Milling productivity is still heavily constrained by the onset of chatter. While active control can enlarge chatter free operating windows, practical deployment is limited by actuator force saturation, which degrades performance and may destabilise the controller. This study proposes and validates a saturation aware, spindle speed mapped optimisation of direct velocity feedback (DVF) control that explicitly constrains actuator demand at each spindle speed. A self-adaptive differential evolution algorithm selects the DVF gain per spindle speed by targeting higher stability boundary without actuator saturation and rejecting candidates that exceed available maximum actuation force, thereby aligning controller tuning with realistic hardware limits. The approach is evaluated on a flexible workpiece driven by a proof mass actuator during machining of Al-7075-T6 with a 16 mm diameter, 4 flutes, 45 degrees helical tool at half immersion and 0.05 mm/tooth feed. Stability lobe diagram predictions and cutting tests span between 500 and 3000 rpm, with the resulting controller gains map applied across the range. Results show that saturation aware, spindle speed specific tuning increases the stable axial depth of cut by up to 13 times. Compared with a conventional single gain strategy optimised over a spindle speed range but limited by the most demanding conditions, the proposed method achieves significantly larger productivity improvements. By coupling actuator saturation awareness with spindle speed resolved DVF optimisation, this work provides a practical and generalisable framework for robust active damping of milling chatter on flexible systems, enabling aggressive yet safe expansion of chatter free cutting conditions with experimentally verified benefits.

The machining of near net shapes (NNS) produced by laser powder bed fusion (L-PBF) presents challenges regarding the stiffness of components. Notably, complex geometries featuring thin-walled, slender and hollow regions are of particular interest to additive manufacturing technologies, yet to meet the dimensional and surface quality requirements of functional parts, machining is often deemed necessary. Compliant regions of a workpiece are prone to chatter, and workholding becomes difficult with complex surfaces. Previous works have explored the pure stiffening of flexible workpieces with solid elements such as buttresses and lateral stiffeners. Meanwhile, advances have been made in mesostructural design for a range of metamaterial functions due to the maturation of L-PBF.Building upon these two concepts, the present contribution investigates what damping and stiffening effects a lattice support structure would have on the chatter stability of a flexible workpiece produced by L-PBF. A dynamic model of a cantilever beam supported by a spring and a viscous damper is proposed to predict the vibrational behaviour of a workpiece supported by a lattice support structure. A preliminary modal test is carried out to acquire damping behaviour to inform the model, and provide a deeper understanding of the relationships between lattice parameters and damping.This study is part of an ongoing discussion into the post-processing of NNS parts produced by L-PBF. It presents the concept of additive design for machining, and prompts investigation into how a mesostructural support could be designed to enhance machining operations. As the proposed structure is an addition to the functional part, it should be sacrificial, and to be sacrificial it should be removed effectively and efficiently. The present contribution seeks to provoke a discussion around these emerging concepts.

Active control methods can be used to improve the chatter stability in milling. However, optimisation of the active control method is vital to obtain the best performance from the controller, especially considering actuator force saturation. Otherwise, the saturation effect can destabilise the controller. In the present paper, an optimisation approach is demonstrated, targeting specific spindle speeds considering the actuator force saturation. A self-adaptive differential evolution algorithm is used for the optimisation process. The predicted results are validated experimentally. It is shown that the stable depth of cut can be improved by a factor up to 13.

In this work, the response of a single degree of freedom electromagnetic energy harvester to a white noise base excitation is analysed using the Fokker-Planck-Kolmogorov equation. In this case, a magnetic levitation device with Duffing-type nonlinearities is investigated. It is shown analytically that the introduction of the nonlinearity has the effect of reducing the maximum displacement amplitude of the device centre magnet while having no effect on its expected relative velocity. As a result, it is concluded that the nonlinearity can be used to aid the construction of smaller devices without effecting their power output. The feasibility of applying this idea to real devices is then investigated experimentally. Subsequently, the response of the device when connected to a load resistance is analysed. It is shown that, when under a white noise base excitation, the principle of impedance matching does not always appear to lead to the maximum transfer of energy through the load resistor.

