Abstract: A key factor to enhance industrial competitiveness is to develop strategies around product design, applying the concept of excellence in all its stages and emphasizing innovation efforts. The process of product design as an important element in the differentiation between competing products needs to lean on effective tools that help to meet the demands of customers in the global competitive markets. In response to this need it arises, the European regulatory paradigm on the design of products, standard BS 7000-2: 2008 . It is worth analyzing the influence on the design of manufactured products of the processes of project management of predictive models used mainly. The processes described in each of the models covered along with those reflected in the aforementioned regulations will provide guidance on any differences or similarities in the various phases at project level.
Abstract: In today’s globalized world, knowledge management (KM) has become an essential tool for achieving economic growth, corporate development and competitiveness. Knowledge management must also involve a balance between good practices and productive processes. Therefore, acquisition of knowledge (generation of ideas and opportunities), as well as its implementation in processes, where it can be put into practice, is of great importance. The objective of this paper is to propose action lines to solve the problems inherent in collaborative knowledge management related technological barrier from the perspective of Project Management. Among the results highlights the application of ISO 21500:2012 international standard on good practices in Project Management, which helps establish a framework for Project Managers that helps them manage key aspects such as deadlines, cost and deliverables, achieving stakeholders’ satisfaction, which are related to appropriate management of collaborative networks.
Abstract: This paper presents a tool wear monitoring system that uses the same signals and prediction strategy for monitoring the machining process of different materials, i.e., a steel and an aluminium alloy. It is an important requirement for a monitoring system to be applied in real applications. Experiments have been performed on a lathe over a range of different cutting conditions, and TiN coated tools were used. The monitoring signals used are the AC feed drive motor current and the cutting vibrations. The geometry tool parameters used as inputs are the tool angle and the radius. The performance of the proposed system was validated against different experiments. In particular, different tests were performed using different numbers of experiments obtaining a rmse for tool wear estimation of 17.63 μm and 13.45 μm for steel and aluminium alloys respectively.
Cutting force simulation is a crucial tool for estimating the cutting tool behavior during machining. Due to the flexibility of the cutting process and the different variables involved, optimization in the milling process has become a key issue in order to achieve higher productivity and quality.
To optimize the process planning, it is important to select an adequate machining strategy. A machining strategy provides a cutting mode for the tool during a particular machining operation, determining the axial and radial depth of cut and the recommended trajectories for the cutting tool.
This paper presents an analysis and validation of different strategies for peripheral milling, being this performed under varying cutting conditions. For this purpose, a new cutting force model is used. The cutting force model used in this paper is an average-chip-thickness-based model developed by the authors in a previous publication.
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Abstract: In this work, the energy required during the dry drilling of PEEK GF30, a thermoplastic material, polyether-ether-ketone, reinforced with glass fiber, is analyzed. Three different types of drills are used, respect to material and geometry, under nine cutting conditions based on cutting speed of 6000, 7000 and 8000 rpm, and feed rate of 300, 400 and 500 mm/min. The results show that similar outcomes are obtained with two drills, one of them, wolfram carbide with coating of TiAlN and another of wolfram carbide with point of diamond. This aspect is important due to the economic advantages of the first drill respect to the second one. An analysis of variance, ANOVA, shows that the drill type is the more influent factor, and that the optimal situation can be given with drill of WC and point of diamond with the higher cutting conditions. The energy required, assigned to the torques, is superior to 98%, in each case, question that could be taken in account in the tools design.
Abstract: Currently, Carbon Fiber Reinforced Non-Metal Composites (CFRC) are commonly applied in structural components of aircrafts. Frequently, these elements need to be drilled for their assembly in the final product. Chips close to powder are formed when this kind of material is machined. Because of this, drilling processes are mostly performed in absence of cutting fluids. High quality requirements are demanded for holes due to the fact than those elements are placed in key components of the aircrafts. The most relevant defects that can be produced in the dry drilling of CFRC are located in the both tool input and tool output. These defects are known as Break-IN (B-IN) and Break-OUT (B-OUT). This paper reports on the results of a comparative study of different methodologies for evaluating those defects. First of them is based on the analysis of the diameter deviation. Second procedure is based on the damaged area. Both parameters have been measured making use of image analysis techniques. Obtained results have revealed that damaged area based method is more sensitive to hole changes.
Abstract: On-line monitoring systems eliminate the need for post-process evaluation, reduce production time and costs, and enhance automation of the process. The cutting forces, mechanical vibration and acoustic emission signals obtained using dynamometer, accelerometer, and acoustic emission sensors respectively have been extensively used to monitor several aspects of the cutting processes in automated machining operations. Notwithstanding, determining the optimum selection of on-line signals is crucial to enhancing system optimization requiring a low computational load yet effective prediction of cutting process parameters. This study assess the contribution of three types of signals for the on-line monitoring and diagnosis of the surface finish (Ra) in automated taper turning operations. Systems design were based on predictive models obtained from regression analysis and artificial neural networks, involving numerical parameters that characterize cutting force signals (Fx, Fy, Fz), mechanical vibration (ax, ay, az), and acoustic emission (EARMS).
Abstract: Cutting forces are one of the inherent phenomena and a very significant indicator of the metal cutting process. The work presented in this paper is an investigation of the prediction of these parameters in slotting processes of UNS A92024-T3 (Al-Cu) stacks. So, cutting speed (V) and feed per tooth (fz) based parametric models, for experimental components of cutting force, F(fz,V) have been proposed. These models have been developed from the individual models extracted from the marginal adjustment of the cutting force components to each one of the input variables: F(fz) and F(V).
Abstract: The combination of specific properties, cost, reliability and predictable behavior, guarantee that the aluminium alloys will be kept as one of the materials used in aerospace industry. When aluminium alloys are machined, transfer of cutting material to cutting tool is related with the secondary or indirect adhesion wear mechanism, which can be presented in form of Built-Up Layer (BUL) and Built-Up Edge (BUE), located in two defined zones of the tool, cutting edge and rake face respectively. The material adhered involve tool properties, geometrical and physicochemical alterations which modify the initial cutting conditions, in accordance with currently concept of tool wear. Until now, a generalized lack is observed in methodologies to assessment the secondary adhesion wear in machining of aluminium alloys, mainly due to the difficulty found in characterizing and quantify thereof. In this paper, based in Focus-Variation Microscopy (FVM) techniques, a methodology is proposed through high-resolution optical 3D topography measurements obtained from WC-Co worn tools tested in the dry turning of UNS A92024-T3 alloy, in order to obtained information about effects and intensity of secondary adhesion wear.