilkan berdasarkan ACOPB ke dalam mesin kisar CNC tiga-paksi. Bahan kerja Aluminium 6061 dan mata alat jenis keluli laju tinggi (HSS) hujung rata yang bersalut Titanium Nitrida digunakan sepanjang proses pemesinan kasar. Hasil kajian mendapati terdapat perbezaan Tmk sebanyak 7.2 % di antara Tmk ACO-PB dan uji kaji. Keputusan ini telah mengesahkan bahawa ACO-PB yang dibangunkan berupaya untuk meminimumkan jarak laluan mata alat dan dapat dipraktikkan di dalam proses pemesinan sebenar. Llt dan Tmk yang dihasilkan ACO-PB juga telah dibandingkan dengan Llt dan Tmk yang diperoleh berdasarkan kajian terdahulu. Keputusan simulasi menunjukkan ACO-PB telah menghasilkan laluan mata alat yang lebih pendek sebanyak 23.7 % dan pengurangan Tmk sebanyak 4.95 % berbanding kajian terdahulu. Kajian ini juga telah membandingkan Tmk yang diperoleh menggunakan ACO-PB dan Mastercam dan mendapati ACO-PB berjaya mengurangkan Tmk sebanyak 46.5 %. Sebagai kesimpulan, kajian ini telah berjaya membangunkan algoritma ACO-PB yang berupaya untuk meminimumkan jarak laluan mata alat di dalam pemesinan kontur selari dan mengurangkan masa pemotongan bagi proses pemesinan kasar

Pengoptimuman jarak laluan mata alat menggunakan algoritma koloni semut untuk proses pengisaran poket

Pada masa kini, proses pemesinan kisar poket menggunakan mesin Kawalan Komputer Berangka (CNC) banyak digunakan dalam pemotongan logam. Terdapat dua langkah pemesinan di dalam proses pengisaran poket iaitu pemesinan kasar dan kemasan. Pemesinan kasar mengambil masa lebih 50 % dari keseluruhan masa pemotongan kerana sejumlah besar bahan kerja dipotong sehingga hampir menyerupai bentuk yang dikehendaki. Oleh itu, adalah penting untuk mempercepatkan masa pemesinan kasar. Pemesinan kontur selari dapat menghasilkan masa pemesinan kasar yang lebih rendah berbanding zigzag dan satu hala. Walau bagaimanapun, terdapat satu masalah di dalam pemesinan kontur iaitu berlaku bahagian lebihan tidak terpotong pada bahagian bucu dan tengah. Kawasan lebihan tidak terpotong ini berlaku kerana penetapan nilai selang antara kontur (ω) yang melebihi jejari mata alat (r). Salah satu cara untuk memotong kawasan lebihan ini adalah dengan menambahkan satu laluan mata alat tambahan (Llt) ke atas laluan asal, iaitu laluan kontur selari. Kaedah penghasilan laluan mata alat tambahan yang diperkenalkan kajian terdahulu berjaya untuk memotong keseluruhan kawasan lebihan ini. Namun, laluan yang dihasilkan oleh kajian sebelum ini tidak mempertimbangkan pergerakan mata alat yang menyumbang kepada peningkatan jarak laluan mata alat dan masa pemesinan kasar. Oleh itu, objektif kajian ini adalah untuk mengoptimumkan laluan mata alat bagi menentukan jarak laluan mata alat yang minimum di dalam proses pengisaran poket berdasarkan pemesinan kontur selari menggunakan kaedah cerdik buatan (AI). Algoritma kontur selari (Algo-KS) dibina bagi menghasilkan laluan mata alat secara kontur selari dan untuk menentukan kawasan lebihan tidak dipotong. Algoritma Koloni Semut berdasarkan aturan peralihan baru (ACO-PB) telah diperkenalkan untuk menentukan pergerakan mata alat bagi memotong kawasan lebihan berdasarkan aturan peralihan dan jarak minimum di antara dua kawasan lebihan. ACO-PB telah diuji keberkesanannya ke atas dua model iaitu model pertama dan model kedua bagi menentukan masa pemesinan kasar (Tmk). Seterusnya, Tmk yang diperoleh ini disahkan keputusannya menggunakan proses uji kaji pemesinan. Uji kaji dilakukan dengan mempraktikkan laluan mata alat yang dihasilkan berdasarkan ACO-PB ke dalam mesin kisar CNC tiga-paksi. Bahan kerja Aluminium 6061 dan mata alat jenis keluli laju tinggi (HSS) hujung rata yang bersalut Titanium Nitrida digunakan sepanjang proses pemesinan kasar. Hasil kajian mendapati terdapat perbezaan Tmk sebanyak 7.2 % di antara Tmk ACO-PB dan uji kaji. Keputusan ini telah mengesahkan bahawa ACO-PB yang dibangunkan berupaya untuk meminimumkan jarak laluan mata alat dan dapat dipraktikkan di dalam proses pemesinan sebenar. Llt dan Tmk yang dihasilkan ACO-PB juga telah dibandingkan dengan Llt dan Tmk yang diperoleh berdasarkan kajian terdahulu. Keputusan simulasi menunjukkan ACO-PB telah menghasilkan laluan mata alat yang lebih pendek sebanyak 23.7 % dan pengurangan Tmk sebanyak 4.95 % berbanding kajian terdahulu. Kajian ini juga telah membandingkan Tmk yang diperoleh menggunakan ACO-PB dan Mastercam dan mendapati ACO-PB berjaya mengurangkan Tmk sebanyak 46.5 %. Sebagai kesimpulan, kajian ini telah berjaya membangunkan algoritma ACO-PB yang berupaya untuk meminimumkan jarak laluan mata alat di dalam pemesinan kontur selari dan mengurangkan masa pemotongan bagi proses pemesinan kasar