Machining chatter is a common problem in the manufacturing industry that can lead to reduced productivity, poor surface quality, and accelerated tool wear. Various methods have been proposed to suppress chatter, including passive, active, and hybrid techniques. Active control methods, in particular, have gained increasing attention due to their potential for achieving higher suppression effectiveness and adaptability to different machining conditions. However, one of the main challenges of active control is the occurrence of actuator saturation, which happens when the actuator reaches its maximum output and cannot provide any further control action. This can lead to instability and deterioration of suppression performance. Despite its significance, the issue of actuator saturation in machining chatter suppression has not received much attention in the literature. Therefore, this paper aims to fill this gap by providing a detailed investigation of the effects of actuator saturation on the performance of active control methods for chatter suppression. The paper presents a comprehensive review of existing literature on machining chatter suppression methods, with a specific focus on active control techniques and their associated problems, such as saturation. An experimental scenario is presented that illustrates the problem of actuator saturation in the context of robotically assisted milling. The paper then proposes a novel actuator saturation model in the frequency domain that can significantly inform the selection of cutting parameters, potentially enhancing material removal rates and operational productivity. By addressing this research problem, this paper aims to make a significant contribution to the field of machining chatter suppression and stimulate further research in this direction.

Abstract In recent years, there is a growing interest of using and implementing data driven control in structural dynamics. This study considers applying Nonlinear Model Predictive Control (NMPC) to flexible structures by utilising recent developments in models which have been learnt from example data, i.e. machine learning approaches. The Gaussian process (GP) is a Bayesian machine learning algorithm identified for use as a black-box model in NMPC; it provides both the prediction of the system output and the associated confidence. In a control context, a GP can be utilised as a discrepancy model for linear or nonlinear flexible dynamic structures within MPC or even as the nonlinear model of the system itself. The Nonlinear Output Error model (GP-NOE) is a popular GP structure for dynamic systems that is utilised in predictive control strategies and requires predictions to be propagated to the control horizon. This novel framework is evaluated on a cantilever beam with light damping, and the results demonstrate robust control performance in both tracking and regulator tasks. The positive results inspire additional investigation into the proposed technique, particularly in the setting of a fully nonlinear system with unknown dynamics, such as an actuator within the flexible structure.

This paper presents a novel approach to active chatter control in milling operations using a new concept called the virtual inerter-based dynamic vibration absorber (VIDVA). While passive control methods, such as tuned mass damper (TMDs), have their merits, they may not provide optimal performance and adaptability in certain scenarios. Moreover, the realisation of an idealised inerter-based absorber as a localisation addition can be a difficult task to achieve. In response of these challenges, the integration of the inerter concept into virtual passive absorber (VPA) control to improve chatter stability performance is proposed. Four IDVAs are numerically evaluated to enhance the absolute chatter stability limit, and the numerical results are experimentally validated using cutting tests with a proof-mass actuator providing the control force. The study also includes robustness and actuator saturation analysis to provide a comprehensive evaluation of the proposed virtual IDVA. The findings demonstrate that the virtual IDVA offers improved chatter suppression performance, making it a promising solution for active chatter control and application of IDVAs in milling operations.

It is well established that excessive vibrations in machining operations hinder productivity and quality of the components being made. In these environments it is common to encounter self-excited vibrations due to the dynamic response characteristics of the cutting tool and workpiece; referred to as regenerative chatter. To suppress these effects, conventional practices provide the workpiece with as much support as possible and therefore commonly require custom-built fixturing bases and several manual intervention stages. In contrast, for modern reduced fixturing approaches, the workpiece is minimally-held, with the benefits of reduced setup times, lower fixturing and inventory costs, and improved access to the workpiece thereby avoiding multi-stage setups. However, minimal fixturing reduces support of the workpiece, and so vibration becomes a greater challenge, along with the subsequent detrimental effects to part quality and material removal rate (mrr). This paper sets out to determine an optimisation methodology for layout configurations that maximise milling depths of cut whilst achieving dynamic stability; by means of FEA model-based simulations and particle swarm optimisation (pso) methods. The optimisation algorithm is then tested on simplified setups and compared to exhaustive searches. It is shown that optimal results can differ from standard practice, and despite the comparative reduction in workpiece stiffness to a traditional approach is mostly unavoidable, careful placement of workholding elements can reportedly improve cutting conditions and increase dynamic stability within an unsupported environment.

