SWARM Optimization of Force Model Parameters in Micromilling

Because of the improvement of machine-tool and tool performances in micro cutting field, the interest on these processes is increasing. Therefore, researchers involved in micro manufacturing processes focused their attention on these types of processes with the aim of improving the knowledge on the phenomena occurring during micro cutting operations. The objective of this work is to develop a modelling procedure for forecasting cutting forces in micromilling considering the tool run-out and the cutting tool geometry. The designed modelling procedure combines information coming from a force model, an optimization strategy and some experimental tests. The implemented force model is based on specific cutting pressure and actual instantaneous chip section. The tool run-out and the cutting tool geometry were considered in the analytical model. The adopted optimization strategy was based on the Particles Swarm strategy due to its suitability in solving analytical non-linear models. The experimental tests consisted in realizing micro slots on a sample made of Ti6Al4V. The comparison between experimental and analytical data demonstrates the good ability of the proposed procedure in correctly defining the model parameters

An Innovative Experimental Study of Corner Radius Effect on Cutting Forces

The cutting forces are often modelled using edge discretisation methodology. In finish turning, due to the smaller corner radii, the use of a local cutting force model identified from orthogonal cutting tests poses a significant challenge. In this paper, the local effect of the corner radius on the forces is investigated using a new experimental configuration: corner cutting tests involving the tool nose. The results are compared with inverse identifications based on cylindrical turning tests and elementary cutting tests on tubes. The results obtained from these methods consistently show the significant influence of the corner radius on the cutting forces

Rational Choice of Machining Tools Using Prediction Procedures

Introducing the methods and procedures for predictive analysis into the design process contours of a variety of machining tools (MT) of metal cutting machines is the main aim of this article. A sequence of realization of prediction object (PO) choice as an initial stage of search of perspective designs is offered. Effective in this regard is the "Tree of objectives" apparatus, on the basis of which many ways of improving MT are formed, selecting progressive (reducing the dimension of the problem) at each level of the hierarchy of the constructed graph-tree. The procedure for selecting the prediction method (PM) as a means of generating the forecast data is developed. The task of choosing a method is structured in detail and uses "Information supply"as the main criterion. To this end, assessment scales of choice criteria have been formed, on the basis of which it is possible to evaluate their effectiveness for the PM selection process. The rules forPOcoding are introduced by a three-element information code, including information source classes – static data, expert estimates and patent data. The process of forecasting the MT components by the method of engineering forecasting on the basis of a representative patent fund is realized. The General Definition Table has been built (GDT "Machining tools") and estimates of the prospects of design solutions have been obtained. A fragment of the database of 3D models of promising MT designs in the integrated computer-aided design KOMPAS-3D is proposed

Design and Fabrication of Customized Tracheal Stents by Additive Manufacturing

Abstract Additive Manufacturing (AM) is already becoming part of our life from a technological, economic and social point of view. Nowadays, it is applied in several manufacturing sectors. In particular, AM shows huge opportunities in the medical field and for healthcare applications. Due to its capability to produce complex geometries directly working on medical 3D images and thanks to the possibility to 3D-print biocompatible materials, AM is a key technology for the fabrication both of external and internal medical devices. In particular, the use of AM for medical applications is typically articulated in three steps: 3D-scanning of the patient anatomy, segmentation the medical scan and elaboration through CAD software for the preparation of a STL file suitable for the AM process. One of the main research topic in this field is the definition and optimization of procedures that, taking precise data from an individual patient, could be applied to the design and fabrication of customized components for medical applications. Therefore, this paper presents a project aimed at the fabrication of customized tracheal stents starting from the actual patient anatomy. In particular, it follows an approach based on molds FDM fabrication followed by biocompatible silicone casting. Molds were designed to obtain a tracheal stent based the patient anatomical tracheal lumen and were fabricated using FDM technology. Moreover, since the surface roughness is one of the most critical aspects related to the FDM, the produced molds were finished with a chemical surface post-treatment based on the use of acetone vapours. Overall, the whole developed procedure results in an effective custom-made medical devices realization

