Coolant channels allow internal coolant delivery to the cutting region and significantly improve drilling, but these channels also reduce the torsional and torsional-axial stiffness of the drills. Such a reduction in stiffness can degrade the quality of the drilled holes. The evacuation of cutting chips and the delivery of the cutting fluid put strict geometrical restrictions on the cross-section design of the drill. This necessitates careful selection and optimization of features such as the geometry of the coolant channels. This paper presents a new method that uses Prandtl's stress function to predict the torsional and torsional-axial stiffness values. Using this method drills with one central channel are compared to those with two eccentric coolant channels, which shows that with the same cross-section area, the reduction of axial and torsional-axial stiffness is notably smaller for the design with two eccentric channels compared to a single central channel. The stress function method is further used to select the appropriate location of the eccentric coolant channels to minimize the loss of torsional and torsional-axial stiffness. These results are verified by comparison to the results of three-dimensional finite element analyses.

The advantages and importance of university-industry collaboration, particularly in curriculum design and delivery, are well-known. However, although curriculum development models are available in the literature, very few are sufficiently concrete to be applicable in practice or are generalizable beyond their discipline of origin. In this paper, a co-operative model based on the Plan-Do-Study-Act cycle is presented and described. An example of its application in the curriculum design of two courses in welding within a Manufacturing Engineering Master's program is detailed. The model was found successful based on the evaluation of the courses by students, teachers, and the industrial representatives involved. Therefore, it proved to be an effective tool for bridging the gap between industrial needs and academia in the field of Manufacturing Engineering education. At the same time, the methodology is generalizable and is applicable to any field of education.

Machining process modeling has been an active endeavor for more than a century and it has been reported to be able to predict industrially relevant process outcomes. Recent advances in the fundamental understanding of material behavior and material modeling aids in improving the sustainability of industrial machining process. In this work, the flow stress behavior of C45E steel is modeled by modifying the well-known Johnson-Cook model that incorporates the dynamic strain aging (DSA) influence. The modification is based on the Voyiadjis-Abed-Rusinek (VAR) material model approach. The modified JC model provides the possibility for the first time to include DSA influence in chip formation simulations. The transition from continuous to segmented chip for varying rake angle and feed at constant cutting velocity is predicted while using the ductile damage modeling approach with two different fracture initiation strain models (Autenrieth fracture initiation strain model and Karp fracture initiation strain model). The result shows that chip segmentation intensity and frequency is sensitive to fracture initiation strain models. The Autenrieth fracture initiation strain model can predict the transition from continuous to segmented chip qualitatively. The study shows the transition from continuous chip to segmented chip for varying feed rates and rake angles for the first time. The study highlights the need for material testing at strain, strain rate, and temperature prevalent in the machining process for the development of flow stress and fracture models.

Surface roughness is an important aspect of a machined piece and greatly influences its performance. This paper presents the surface roughness of end-milled aluminium plates in stable and unstable machining conditions at various spindle speed and depth of cuts machined with cylindrical end-mills. The surface roughness is measured using high-resolution surface replicas with a white light interferometry (WLI) microscope. The measurements of the end-milled floors show that the surface roughness as long as the cutting is performed in stable conditions is insensitive to the depth of cut or spindle speed. In contrast, within chattering conditions, which appear according to stability lobes, surface roughness values increase almost 100%. While at the valleys of the stability lobe diagram, there is a gradual increase in roughness, at the peaks of the stability lobe, the transition from the stable to unstable condition occurs with a sudden increase of the roughness values. In the study of down-milled walls, while the roughness increases with the depth of cut within both the stable and the chattering regions, the transition from the stable to chattering condition can lead to a much larger increase in the surface roughness. These results could be used for strategic selection of operation considering the needs of robustness and possible variation of dynamic parameters that can affect the position of the cutting conditions within the stability lobe diagrams.

In this study, the flow stress behavior of ferritic-pearlitic steel (C45E steel) is investigated through isothermal compression testing at different strain rates (1 s-1, 5 s-1, and 60 s-1) and temperatures ranging from 200 to 700 °C. The stress-strain curves obtained from experimental testing were post-processed to obtain true stress-true plastic strain curves. To fit the experimental data to well-known material models, Johnson-Cook (J-C) model was investigated and found to have a poor fit. Analysis of the flow stress as a function of temperature and strain rate showed that among other deformation mechanisms dynamic strain aging mechanism was active between the temperature range 200 and 400 °C for varying strain rates and J-C model is unable to capture this phenomenon. This lead to the need to modify the J-C model for the material under investigation. Therefore, the original J-C model parameters A, B and n are modified using the polynomial equation to capture its dependence on temperature and strain rate. The results show the ability of the modified J-C model to describe the flow behavior satisfactorily while dynamic strain aging was operative. © 2019 by the authors. Licensee MDPI, Basel, Switzerland.