Resource-efficient machining has been at the forefront of sustainable manufacturing for many years. However, the total life of the cutting tool is often not fully exploited to avoid the severe consequences of excessive wear. This conservative strategy increases production time, cost per part, and the carbon footprint of the machining process. The present contribution focuses on resource-efficient machining through physics-informed machine learning, exploiting the benefits of both physics-based and data-driven modelling to accurately predict cutting tool life. The results demonstrate the utility and superiority of this hybrid approach relative to traditional methods and the recent trends towards purely data-driven techniques.

During the design of automotive structures assembled using Self-Piercing Rivets (SPRs), a rivet and die combination is selected for each joint stack. To conduct extensive physical tensile testing on every joint combination to determine the range of strength achieved by each rivet–die combination, a great deal of lab technician time and substrate material are required. It is much simpler and less material-consuming to select the rivet and die solution by examining the cross sections of joints. However, the current methods of measuring cross sections by measuring the amount of mechanical interlock in a linear X–Y direction, achieved with the flared rivet tail, do not give an accurate prediction of joint strength, because they do not measure the full amount of material that must be defeated to pull the rivet tail out of the bottom sheet. The X–Y linear interlock measurement approach also makes it difficult to rapidly rank joint solutions, as it creates two values for each cross section rather than a single value. This study investigates an innovative new measurement method developed by the authors called Volumelock. The approach measures the volume of material that must be defeated to pull out the rivet. Creating a single measurement value for each rivet–die combination makes it much easier to compare different rivet and die solutions; to identify solutions that work well across a number of different stacks; to aid the grouping of stacks on one setter for low-volume line; and to select the strongest solutions for a high-volume line where only one or two different stacks are made by each setter. The joint stack results in this paper indicate that there is a good predictive relationship between the new Volumelock method and peel strength, measured by physical cross-tension testing. In this study, the Volumelock approach predicted the peel strength within a 5% error margin.

Inerter-based-dampers have received substantial interest from the earthquake engineering community in the last two decades. These typically consist of an inerter, a linear spring and a viscous damper arranged into various possible configurations. In this paper, for the first time, experimental results are presented from shake table tests on a scaled three-storey structure with an inerter-based damper included, in order to suppress vibration amplitudes at the resonant frequencies. In particular two types of device are used to demonstrate the differences between using viscous and hysteretic damping in the inerter-based device. The two different types of experimental dampers were manufactured using eddy current dampers and gel damping material. The inerter was manufactured based on a flywheel design. The experimental results were compared with four analytical models tuned to suppress vibrations in the first resonance; namely the tuned-inerter-damper, the tuned-inerter-hysteretic-damper, the tuned-mass-damper-inerter, and the tuned-mass-hysteretic-damper-inerter. These experimental results confirm the observations made from the models that the suppression of higher resonance peaks is significantly different between the viscous and hysteretic damped inerter-based-dampers. Consequently, it is recommended that future studies exploring the performance of inerter-based seismic mitigation systems pay close attention to the damping mechanisms that are prevalent within the structure.

