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Active chatter suppression with monitoring-based process control for self-optimizing machining systems (本文)

大和, 駿太郎 慶應義塾大学

2021.03.23

概要

This dissertation proposed novel enabling technologies for SOMS, where the machine tool can self-actively suppress the chatter vibration according to the monitored chatter state. In the chatter vibration, the “phase shift” is a key factor. All methodologies for chatter detection and suppression proposed in this dissertation are interpreted from the perspective of phase-shift control and monitoring. Additionally, only the internal servo information and motors of the machine tool are utilized to monitor and suppress the chatter.

In Chapter 1, an overview of SOMS functionalities is provided. SOMS is a novel intelligent concept to address the recent high-level manufacturing issues, such as energy/labor-saving, flexibility, traceability, and reliability. The machining chatter problem is a main concern even in SOMS, as it remains a major impediment to productivity. The basic categorization and mechanism of machining chatter are also given, followed by the state-of-the-art enabling technologies for SOMS in the chatter issue. Based on the problems of existing chatter monitoring and suppression techniques, the research direction and concrete objective/applications in this dissertation are explicitly defined.

In Chapter 2, the existing sensorless cutting force estimation techniques using the internal servo information of the machine tool are derived with in-depth description of their characteristics through a series of exemplary simulations and experiments. On one hand, the conventional DOB is useful in the linear-motor-driven stage, where a single-inertia model can be assumed. On the other hand, the expanded DOB techniques, such as MEDOB, LDOB, and VMDOB, should be used in the ball-screw-driven system. These techniques can be applied to machine tools with fully closed ball-screw-driven stages, which have become recent mainstream. In case that the ball-screw-driven system can be regarded as a dual- inertial model, MEDOB, LDOB, and VMDOB can accurately estimate the cutting force with a sufficiently reliable bandwidth. Interestingly, although these three techniques should produce the same estimation results in ideal cases, their behavior is strongly characterized by the internal component forces, contributing to the estimated cutting force. In addition, the limitations of the sensorless cutting force estimation system are mentioned. Especially, the essential limitation is attributed to the complex structural dynamics that make the dual-inertia model ambiguous. To overcome this limitation, the pre-compensation concept with a cutting-data-driven self-optimized compensation digital filter is proposed. If the proposed compensation techniques can be applied successfully, the accuracy of the sensorless cutting force estimation system can be substantially enhanced with sufficient bandwidth. Note that the estimated cutting force can capture a very high-frequency chatter by integrating linear encoder information (i.e., high sensitivity can be maintained), although the estimation accuracy of the spectrum amplitude depends on the modeling error. In this dissertation, the estimated cutting force is consistently used for chatter monitoring.

In Chapter 3, an online chatter detection method is proposed based on the novel concept of phase shift monitoring by using MPF and MEF, which are proposed anew as indices for chatter detection, inspired from the power factor in the AC circuit. The MPF and MEF during the machining process represent the phase differences between the cutting force and tool velocity/displacement, and can be utilized to detect the forced vibration and self-excited (regenerative) chatter, respectively. In addition, a concrete algorithm for type-assorted online fast chatter detection by MPF/MEF with low computational cost is described. Additionally, the system integration with a sensorless cutting estimation technique is proposed. Note that, in principle, the chatter detection with MPF/MEF can be applied to the sensor-based system with a dynamometer and displacement/acceleration sensor. If MEF/MPF can be calculated ideally, on one hand, the MEF becomes rapidly negative when the regenerative chatter occurs. On the other hand, the MPF become fairly close to 1 during only forced vibration (i.e., resonance). The experimental verification is performed in the prototype precision lathe with linear-motor-driven stage, where the SDoF system can be ideally assumed and a highly accurate cutting force estimation can be attained. However, it is believed that further improvements of the proposed method must be studied systemically for ball-screw-driven stage, other machining processes with or without MDoF system, and/or local chatter of tool/workpiece/spindle. System Integration to a spindle axis and/or adaptronic intelligent machine components is also interesting. Because the thresholds for phase-shift monitoring with MEF/MPF are determined from the chatter mechanism, it is expected that the chatter can be detected independent of the workpiece materials and cutting conditions. If this can be achieved, the adaptability of chatter monitoring function to SOMS addressing mass customization will be significantly enhanced. It is also thought that the reliability of the system can be improved using MPF/MEF together with the existing chatter detection techniques.

The simple, practical, and optimal design of the SSV process has been an open issue for both industry and academia for a long time. Chapter 4 attempted integrating the SSSV process in the framework of FM technology and constructing a systematic and comprehensive design methodology, which can be online or integrable in CNC machine tools. The proposed method stands on the minimization of the net inflow energy in the CWS during the SSSV cycle. In the process of deriving the design methodology, the technological analogy between the SSSV and PM/FM used in the radio communication engineering is found and focused on. This allows the MI to be defined as a novel design index for SSSV. As a result, the net inflow energy model can be expressed with the Bessel function having MI as an argument. It provides design candidates for selecting the optimal amplitude of SSSV, which will effectively dissipate the chatter energy. Additionally, several limit criteria for SSSV frequency according to the variation amplitude are proposed from the viewpoints of SSSV efficiency and beat vibration. Note that the requirement of the proposed design methodology is to only measure the chatter frequency, similar to DSST; hence, it can contribute to self-acting chatter suppression integrated with a chatter monitoring system. Additionally, it is possible to flexibly take the machine constraints into the design procedure as several recommend design candidates are presented. As a result, the practical design of SSSV is feasible on the actual shop floor; hence, it is important that the proposed design method be applied to many real industrial applications and subjected to more verification for further development. The future SOMS will need to include an effective and flexible chatter avoidance system with autonomous spindle control that achieves the appropriate use and in-situ optimal design of DSST and CSSV according to the observed chatter lobe number, chatter origin, and machining process information.

