Comparative LCA of a Linear Motor and Hybrid Feed Drive under High Cutting Loads

AbstractLinear motor drives (LMDs) are well known to provide significant advantages in terms of positioning speed and accuracy over traditional screw drives (SDs), making them better suited for high-speed high-precision machine tools. However, their use in such machine tools is severely limited by their tendency to consume a lot of electrical energy and cause thermal issues, particularly under high cutting loads. A hybrid feed drive (HFD) has recently been proposed as a possible solution to this dilemma. The HFD switches between LMD and SD actuation depending on the mode of the manufacturing operation, thus achieving speeds and accuracies similar to LMDs while consuming much less energy. This paper presents a comparative life cycle analysis (LCA) of the proposed HFD with an LMD as the baseline for the comparison. The functional unit is taken as the production of parts that involve heavy cutting by a small-sized 3-axis precision milling machine for 250 8-hour work days per year over a 12-year first-use life span. Energy savings provided by the HFD during its use phase vis-a-vis the additional energy investments into the HFD at various phases in its life cycle are compared. The analysis predicts a net positive impact, in terms of energy and the environment, for the HFD compared to the LMD under high cutting loads

Finite element modeling of ballscrew feed drive systems for control purposes

This thesis details a scheme, based on finite element methods, for modeling of the ballscrew drives of Cartesian-configured machine tools. Using this scheme, the structural dynamics of the ballscrew mechanism can be incorporated into the feed drive model, and thereby considered during high-bandwidth controller design, and interactive simulation of feed drive-controller performance in the virtual environment. The finite element method used in this thesis for modeling is a hybrid kind, whereby the more rigid components of the feed drive are modeled as lumped-parameter rigid bodies, while the flexible members, like the ballscrew, are modeled using distributed-parameter structural members. As a result, a feed drive model is developed which both maintains a reasonably low level of complexity while adequately capturing the relevant dynamics needed for controller design and simulation. This scheme also pays close attention to the modeling of the screw-nut interface, because it plays an important role in the functioning of ballscrew drives. Two methods are proposed for deriving the stiffness matrix of this interface - the Rigid Ballscrew Method and the Shape Function Method. The former method is shown to capture interesting dynamics of the interface, while the latter is derived in anticipation of situations where the former may not perform satisfactorily. In order to show the benefits of this modeling scheme, three high-bandwidth controllers are designed. The first controller is designed based on the traditional technique which considers only the rigid-body dynamics of the drive. On the other hand, the second and third controllers are designed considering the rigid-body and structural dynamics information obtained from the proposed modeling scheme. Analyses performed on the three controllers reveal that the two controllers designed based on the proposed scheme outperform that which is designed following the traditional technique. Finally, a simulation strategy is designed which allows the feed drive model, together with its non-linear dynamics to be combined with the controller dynamics and other dynamics of the feed drive system. In order to reduce simulation time, a novel method of performing model reduction based on a Component Mode Synthesis technique combined with Modal Acceleration recovery is described. This method is used to achieve an efficient reduction without compromising relevant dynamic properties of the full model. The potentials of the scheme presented in this thesis are demonstrated partly by experiments conducted on a test bed, and in other cases, by simulations performed on a model generated from the test bed.Applied Science, Faculty ofMechanical Engineering, Department ofGraduat

Modeling and control of high speed machine tool feed drives

Aerospace, die and mold, and automotive industries machine parts at high cutting speeds to reduce production cycle periods. Machine tools which carry out the cutting operations rely on either precision ball screw or linear motor direct drives to accurately position the workpiece relative to the cutting tool. However, the precise positioning capability of the drives is limited by low servo bandwidth and poor disturbance rejection resulting from structural flexibilities in ball screw drives as well as weak dynamic stiffness/robustness in direct drives. This thesis proposes modeling, parameter identification, control and online parameter estimation techniques which aim at increasing the servo bandwidth and disturbance rejection ability of high speed machine tool feed drives. A hybrid finite element methodology is used to model the structural dynamics of ball screw drives. As part of the model, two stiffness matrices are developed for connecting the finite element representation of the ball screw to the lumped-mass representation of the nut. The developed model is used to analyze the coupled axial-torsional-lateral vibration behavior of a critical structural mode that limits high bandwidth control of ball screw drives. Moreover, a method for accurately identifying the mass, damping and stiffness matrices representing the open-loop dynamics of ball screw drives is developed. The identified matrices are used to design gain-scheduled sliding mode controllers, combined with minimum tracking error filters, to effectively suppress the critical axial-torsional-lateral mode of ball screw drives thereby achieving high bandwidth control and good disturbance rejection. For direct-driven machines, a high bandwidth disturbance adaptive sliding mode controller is designed to improve the dynamic stiffness of the drive, compared to similar controller designs, without increasing the controller’s complexity. Furthermore, the cutting forces applied to the drive are estimated accurately using a disturbance recovery algorithm and used to improve the dynamic stiffness of low-frequency structural modes of direct-driven machine tools. Finally, a method for estimating the changing mass of the workpiece during machining operations with cutting forces that are periodic at spindle frequency is introduced. The techniques presented in this thesis are verified through simulations and/or experiments on single-axis ball screw and linear motor feed drives.Applied Science, Faculty ofMechanical Engineering, Department ofGraduat

Intelligent Feedrate Optimization Using an Uncertainty-Aware Digital Twin Within a Model Predictive Control Framework

The future of intelligent manufacturing machines involves autonomous selection of process parameters to maximize productivity while maintaining quality within specified constraints. To effectively optimize process parameters, these machines need to adapt to existing uncertainties in the physical system. This paper proposes a novel framework and methodology for feedrate optimization that is based on a physics-informed data-driven digital twin with quantified uncertainty. The servo dynamics are modeled using a digital twin, which incorporates the known uncertainty in the physics-based models and predicts the distribution of contour error using a data-driven model that learns the unknown uncertainty on-the-fly by sensor measurements. Using the quantified uncertainty, the proposed feedrate optimization maximizes productivity while maintaining quality under desired servo error constraints and stringency (i.e., the tolerance for constraint violation under uncertainty) using a model predictive control framework. Experimental results obtained using a 3-axis desktop CNC machine tool and a desktop 3D printer demonstrate significant cycle time reductions of up to 38% and 17% respectively, while staying close to the error tolerances compared to the existing methods