Chatter is one of the major issues that cause undesirable effects limiting machining productivity. Passive control devices, such as tuned mass dampers (TMDs), have been widely employed to increase machining stability by suppressing chatter. More recently, inerter-based devices have been developed for a wide variety of engineering vibration mitigation applications. However, no experimental study for the application of inerters to the machining stability problem has yet been conducted. This article presents an implementation of an inerter-based dynamic vibration absorber (IDVA) to the problem of chatter stability, for the first time. For this, it employs the IDVA with a pivoted-bar inerter developed in the study by Dogan et al. (2022, “Design, Testing and Analysis of a Pivoted-Bar Inerter Device Used as a Vibration Absorber, Mechanical Systems and Signal Processing,” 171, p. 108893) to mitigate the chatter effect under cutting forces in milling. Due to the nature of machining stability, the optimal design parameters for the IDVA are numerically obtained by considering the real part of the frequency response function (FRF), which enables the absolute stability limit in a single degree-of-freedom (SDOF) to be maximized for a milling operation. Chatter performance is experimentally validated through milling trials using the prototype IDVA and a flexible workpiece. The experimental results show that the IDVA provides more than 15% improvement in the absolute stability limit compared to a classical TMD.

Regenerative chatter is a serious problem in machining. It is an unstable relative vibration between the workpiece and the cutting tool that adversely affects virtually all chip formation processes. This paper addresses regenerative chatter in grinding, which is one of the most widely used abrasive processes today. As a result of significant tool wear in grinding, surface regeneration (which is a prerequisite for regenerative chatter) can occur not only on the workpiece but also on the grinding wheel. This article is concerned with the regenerative mechanism by which wheel-related instability develops. In the present study, the role of distributed grit dullness alone is explored. A new chatter model is formulated and validated by both numerical simulations and experimental data. The new theory accurately predicts the existence of stable regimes in grinding, for the first time. This is in contrast to the published literature where the consensus has been that grinding cannot be stable with respect to wheel regeneration. Consequently, the present contribution enables a novel opportunity to increase the productivity of industrial grinding operations. (c) 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

The role of robots has been increasing in machining applications, with new concepts such as robotic-assisted machining where a robot supports the workpiece while it is machined by a machine tool. This method improves chatter stability to a certain extent. However, forced vibrations or unstable vibrations such as chatter can still be a limiting factor for the productivity and quality of the machining process. In this paper, the robotically assisted milling approach is extended to consider an actively controlled robot arm, to suppress the chatter vibrations for milling operation. To assess the feasibility of the method, a proof-mass actuator is assembled on a beam structure that is representative of the robot system. The beam structure is designed to exhibit two degrees of freedom in its structural dynamics, thereby emulating the robots’ dynamic response. The effect of active control is evaluated. Frequency domain results show that the actively controlled robot arm increases the chatter stability and critical limiting depth of cut. A range of active control methods are evaluated, namely direct velocity feedback (DVF), virtual passive absorber (VPA), proportional integrated derivative (PID), linear quadratic regulator (LQR), H infinity (H∞) and μ synthesis control. To validate the simulated frequency response function (FRF) results, several experimental tests are carried out for each control method. Furthermore, a time domain model is used to validate the stability lobe diagrams by detecting the chatter boundaries with/without actuator force saturation. It is shown that the critical limiting depth of cut can be increased by a factor of 2.6, compared to the scenario where the robot has no active control applied.

In this paper a new design for a small scale inerter-based dynamic vibration absorber (IDVA) is presented, based upon a pivoted-bar mechanism. There are several new innovations in this study. The first is to design, build and test an inerter-based device that does not need to be grounded, or placed between different parts of the structure in order to create relative motion. Instead, the relative motion is created between an auxiliary mass and the host structure. Secondly, the pivoted-bar mechanism is designed to act as a pure inerter, and avoids unbalanced inertance effects such as those that occur in the dynamic antiresonant vibration isolator (DAVI). Thirdly, the effects of parasitic mass are minimised by using (i) the appropriate device arrangements, (ii) numerical optimisation, and (iii) fine tuning of the device by adding small additional masses. Fourth, the optimum device damping values are obtained by using a gel damper that can be modelled as a hysteretic damper. In addition, the design uses frictionless flexure hinges that have a small amount of stiffness that can affect the device performance. It is shown how this can also be compensated for using the design optimisation and fine tuning strategies. Detailed design and analysis methodologies are provided, in order to extend the existing work on inerters towards practical design and implementation. In terms of applications, it is anticipated that the design would be suitable for small-size restricted-space applications. A prototype of the design for a small-scale and relatively high frequency application is manufactured. Experimental and numerical results show that the device provides a 18% improvement in performance compared to a classical tuned mass damper (TMD).

