Real-time adaptive cutting tool flank wear prediction.

摘要

In modern manufacturing industry, automation is main stream to create products rapidly and economically. Many researches for automation are also going in the metal cutting industry. Therefore, computer Numerical Controlled (CNC) machines are widely used to achieve this goal while maintaining flexible production. Although the advent of CNC in the cutting industry has given many conveniences and benefits, CNC still has many limits. For example, contemporary CNC machines often cannot anticipate the problems caused by unexpected changes in the workpiece. Consequently, much research has been done to develop techniques to respond to these changes.;For automation in metal cutting, it is very important to predict workpiece and tool condition. In turning operations, unexpected changes in the workpiece material properties can have negative effects on the efficiency of the operation and quality of the product. Variations in workpiece hardness and dimensions can cause variation in cutting forces, which can then lead to accelerated tool wear and even breakage. Such problems can be overcome during CNC operations by measuring the variation in hardness in the workpiece and adjusting the cutting conditions to account for increased forces. However, there are limitations to in-process measurements of material hardness. Conventional hardness measurement devices require contact with the material being measured, which can be time-consuming and may damage the workpiece. A method to detect variations in workpiece hardness that does not rely on contact could preserve tool life without costing additional time or creating damage in the workpiece. Theoretically, the spindle power required for turning operations in hard materials is higher than that required for soft materials. Therefore, a power sensor provides a novel means of detecting hardness changes in the work material without affecting the cutting process.;Tool condition monitoring is important part for automation in metal cutting and many researches for tool condition monitoring have been done. Currently, many wear models are known. However, there is limitation because metal cutting process is very complex and has various conditions. In this research, flank wear was considered the main wear factor. Flank wear arises due to both adhesive and abrasive wear mechanisms from the intense rubbing action of the two surfaces in contact, i.e., the clearance face of the cutting tool and the newly formed surface of the workpiece. Its rate of increase at the beginning of the tool life is rapid, settling down to a steady state then accelerating rapidly again at the end of tool life. Flank wear leads to a deterioration of surface quality, increased contact area and, consequently, increased heat generation. Flank wear models have been developed for specific workpieces made of a single material in many studies. However, if workpiece material properties (such as hardness) are changed during operation, the existing flank wear models cannot be used, because general flank wear models cannot reflect the real-time workpiece material changes. Therefore, the flank wear model what is possible to use in cutting of workpiece jointed parts of different materials.;First, the sensor what can detect the workpiece material change was decided. Three different types of sensors (power sensor, ultimate thermometer, and dynamometer) were tested for feasibility of detecting workpiece material changes. In the case of the ultimate thermometer, an infrared sensor was tested, and problems arose due to the difficulty of focusing on the tool edge. The dynamometer was found to be good for detecting the workpiece changes, but installation is difficult and also expensive. The dynamometer also adds unwanted vibrations by increasing the length of tool holder. The power sensor was installed to measure the spindle motor power. The power sensor was found to be the most practical choice for a sensor to detect the workpiece material changes. This is because installation of the sensor is easy compared to the dynamometer and it is also cheaper than the dynamometer.;In this dissertation, the ultimate objective is to demonstrate the real-time flank wear model using a power sensor. This proposed model estimates the flank wear even for a workpiece with varying material properties. To validate proposed model, two different materials was used for cutting test. 8620 alloy steel was as soft metal and P20 tool steel was used as hard metal. Results show that proposed model can be used in cutting of workpiece combined with parts of different materials. However, consistency of tool is very important. In case of low quality tool, flank wear rate was not same when tool was changed. But, the flank wear rate was maintained in sing tool even thought cutting was performed with parts of different materials. (Abstract shortened by UMI.)