Computer aided manufactoring intelligent optimisation

CAMIO项目旨在针对2.5轴和3轴切割策略，对在高生产率加工中心上加工零件进行“实时”和最佳选择。结果将缩短数控程序准备时间，减少机床停机时间，降低加工成本，延长刀具寿命，提高车间工作人员的灵活性。这将通过人工智能学习和优化技术(如遗传算法和神经网络)和快速实施(通过基于并行计算的卸载加速器技术)相结合来实现。这将减少为复杂对象开发和优化CAM设计的时间，速度可达数量级。一个高度稳健的解决方案将通过从分析结果中学习来提供，以便获得最优解。

The CAMIO project aims to make a 'real time' and optimum selection, in relation to 2.5 and 3 axis cutting strategies, for machining parts on high productivity machining centres. The results will lead to a reduction of CNC program preparation time, reduced machine tool downtime, reduced machining costs, longer cutting tool life and greater flexibility of shop floor personnel. This will be achieved through a combination of AI learning and optimisation techniques (such as Genetic Algorithms and Neural Networks) and fast implementation (through off load accelerator techniques based on parallel computing). This will reduce the time to develop and optimise a CAM design, for a complex object, by orders of magnitude. A highly robust solution will be ' delivered by learning from analysed results in order to obtain the optimum solution.