Silicon Carbide (SiC) machining by traditional methods with regards to its high hardness is not possible. Electro Discharge Machining, among non-traditional machining methods, is used for machining of SiC. The present...Silicon Carbide (SiC) machining by traditional methods with regards to its high hardness is not possible. Electro Discharge Machining, among non-traditional machining methods, is used for machining of SiC. The present work is aimed to optimize the surface roughness and material removal rate of electro discharge machining of SiC parameters simultaneously. As the output parameters are conflicting in nature, so there is no single combination of machining parameters, which provides the best machining performance. Artificial neural network (ANN) with back propagation algorithm is used to model the process. A multi-objective optimization method, non-dominating sorting genetic algorithm-II is used to optimize the process. Affects of three important input parameters of process viz., discharge current, pulse on time (Ton), pulse off time (Toff) on electric discharge machining of SiC are considered. Experiments have been conducted over a wide range of considered input parameters for training and verification of the model. Testing results demonstrate that the model is suitable for predicting the response parameters. A pareto-optimal set has been predicted in this work.展开更多
Machine learning is an Artificial Intelligence (or AI) application, an idea that came into being by giving machines access to data and letting them learn by themselves. AI has been making headlines, especially since C...Machine learning is an Artificial Intelligence (or AI) application, an idea that came into being by giving machines access to data and letting them learn by themselves. AI has been making headlines, especially since ChatGPT was introduced. Malaysia has taken many significant steps to embrace and integrate the technology into various sectors. These include encouraging large companies to build AI infrastructure, creating AI training opportunities (for example, the local media reported Microsoft and Google plan to invest USD 2.2 billion and USD 2 billion, respectively, in the said activities), and, as part of AI Talent Roadmap 2024-2030, establishing AI faculty in one of its public universities (i.e., “Universiti Teknologi Malaysia”) leading the way in the integration and teaching of AI throughout the country. This article introduces several products developed by the author (for the energy and transportation industries) and recommends their improvement by incorporating Machine learning.展开更多
Be directed against the development trend of modern CNC grinding machine towards high precision and high efficiency, some general weaknesses of existing camber grinding machine are analyzed in detail. In order to deve...Be directed against the development trend of modern CNC grinding machine towards high precision and high efficiency, some general weaknesses of existing camber grinding machine are analyzed in detail. In order to develop new type CNC camber grinding machine that can grind complex die, and genuinely achieved accurate feed and high efficient grinding, a new type camber grinding machine is put forward, called non-transmission virtual-shaft CNC camber grinding machine. Its feed system is a parallel mechanism that is directly driven by linear step motor. Therefore, traditional transmission types, such as the ball lead-screw mechanisms, the gears, the hydraulic transmission system, etc. are cancelled, and the feed system of new type CNC camber grinding machine can truly possess non-creep, good accuracy retentiveness a wide range of feed-speed change, high kinematical accuracy and positioning precision, etc. In order to realize that the cutting motion is provided with high grinding speed, step-less speed variation, high rotational accuracy, good dynamic performance, and non-transmission, the driving technology of hollow rotor motor is applied to drive the spindle of new type grinding machine,thus leading to the elimination of the transmission parts of cutting motion. The principle structure model of new type camber grinding machine is advanced. The selection, control gist and driving circuit line of the linear step motor are expounded. The main technology characteristics and application advantages of non-transmission virtual-shaft CNC camber grinding machine are introduced.展开更多
文摘Silicon Carbide (SiC) machining by traditional methods with regards to its high hardness is not possible. Electro Discharge Machining, among non-traditional machining methods, is used for machining of SiC. The present work is aimed to optimize the surface roughness and material removal rate of electro discharge machining of SiC parameters simultaneously. As the output parameters are conflicting in nature, so there is no single combination of machining parameters, which provides the best machining performance. Artificial neural network (ANN) with back propagation algorithm is used to model the process. A multi-objective optimization method, non-dominating sorting genetic algorithm-II is used to optimize the process. Affects of three important input parameters of process viz., discharge current, pulse on time (Ton), pulse off time (Toff) on electric discharge machining of SiC are considered. Experiments have been conducted over a wide range of considered input parameters for training and verification of the model. Testing results demonstrate that the model is suitable for predicting the response parameters. A pareto-optimal set has been predicted in this work.
文摘Machine learning is an Artificial Intelligence (or AI) application, an idea that came into being by giving machines access to data and letting them learn by themselves. AI has been making headlines, especially since ChatGPT was introduced. Malaysia has taken many significant steps to embrace and integrate the technology into various sectors. These include encouraging large companies to build AI infrastructure, creating AI training opportunities (for example, the local media reported Microsoft and Google plan to invest USD 2.2 billion and USD 2 billion, respectively, in the said activities), and, as part of AI Talent Roadmap 2024-2030, establishing AI faculty in one of its public universities (i.e., “Universiti Teknologi Malaysia”) leading the way in the integration and teaching of AI throughout the country. This article introduces several products developed by the author (for the energy and transportation industries) and recommends their improvement by incorporating Machine learning.
文摘Be directed against the development trend of modern CNC grinding machine towards high precision and high efficiency, some general weaknesses of existing camber grinding machine are analyzed in detail. In order to develop new type CNC camber grinding machine that can grind complex die, and genuinely achieved accurate feed and high efficient grinding, a new type camber grinding machine is put forward, called non-transmission virtual-shaft CNC camber grinding machine. Its feed system is a parallel mechanism that is directly driven by linear step motor. Therefore, traditional transmission types, such as the ball lead-screw mechanisms, the gears, the hydraulic transmission system, etc. are cancelled, and the feed system of new type CNC camber grinding machine can truly possess non-creep, good accuracy retentiveness a wide range of feed-speed change, high kinematical accuracy and positioning precision, etc. In order to realize that the cutting motion is provided with high grinding speed, step-less speed variation, high rotational accuracy, good dynamic performance, and non-transmission, the driving technology of hollow rotor motor is applied to drive the spindle of new type grinding machine,thus leading to the elimination of the transmission parts of cutting motion. The principle structure model of new type camber grinding machine is advanced. The selection, control gist and driving circuit line of the linear step motor are expounded. The main technology characteristics and application advantages of non-transmission virtual-shaft CNC camber grinding machine are introduced.
文摘数据驱动的多元化发展导致数据异构性增强、维度提升和特征量规模扩大,给贸易经济分析带来更大挑战。为了提高贸易经济分析的科学性,采用非平行超平面支持向量机算法(support vector machine,SVM)对贸易经济进行预测分析。首先,根据贸易经济影响因素进行主成分分析,获取影响贸易经济的关键特征,并对特征进行量化和去噪处理。然后,采用广义特征值最接近支持向量机(proximal support vector machine via generalized eigenvalues,GEPSVM)进行贸易经济预测分类。根据预测指标要求,选择核函数GEPSVM算法(KGEPSVM算法)对分类的非平行超平面求解,通过类别划分函数获得经济预测结果。实证分析表明,对比常用的非平行超平面支持向量机算法,所提算法的贸易经济预测性能更优,而且在常用贸易经济指标的预测中,表现出较高预测精度和稳定性。
