| Since its first application to manufacturing industry in 1940s, the electrical discharge machining (EDM) has experienced a great development. In the key manufacturing industries such as mould, national defense and aerospace industry, EDM plays an irreplaceable and crucial place. There are so many influencing factors which have complicated relationship with each other in EDM that it's impossible to describe the EDM process using a standard mathematical model. Compared with other mechanical machining method, it is more difficult to master the technology of process planning in EDM.Miniaturization and high precision machining are the most important characteristics of modern manufacturing technology, whereas the complexity of the process planning in EDM has severely hindered the development of EDM technology. Meantime the Artificial Intelligence (AI) technology, which provides a practicable solution to the difficult that EDM is faced with, has experienced a significant development. It is necessary and possible to combine AI and EDM to promote a further development of manufacturing technology. Some foreign machine tools providers have integrated AI technology into their machining systems while domestic machine tools providers are only studying the AI technology without advanced process planning system combined into their equipments. Under such circumstances, this issue studied the utilization of AI technology in machine tools controlling system and successfully integrated the AI technology into the system.Considering the features and contents of EDM process planning, this issue proposed a framework of an intelligent process planning system. Then the functional requirements of each composition modules of the system are put forward and realized. Artificial Neural Network was adopted to realize the function of self-directed learning, making up for the deficiency of Expert System in knowledge-obtaining. Fuzzy Reasoning technology was introduced to carry out human-like reasoning process, which helps the operator to a large extent.Based on the two kinds of existing machining allowance distribution models, this issue introduced a conception of weights between security and efficiency, providing the operator optimized NC according to their requirements.At present all of the AI Technology planning systems used in EDM equipments only take the efficiency of the machining, processing of the economy and the surface quality of the final machining into consideration while shaping precision was neglected. At present all of the Artificial Intelligence Technology planning systems in EDM technology only consider the efficiency of the machining, processing of the economy and the surface quality of the final machining while neglecting shaping precision, which means that high precision machining of complex shapes could not be machined using these systems.This issue hold that versatile database should be added into the process planning systems to consider the shaping precision. Now a Die-Sinking EDM simulation model, which could simulate the process of shapes changing in Die-Sinking EDM, has been put forward. In this simulation model, a discharge location searching algorithm base on the discharge delay time was used to determine the discharge location. The searching algorithm believes that in single pulse duration, discharge occurs at the spot which has the shortest discharge delay time on the surface of electrodes. Key point of this simulation is the establishment of discharge delay time database. As a foundation of a more intelligent machining process planning system, this issue carried out a series of experiments to study the influencing factors of discharge delay time in single pulse discharge. |
PDF Full Text Request