Development of Proficient Machines for Manufacturing

点击翻译按钮获取中文摘要

In this report, scraping operation is firstly analyzed in order to investigate the proficient process of human. The scraping is a process to generate flat surfaces from roughly cut surfaces. It is found that the proficiency of the scraping consists of the understanding of surface shpes, planning scraping sequences, and the removal of unnecessary parts.Second, a prototype of a proficient machine tool is developed. The proficient machine tool can design machining process via process simulation and can update the process model through actual machining. Namely, it has a capability of learing from operation experience. In the learning, a desirable process model is selected among multiple process models via process simulation. After actual milling, new process model parameters are derived from measured sensor signals using a mathematical programming method. The process model correponding to current conditions is adjusted and is memorized by use of a memory-based learning. It is found that prediction correctness of the process simulation can be improved as the machine tool obtains much experience of the machining.Third, a prototype of a proficient manipulator is developed. It is consists of a sensor-feedback manipulator, a device capable of measuring human skillful motion, and a workstation for operation model construction and operation planning. Transplanting human skillful motion to a manipulator is examined. Human action during the insertion of a deformable hose into a plug is measured by use of the position and the force sensors, and analyzed with regard to the contact between the hose and the plug. It is found that the pull motion during the process is effective for the successful insertion of a deformable hose into a plug. Embedding effective pull motion in a manipulator program, it turns out that the manipulator can perform the insertion successfully.