Understanding the influence of the cutting edge geometry on the development of cutting forces during the milling process is of high importance in order to predict the mechanical loads on the cutting edge as well as the dynamic behavior on the milling tool. The work conducted in this study involves the force development over the entire engagement of a flute in milling, from peak force during the entry phase until the exit phase. The results show a significant difference in the behavior of the cutting process for a highly positive versus a highly negative cutting edge geometry. The negative edge geometry gives rise to larger force magnitudes and very similar developments of the tangential and radial cutting force. The positive cutting edge geometry produces considerably different developments of the tangential and radial cutting force. In case of positive cutting edge geometry, the radial cutting force increases while the uncut chip thickness decreases directly after the entry phase; reaching the peak value after a certain delay. The radial force fluctuation is significantly higher for the positive cutting edge geometry. The understanding of such behavior is important for modelling of the milling process, the design of the cutting edge and the interactive design of digital applications for the selection of the cutting parameters.

The ability to minimize vibrations in milling by the selection of cutting edge geometry and appropriate cutting conditions is an important asset in the optimization of the cutting process. This paper presents a measurement method and a signal processing technique to characterize and quantify the magnitude of the vibrations in an end milling application. Developed methods are then used to investigate the effects of various cutting edge geometries on vibrations in end milling. The experiments are carried out with five cutting edge geometries that are frequently used in machining industry for a wide range of milling applications. The results show that a modest protection chamfer combined with a relatively high rake angle has, for the most of cutting conditions, a reducing effect on vibration magnitudes. Furthermore, dynamics of a highly positive versus a highly negative cutting geometry is explored in time domain and its dependency on cutting conditions is presented. The results give concrete indications about the most optimal cutting edge geometry and cutting conditions in terms of dynamic behavior of the tool.

Machining parameters needed for stable, high-performance high-speed machining could be found using mathematical models that need accurate measurements of modal parameters of the machining system. In-process modal parameters, however, can slightly differ from those measured offline and this can limit the applicability of simple measurement methods such as impact hammer tests. To study and extract the in-process modal parameters, mathematical models are used to define two key dimensionless parameters and establish their relationships with each other and the modal parameters. Based on these relationships, the modal parameters are extracted using two analytical methods, the two-point method (TPM), and the regression method (RM). As shown with experimental studies, the RM extracts the modal parameters successfully and while being much faster than the existing iteration-based methods, it provides stability lobe predictions that match well the experimental results. Furthermore, it is noted that the natural frequency parameter is estimated with much better relative precision compared to the damping ratio and the modal stiffness parameters. © 2019 Elsevier Ltd

Cutting tool geometry design has traditionally relied on experimental studies; while engineering simulations, to the level of industrial deployment, have been developed only in the last couple of decades. With the development of simulation capability across length scales from micro to macro,cutting tool geometry development includes engineering data development for its efficient utilization. This calls for the design of a simulation-based approach in the design of cutting tool geometry so that the engineering data can be generated for different machining applications (e.g.digital twin). In this study, the needs for engineering model development of different stages of cutting tool design evaluation is assessed. To this end, some of the previously developed engineering models have been evaluated for evaluation of chip form morphology in industrially relevant nose turning process, work piece material behavior modeling and damage modeling for the prediction of chip shape morphology. The study shows the possibility for the developed models to act as building blocks of a digital twin. It also shows the need for engineering model development for different aspects of cutting tool design, its advantages, limitations, and prospects.

Chatter vibrations encountered in machining can degrade surface finish and damage the machining hardware. Since chatter originates from unstable interaction of the machining process and the machining structure, information about vibration parameters of the machining structure should be used to predict combinations of cutting parameters that allow stable machining. While modal test methods, for example those with impact hammers, are widely used to identify structural parameters; the need for sophisticated test equipment is prohibitive in their use. Furthermore, dynamic properties of critical components of a machine tool may change as they get affected by cutting loads, material removal and spindle rotation. Recently few algorithms have been proposed that identify the in-process dynamic parameters by frequency measurements, thus avoiding these problems. In this paper, some of these algorithms are reviewed and their capabilities and limitations in processing am experimental data set are compared and discussed. © 2018 The Authors. Published by Elsevier Ltd.