Technical trends in intelligent monitoring of maintenance status to drive the intelligent transformation of machine tools

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The last edit to this post was made by ztj1118 on 2015-8-10 at 17:38. The \"Office for the Implementation and Management of Major Science and Technology Projects\" related to high-end CNC machines and basic manufacturing equipment, through in-depth research, systematically identified six technological trends in the automation of machine tools: the first is the intelligence involved in monitoring the operating status of machine tools. In the monitoring of machine tools during operation, the most significant progress has been made in terms of the intelligence of the spindle; high levels of intelligence are achieved through sensing systems equipped with temperature sensors and load-displacement sensors. Here, MEMS temperature sensors are primarily used to monitor the lubrication condition of the bearings, prevent bearing sintering, and correct the thermal displacement of the spindle ； Abnormal loads during processing are detected using load-displacement sensors, bearing loads are monitored, and their lifespan is estimated to prevent bearing damage. Since the spindle is close to the workpiece processing area, it is more suitable for accurately monitoring the machining condition of the machine tool. However, installing a sensing system within the limited space of the spindle is not simple, and there are still many challenges. Thermal displacement of the structure is detected by installing FBG sensors (strain sensors) in the structural materials, thereby identifying and correcting the thermal displacement patterns of the machine tool’s structure, and controlling the temperature distribution within the main structure to minimize thermal deformation. Additionally, the temperature of several monitoring points in the machine tool’s structure and information on the spindle’s operation are utilized to adjust the relative thermal deformation between the tool and the workpiece through CNC commands. The second is the intelligence in monitoring maintenance status. To reduce the burden of maintenance work, a system that allows for taking measures before major failures occur is necessary; therefore, it is very important to monitor the maintenance status on a regular basis. Accumulating historical data on the operating conditions of machine tools and using it to predict their lifespan, as well as detecting the lifespan while they are in operation, can be considered challenges for the future. Third is the intelligence that ensures safety. The latest intelligent technologies aimed at ensuring safety can be described as technologies that prevent collisions. Through the program, interference checks can be carried out during movement as well as during preparation.