The role of inerter-based devices has generated considerable interest in terms of suppressing the vibrations in machines and structures. The inerter is a mechanical device that generates force proportional to the relative acceleration between its terminals. Recently, it has been shown that inerter-based dynamic vibration absorbers (IDVAs, for the mass ratios between 0 and 0.2) can improve the chatter suppression performance compared to a traditional tuned mass damper (TMD) for the same mass ratios. This study proposes an IDVA applied to machining operations as a novel active control method to increase chatter suppression performance. Considering the TMD application as a virtual passive absorber (VPA) method in active control, IDVAs can be potentially employed in the same framework. A proof-mass actuator, which is mounted on a beam that is designed to support a flexible structure, is proposed. Once the IDVA parameters are optimised, a time-domain model is applied to explore the actuator saturation effects. The effect of an IDVA as a novel active control method on chatter stability is then evaluated. The simulated stability lobe diagram shows that the IDVA increases the absolute chatter stability by just above 20%. To validate the simulation results, an experimental setup is designed including a flexible workpiece to be machined and a proof-mass actuator assembled using a beam. In summary, it is shown that inerter-based dynamic vibration absorbers, as an active control method, can successfully be implemented to improve the chatter suppression performance and critical limiting depth of cut.

Nonlinear oscillators with geometric stiffness terms can be used to model a range of structural elements such as cables, beams and plates. In particular, single-degree-of-freedom (SDOF) systems are commonly studied in the literature by means of different approximate analytical methods. In this work, an analytical study of nonlinear oscillators with different combinations of geometric polynomial stiffness nonlinearities is presented. To do this, the method of direct normal forms (DNF) is applied symbolically using Maple software. Closed form (approximate) expressions of the corresponding frequency-amplitude relationships (or backbone curves) are obtained for both. and epsilon(2) expansions, and a general pattern for. truncation is presented in the case of odd nonlinear terms. This is extended to a system of two degrees-of-freedom, where linear and nonlinear cubic and quintic coupling terms exist. Considering the non-resonant case, an example is shown to demonstrate how the single mode backbone curves of the two degree-of-freedom system can be computed in an analogous manner to the approach used for the SDOF analysis. Numerical verifications are also presented using COCO numerical continuation toolbox in Matlab for the SDOF examples.

This paper explores the use of a novel tuned-inerto-viscous-hysteretic-damper (TIVhD) for reducing the seismic response of multi-storey building structures. The TIVhD is an inerter-based damper device consisting of a linear hysteretic damper connected in series with an inerto-viscous damper. The layout of TIVhD is similar to that of tuned-inerter-hysteretic-damper (TIhD) with an additional viscous damping element in parallel with an inerter. The design is motivated by the fact that most inerter designs cannot completely remove the parasitic damping due to friction, fluid compression, etc. Moreover, the use of linear hysteretic damping is considered to be a more realistic approach when material damping is present. In this paper, the TIVhD is installed between the ground and the first-storey and is tuned by firstly assumed the viscous damping coefficient to be zero. Then the other three parameters are optimised following the tuning procedure of the TIhD that is based on the fixed-point theory with additional fine-tuning procedure by targeting the first vibration mode of the multi-storey structure. The optimum TIVhD parameters are finally obtained using two scenarios: (1) amplifying its viscous damping coefficient and stiffness while keeping the inertance constant; (2) amplifying its inertance and stiffness while keeping the viscous damping constant. Both scenarios are aiming at the same reduction level of that given by the TIhD. Finally, the effectiveness of the TIVhD on reducing the structural response is demonstrated for both harmonic and seismic base excitation cases in the time domain. This has been made possible by a newly developed time domain response of linear hysteretic damping via the Hilbert transform and a time reversal technique.