Tool run-out measurement in micro milling

The interest in micro manufacturing processes is increasing because of the need for components characterized by small dimensions and micro features. As a result, researchers are studying the limitations and advantages of these processes. This paper deals with tool run-out measurement in micro milling. Among the effects of the scale reduction from macro to micro, tool run-out plays an important role, affecting cutting force, tool life, and the surface integrity of the produced part. The aim of this research is to develop an easy and reliable method to measure tool run-out in micro milling. This measuring strategy, from an Industry 4.0 perspective, can be integrated into an adaptive model for controlling cutting force, with the aim of improving the production quality and the process stability, while at the same time reducing tool wear and machining costs. The proposed procedure deduces tool run-out from the actual tool diameter, the channel width, and the cutting edge’s phase, which is estimated by analyzing the cutting force signal. In order to automate the cutting edge phase measurement, the suitability of two functions approximating the force signal was evaluated. The developed procedure was tested on data from experimental tests. A Ti6Al4V sample was machined using two coated micro end mill flutes made by SECO setting different run-out values. The results showed that the developed procedure can be used for tool run-out estimation

A Coupled Eulerian Lagrangian Model to Predict Fundamental Process Variables and Wear Rate on Ferrite-pearlite Steels

A coupled Eulerian-Lagrangian Finite Element model of the orthogonal cutting process was developed to predict the influence that ferritepearlite steel variants have on fundamental process variables and tool wear. As a case study, this paper is focused on two different ferritepearlite inclusion free alloys, where mainly the influence of ferrite-pearlite ratio was tested. Flow stress behavior based on dynamic compression tests and thermal properties function of temperature were characterized for model input parameters. The numerical model is compared with orthogonal cutting tests where the cutting and feed forces, tool temperature, chip morphology and tool wear related variables were measured. Globally, predicted tendencies match with experiments in forces and temperatures. Widest differences on predictions were found for chip thickness and tool-chip contact length. Predicted wear rates are in accordance to experimentally measured values

An experimental study on micro-milling of a medical grade Co-Cr-Mo alloy produced by selective laser melting

Cobalt-chromium-molybdenum (Co-Cr-Mo) alloys are very promising materials, in particular, in the biomedical field where their unique properties of biocompatibility and wear resistance can be exploited for surgery applications, prostheses, and many other medical devices. While Additive Manufacturing is a key technology in this field, micro-milling can be used for the creation of micro-scale details on the printed parts, not obtainable with Additive Manufacturing techniques. In particular, there is a lack of scientific research in the field of the fundamental material removal mechanisms involving micro-milling of Co-Cr-Mo alloys. Therefore, this paper presents a micro-milling characterization of Co-Cr-Mo samples produced by Additive Manufacturing with the Selective Laser Melting (SLM) technique. In particular, microchannels with different depths were made in order to evaluate the material behavior, including the chip formation mechanism, in micro-milling. In addition, the resulting surface roughness (Ra and Sa) and hardness were analyzed. Finally, the cutting forces were acquired and analyzed in order to ascertain the minimum uncut chip thickness for the material. The results of the characterization studies can be used as a basis for the identification of a machining window for micro-milling of biomedical grade cobalt-chromium-molybdenum (Co-Cr-Mo) alloys

Finite element simulation of high speed micro milling in the presence of tool run-out with experimental validations

Micro milling process of CuZn37 brass is considered important due to applications in tool production for micro moulding and micro replication technology. The variations in material properties, work material adhesion to tool surfaces, burr formation, and tool wear result in loss of productivity. The deformed chip shapes together with localized temperature, plastic strain, and cutting forces during micro milling process can be predicted using finite element (FE) modeling and simulation. However, toolworkpiece engagement suffers from tool run-out affecting process performance in surface generation. This work provides experimental investigations on effects of tool run-out as well as process insight obtained from simulation of chip flow, with and without considering tool run-out. Scanning electron microscope (SEM) observation of the 3D chip shapes demonstrates ductile deformed surfaces together with localized serration behavior. FE simulations are utilized to investigate the effects of micro milling operation, cutting speed, and feed rate on forces, chip flow, and shapes. Predicted cutting forces and chip flow results from simulations are compared with force measurements, tool run-out, and chip morphology revealing reasonable agreements