Intervensi Modul Bimbingan Islam Terhadap Masalah Kecelaruan Kebimbangan Umum Dalam Kalangan Pelajar Universiti: Satu Kajian Kes

This study seeks to identify the root causes and the effects on individuals with generalized anxiety disorder and also to measure the effectiveness of the Islamic guidance in treating this disease via an Islamic Guidance Module. Kajian ini bertujuan untuk mengenal pasti punca dan kesan yang dialami oleh penghidap penyakit kecelaruan kebimbangan umum serta mengukur keberkesanan intervensi bimbingan Islam di dalam merawat penyakit ini

Effect of contour interval on minimization of tool path length in pocket milling process

Reduction of machining time in the pocket machining process is important in order to enhance performance and increase productivity. In this paper, the main objective is to decrease the roughing time in pocket milling process by investigating the effect of path interval caused by the uncut area in the pocket milling with sharp corner. Decreasing machining time in process of milling using contour parallel direction as a strategy of machining can be achieved by increasing the value of tool path interval. Though, increasing the tool path interval has caused the existence of an uncut area at the sharp corner. To remove this uncut area, an additional tool path length is generated. So, this paper is carried out to study the consequence of path interval upon the existence of uncut region and the impact to the path length of contour parallel. There were three different values of tool path interval chosen and set to study the consequence of cutting tool path interval on tool path length, which were 5.6 μm, 5.7 μm, and 5.9 μm. Ant colony algorithm was developed to minimise the additional path length. As a result, increasing the path interval has produced larger uncut region at the corner. However, it produced shorter additional tool path length which resulted in lower roughing time

Greenhouse Gas Reduction by Utilization of Cold LNG Boil-off Gas

AbstractThis paper present the analysis of utilization the cryogenic temperature of Boil off Gas (BOG) from Liquefied Natural Gas (LNG) to flow air inside insulation space of LNG. Three Dimensional geometry of the tank are model in Computational Fluid Dynamic (CFD) ANSYS Fluent software package using steady state and K-Epsilon turbulence model. Result shows that almost 60% of BOG can be prevented from flared to the atmosphere thus will reduce Greenhouse Gas (GHG) emission and pollution

