A great deal of research has been carried out since the late 1950s to solve the chatter problems. Researchers have studied how to detect, identify, avoid, prevent, reduce, control or suppress regenerative chatter. Analysis and suppression of chatter has received great attention during the past two decades.
51 The aim is to suppress chatter instability by reducing the relative displacements between the tool and work piece. Methods can involve active, semi-active or passive control. Active control systems do not require external assistance. They depend essentially upon a source of power to drive „active device‟ which may be electro mechanical, electro hydraulic or electro pneumatic actuators. In contrast, passive vibration control involves modification of the stiffness, mass and damping of vibrating system to make the system less responsive to its vibratory environment. Passive control, compared to active control, exhibit the advantages of easy implementation, low cost and no need for external energy.
There are a number of chatter suppression methods established for turning operation such as those reported by Tarng et al. (2000) and Al Regib et al. (2003) who discovered that selecting suitable spindle speeds certainly eliminated regenerative chatter. Online chatter recognition and cutting speed control principles were introduced by Tlusty (1965). These systems detect the occurrence of chatter via sound or vibration sensor, and then automatically choose a new speed for cutting which is less chatter prone. Changes in system damping are one of the effects of different spindle speeds, which are found by Ganguli et al. (2007). They proposed active damping with velocity feedback as a chatter control strategy.
An alternative, modern way to reduce chatter is by actively detecting and suppressing the unwanted vibration with a control algorithm and an actuator which uses active materials. Active materials are materials that exhibit a coupling between two or more of their physical properties. Piezoelectrics, for example, experience an elastic strain when exposed to an electric field and are excellent candidates for vibration control because they can be driven at high frequencies with high force by electrical signals. Mounting a piezoelectric inertia actuator on the cutting tool as a vibration absorber was another method of chatter suppression recommended by Tarng et al. (2000). Furthermore, an analytical tuning method with vibration absorbers to suppress regenerative chatter was established by Sims (2007). Another method of using a magnetic bearing connected with cutter was suggested by Chen and Knopse (2007) to prevent the onset of chatter. Wang and Fei (1999) proposed a method based on
52 variable stiffness in boring bars to suppress chatter. This is based on the principle of avoidance of self excited vibrations by continuously varying the natural frequency of a structure over a range.
Slavicek (1965) and Vanherck (1967) proposed the use of milling cutters with non-uniform tooth pitch and Stone (1970) used end mills with alternating helix. Effectiveness of these methods in chatter suppression has been verified by simulation and experiments (Doolan et al., 1975, Fu et al., 1984 and Tlusty et al., 1983). These techniques can be applied to the design of a non-uniform pitch cutter for a specific cutting condition, but cannot be applied to single point machining. By the way, Weck et al. (1975) utilised an on-line generated stability lobes to select a spindle speed, and thus maximized the depth-of-cut limit. Later, Smith and Tlusty (1992), Delio et al. (1992) and Tarng et al. (1996) avoided the need for the knowledge of the stability lobes and proposed that the best tooth passing frequency be made equal to the chatter frequency. This minimizes the phase between the inner and outer modulations. This approach is adaptive in the sense that the spindle speed is changed based on feedback measurement of the chatter frequency. This method is practical for high spindle speed machining when the stability lobes are well separated.
Another technique to suppress regenerative chatter is by sinusoidal spindle speed variation (S3V) around the mean speed to disturb the regenerative mechanism. Since this technique was introduced by Stoferle and Grab (1972), there have been many research efforts to verify its effectiveness on machining stability by numerical simulation and experiments in turning (Hoshi et al., 1977, Inamura and Sata, 1974, Sexton and Stone, 1978-1980, Takemura et al., 1974 and Zhang, 1996) and in milling (Altintas and Chan, 1992, Inamura and Sata, 1974, Lee and Liu, 1991). Despite the above research efforts, this technique has not been implemented widely in industry because there is no systematic way to select the proper amplitude and frequency of the sinusoidal forcing signal. The selection of these parameters depends on the dynamics of the machining system and is constrained by the spindle-drive system response and its ability to track the forcing speed signal.
53 In addition, variable speed machining can result in an adverse effect and may even cause chatter in an otherwise stable process (Engelhardt et al., 1989, Lin et al., 1990, Sexton and Stone, 1978 and Soliman and Ismail, 1997). This usually occurs when this method is applied to high speed machining. Recently, Soliman and Ismail (1997) proposed using fuzzy logic to select on-line the amplitude and frequency of the forcing speed signal. Yilmaz et al. (1999) generalized sinusoidal spindle speed variation technique by introducing multi- level random spindle speed variation, where the spindle speed is varied in random fashion within the maximum amplitude ratio allowed by the spindle- drive