No abstract

The Swiss-type lathe is a specialized turning machine of Swiss-origin with a wide range of applications across the precision machining industry. Its unique features enable it to mass produce parts at high speeds and with high precision. However, the complex non-symmetric structure of the machine tool makes it particularly susceptible to the adverse effects of thermal influences. These internal and external thermal influences cause an offset at the tool center point and degrade the accuracy of the produced part. It is a common practice in Swiss-type lathe machining for an operator to open the machine door during a production run to exchange tools or inspect the produced part. Consequently, thermal boundary conditions change rapidly when cooler ambient air enters the working space of the machine tool and when the air heats up after the machine tool is restarted. The machine tool exhibits short cool-down and warm-up cycles during which the thermal errors change abruptly and can be challenging to compensate, as it is well known in the machine tool industry. This work develops a novel methodology based on artificial intelligence that compensates thermal errors associated with sudden boundary condition changes. The results show that thermal error residual peaks associated with a machine tool door opening are significantly attenuated and the peak-to-peak thermal error of the Swiss-type lathe is reduced.