An Efficient and Robust Mobile Augmented Reality Application

AR technology is perceived to be evolved from the bases of Virtual Reality (VR) technology. The ultimate goal of AR is to provide better management and ubiquitous access to information by using seamless techniques in which the interactive real world is combined with an interactive computer-generated world in one coherent environment. The direction of research in the field of AR has been shifted from traditional Desktop based mediums to the mobile devices such as the smartphones. However, image recognition on smartphones enforces many restrictions and challenges in the form of efficiency and robustness which are the general performance measurement of image recognition. Smart phones have limited processing capabilities as compared to the PC platform, hence the process of mobile AR application development and use of image recognition algorithm need to be emphasised. The processes of mobile AR application development include detection, description and matching. All the processes and algorithms need to be carefully selected in order to create an efficient and robust mobile AR application. The algorithm used in this work for detection, description and matching are AGAST, FREAK and Hamming distance respectively. The computation time, robustness towards rotation, scale and brightness are evaluated. The dataset used to evaluate the mobile AR application is the benchmark dataset; Mikolajczyk. The results showed that the mobile AR application is efficient with a computation time of 29.1ms. The robustness towards scale, rotation and brightness changes of the mobile AR application also obtained high accuracy which is 89.76%, 87.71% and 83.87% respectively. Hence, combination of algorithm AGAST, FREAK and Hamming distance are suitable to create an efficient and robust mobile AR application

Study on the ability of black soldier fly larvae for reducing the house fly eggs in poultry manure

Black soldier fly larvae (BSFL) are a good source of protein for aquaculture, animal feed, pet and human nutrition. Larvae have a healthy appetite and can be used to make household waste compost and residual agricultural. For previous study [1], observed that the BSFL can be grown in a variety of organic waste stream including pig manure, kitchen waste, fruits and vegetables, and given to the fish. In addition, the larvae benefit from the use of natural resources to overcome the problem of life cycle of widespread flies in the poultry farm openly. Therefore, it is important to note that the poultry farms release many particles into the air that endanger human health and the environment

Minimization of tool path length of drilling process using particle swarm optimization (PSO)

In the era of challenging economic, the industry in our country has been forced to produce a good quality product and increase the productivity of machining process simultaneously in order to compete with other countries. Drrilling process is one of a very important cutting process in industry. In a drilling for machining by Computer Numerical Control (CNC) such as drilling machines, the parameter of the tool routing path for the machining operation plays a very important role to minimize the machining time (Tiwari 2013, Rao and Kalyankar 2012) . This machine can be used with procedures for drilling, spreading, weaning and threading with a lot of the holes precisely. In order to increase the efficiency and productivity of drilling process, optimization on parameters of process can lead to better performance. Optimization of holes drilling operations will lead to reduction in time order and better productivity of manufacturing systems. Optimizing the tool path has played an important role, especially in mass production because reducing the time to produce one piece eventually lead to a significant reduction in the cost of the entire series (Pezer, 2016). In various publications and articles, scientists and researchers adapted several methods of artificial intelligence (AI) or hybrid optimization method for tool path artificial immune system (AIS), genetic algorithms (GA), Artificial Neural networks (ANN) Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) (Narooei and Ramli, 2014). These methods were been proven that can produce better performance and increase the productivity of drilling process. Therefore, in this study, the Particle Swarm Optimization (PSO) algorithm was develop in order to minimizing the tool path length in the drilling process which can produce the better results for the required machining time process. For this study, the main purpose is to apply the Particle Swarm Optimization (PSO) algorithm for use in searching for the optimal tool routing path for in simulation of drilling proces

Microstructure analysis of aluminium metal matrix alloy with silicon carbide and hexogonal boron nitride

Aluminum metal matrix composite (AMMCs) are considered a group of new advance material for its light, weight, high strength, modulus, low co-efficient of thermal expansion and good wear properties. In recent years, Metal Matrix Composite (MMCs) have attracted much attention due to excellent mechanical properties such as high specific strength and wear resistance (Poletti et al., 2008). AMMCs are widely used in aircraft, aerospace, automobile and various others field. The MMCs encompasses a wide range scale and microstructure. MMCs could be a material with a least two constituent elements. One necessary to be metal whereas another could also be special metal or alternative material like reinforcement ceramic. Metal matrix composite attract great deal of attentions nowadays due to their great mechanical properties and also their application in advance industry. The network is bulk and nonstop material though support is short and end material improved into matrix. The reinforcement should be stable in given working temperature and non-reactive too. The most commonly used reinforcement are silicon carbide (SiC) and aluminum oxide (Al2O3). The primary function of the reinforcement in MMCs is to carry most of the applied load, where the matrix binds the reinforcement together, and transmit and distributes the external load to the individual reinforcement. Good wetting is an essential condition for the generation for satisfactory bond between particles between particles reinforcement. The composite microstructure may be subdivided, as depicted in, according to whether the reinforcement is in the form of continuous fibers, short fibers or particles