Machining has been at the centre of manufacturing technologies since the start of the industrial revolution, and so it is fitting that this topic receives special attention in a journal that can trace its origins back to 1847. The first publication of the Proceedings of the Institution of Mechanical Engineers describes a healthy debate concerning the machining of gear teeth, alongside an obituary to George Stephenson himself – the ‘father of railways’ and the founding president of the Institution of Mechanical Engineers. The next 60 years saw a steady growth in scientific and technical dissemination of knowledge concerning machining, which is epitomised by Taylor’s famous monograph of 1907. Over 100 years later, we have of course seen huge leaps in our understanding of all manufacturing processes. But the strive for increased productivity and quality is now also matched by a need for resource efficiency in light of societal challenges such as climate change and pollution. The contributions included in this special issue seek to demonstrate how machining science research is playing a role in addressing this challenge: a rethinking of manufacturing is underway as a consequence of machining learning, ubiquitous data, and networked computing and machining science is a key part of this shifting manufacturing landscape. The topics that are covered are intentionally diverse: they illustrate a vibrant and creative scientific approach across the spectrum of material removal processes, and show emergent approaches that can harness flexible manufacturing processes, as well as data-driven and intelligent automation. The special issue begins with a focus on novel techniques for monitoring the performance of machine tools and their cutting operations. Here, there have been great developments in machine learning techniques that can be brought to bear on production processes. To pick just two examples from the manuscripts: McLeay et al. develop fault detection techniques based upon unsupervised learning methods, and Moore et al. also demonstrate how machine learning concepts can be applied to machine health monitoring. The deployment of these novel monitoring techniques necessitates effective measurement capabilities, and on novel manufacturing problems this can itself be a challenge. Alhadeff et al. explore wear measurements in micro milling, whilst Duboust et al. characterise surface roughness in machining of composites. The machining of new materials, and workpieces produced using novel additive manufacturing techniques, also presents challenges. Several manuscripts within this special issue address these problems, focussing for example on Inconel (Curtis et al.), Titanium (Khan et al.) and metal-matrix composites (Saberi et al.). Finally, the development of state-of-the art modelling techniques can help to improve the performance of machining processes, focussing for example on dynamic effects (Urena et al.) and Robotics (Rooker et al.). At The University of Sheffield, we have been fortunate to be able to explore these avenues of research within the remit of an EPSRC Centre for Doctoral Training in Machining Science (Grant Reference EP/ L016257/1). This special issue was borne from discussions with the journal’s editorial board, in particular Professors Maropoulos and Long, as a consequence of the doctoral training centre. Consequently, much of the work included in this special issue has been inspired by the work within the doctoral training centre. The guest editors, who are co-directors of the centre, are grateful for the support of the journal’s editorial office who have ensured an independent peer review process for these manuscripts. We also express our thanks to Dr Francesca Breeden for her assistance in coordinating the special issue.

Self-pierce riveting (SPR) is a complex joining process where multiple layers of material are joined by creating a mechanical interlock via the simultaneous deformation of the inserted rivet and surrounding material. Due to the large number of variables which influence the resulting joint, finding the optimum process parameters has traditionally posed a challenge in the design of the process. Furthermore, there is a gap in knowledge regarding how changes made to the system may affect the produced joint. In this paper, a new system-level model of an inertia-based SPR system is proposed, consisting of a physics-based model of the riveting machine and an empirically-derived model of the joint. Model predictions are validated against extensive experimental data for multiple sets of input conditions, defined by the setting velocity, motor current limit and support frame type. The dynamics of the system and resulting head height of the joint are predicted to a high level of accuracy. Via a model-based case study, changes to the system are identified, which enable either the cycle time or energy consumption to be substantially reduced without compromising the overall quality of the produced joint. The predictive capabilities of the model may be leveraged to reduce the costs involved in the design and validation of SPR systems and processes.