In Chapter 5, a novel chatter stabilizing machining method employing TSM was proposed in the parallel turning process under the following assumptions: two identical rigid tools machine a flexible workpiece sharing the surface with the same depth of cut. In the TSM process, the two tools are swung in the circumferential direction of the workpiece sinusoidally while maintaining an equal pitch. An appropriate practical design procedure for TSM is also discussed considering the technological analogy with the SSSV process and the side-effects in the TSM process. In a prototype multi-tasking machine tool modified to be flexibly controlled, the chatter stabilization performance and workpiece runout in the TSM process are experimentally evaluated and compared with conventional equal and unequal pitch turning. The results show that the TSM process can perform an effective chatter suppression without the eccentricity of the workpiece, which may be induced by the unbalanced cutting forces, although the swing marks due to the follow-up error of the turret position are observed. The main advantage of the TSM process compared to the SSV process is the bandwidth of the feed drive system, which is independent of the workpiece mass and generally much greater than the spindle drive system; hence, the TSM process can provide a sufficient variation frequency for effective chatter suppression. There is also a possibility that the design range can be further expanded in combination with SSV techniques in the future. As TSM is provided by only the feed drive system and the design parameters can be flexibly adjusted, as in the case of SSV, the proposed TSM has potential to be a practical enabling technology for SOMS addressing the machining chatter issue.

In Chapter 6, the effectiveness of SDM for the parallel end-milling process was discussed. It is assumed that two end mills rotating in opposite directions simultaneously machine a slender workpiece having flexibility on a plane perpendicular to the tool axis direction. In SDM, the spindle speed difference between two tools is just given to suppress the chatter. In addition, the speed difference is designed based on only chatter frequency; hence, SDM is a promising enabling technology for SOMS. Although the concept of SDM has already been proposed for the double-sided face milling of an SDoF thin plate where tools rotate in the same direction [244,245], the effectiveness of SDM has not been elucidated for the scenario mentioned in this dissertation. Therefore, the process model is developed first. Based on an analysis with the developed time- and frequency-domain simulations, the SDM corresponding to ∆𝜀𝑐 = 𝜋 + 2𝜋𝑚𝑝 can improve the process stability, if the mode coupling effect does not exist. However, the SDM may decrease the process stability with mode coupling because of non-diagonal regenerative terms that cannot be erased. In addition, the beat vibration according to the difference in the tooth-pass frequency between two tools is observed in both simulation and experiment when the SDM is applied. As it is clearly observed that the beat vibration is transcribed on the machine surface, the beat vibration should be avoided to the maximum possible extent. Nonetheless, the beat vibration changes sensitively with slight differences from the optimal speed difference value, especially in a high-lobe-number scenario. To address this issue, a real- time adaptive system is a potential solution. By developing an adaptive SDM system with the observer-based chatter-frequency extraction in real time, chatter can be suppressed more robustly with less beat vibration. In this study, however, the spindle speed of one side was fixed during process. Further improvement of the stability may be achieved by adaptively optimizing not only the difference of tooth-pass period between tools but also the reference speed in the future.

None of the proposed systems require additional equipment, such as actuators and sensors; hence, they can be implemented on machine tools as an add-on and contribute the 8th and 9th functions for SOMS (Fig. 1-1). Especially, these functionalities (i.e., control- integrated monitoring and process control) are the fundamental SOMS functions inherently possessed by the machine tool. Furthermore, as these two functions exhibit high affinity, a highly intelligent cooperation between the two is expected. To achieve this expectation, this dissertation is believed to provide valuable enabling techniques and essential information for the process interpretation and control. Note that interpretation of process-machine interaction with a simple model is essential for adaptive process control in SOMS. It is very important to systematically organize the process control strategies involving simple models. Particularly, there are no studies of autonomous process control for complex turn-milling processes. If further process interpretation with a simpler and essential model progresses also in turn-milling process, it is considered that elaborated cooperative process-control strategies between a work spindle and single- or multiple milling spindles, involving DSST, SSV, and/or SDM techniques, will be established.

Not to mention, further research for advanced cooperation and interaction between other functionalities is also important. For instance, robustness and reliability of process and condition monitoring for a harsh and changeable real machining environment would be enhanced by integrating and refurbishing various external and internal sensors through a modeling filter with digital simulations and/or machine learning. The hybrid strategies with simultaneous adaptive control of several process parameters, in addition to an additional adaptronic actuator, would be necessary while considering the process characteristics and predicted surface quality. The feedforward process planning based on the simulated process results, including the machined surface, is also essential for the dual safety system while considering all characteristics of the process, machine, and controller. Furthermore, the research on how to incorporate human know-how into SOMS (i.e., human–machine interaction) is an interesting new direction for SOMS.

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