1. Toward optimal robot machining considering the workpiece surface geometry in a task-oriented approachAleš Hace, 2024, izvirni znanstveni članek Opis: Robot workpiece machining is interesting in industry as it offers some advantages, such as higher flexibility in comparison with the conventional approach based on CNC technology. However, in recent years, we have been facing a strong progressive shift to custom-based manufacturing and low-volume/high-mix production, which require a novel approach to automation via the employment of collaborative robotics. However, collaborative robots feature only limited motion capability to provide safety in cooperation with human workers. Thus, it is highly necessary to perform more detailed robot task planning to ensure its feasibility and optimal performance. In this paper, we deal with the problem of studying kinematic robot performance in the case of such manufacturing tasks, where the robot tool is constrained to follow the machining path embedded on the workpiece surface at a prescribed orientation. The presented approach is based on the well-known concept of manipulability, although the latter suffers from physical inconsistency due to mixing different units of linear and angular velocity in a general 6 DOF task case. Therefore, we introduce the workpiece surface constraint in the robot kinematic analysis, which enables an evaluation of its available velocity capability in a reduced dimension space. Such constrained robot kinematics transform the robot’s task space to a two-dimensional surface tangent plane, and the manipulability analysis may be limited to the space of linear velocity only. Thus, the problem of physical inconsistency is avoided effectively. We show the theoretical derivation of the proposed method, which was verified by numerical experiments.periments. Ključne besede: robotics, automation, robot machining, workpiece surface polishing, collaborative robot, manipulability, complex surface geometry, motion planning Objavljeno v DKUM: 25.11.2024; Ogledov: 0; Prenosov: 0 |
2. Region-based approach for machining time improvement in robot surface finishingTomaž Pušnik, Aleš Hace, 2024, izvirni znanstveni članek Opis: Traditionally, in robotic surface finishing, the entire workpiece is processed at a uniform speed, predetermined by the operator, which does not account for variations in the machinability across different regions of the workpiece. This conventional approach often leads to inefficiencies, especially given the diverse geometrical characteristics of workpieces that could potentially allow for different machining speeds. Our study introduces a region-based approach, which improves surface finishing machining time by allowing variable speeds and directions tailored to each region’s specific characteristics. This method leverages a task-oriented strategy integrating robot kinematics and workpiece surface geometry, subdivided by the clustering algorithm. Subsequently, methods for optimization algorithms were developed to calculate each region’s optimal machining speeds and directions. The efficacy of this approach was validated through numerical results on two distinct workpieces, demonstrating significant improvements in machining times. The region-based approach yielded up to a 37% reduction in machining time compared to traditional single-direction machining. Further enhancements were achieved by optimizing the workpiece positioning, which, in our case, added up to an additional 16% improvement from the initial position. Validation processes were conducted to ensure the collaborative robot’s joint velocities remained within safe operational limits while executing the region-based surface finishing strategy. Ključne besede: robot surface finishing, collaborative robot, region-based machining, workpiece optimization, clustering, task-oriented machining, machining time optimization Objavljeno v DKUM: 25.11.2024; Ogledov: 0; Prenosov: 11
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3. Workpiece placement optimization for robot machining based on the evaluation of feasible kinematic directional capabilitiesSaša Stradovnik, Aleš Hace, 2024, izvirni znanstveni članek Opis: Workpiece placement plays a crucial role when performing complex surface machining task robotically. If the feasibility of a robotic task needs to be guaranteed, the maximum available capabilities should be higher than the joint capabilities required for task execution. This can be challenging, especially when performing a complex surface machining task with a collaborative robot, which tend to have lower motion capabilities than conventional industrial robots. Therefore, the kinematic and dynamic capabilities within the robot workspace should be evaluated prior to task execution and optimized considering specific task requirements. In order to estimate maximum directional kinematic capabilities considering the requirements of the surface machining task in a physically consistent and accurate way, the Decomposed Twist Feasibility (DTF) method will be used in this paper. Estimation of the total kinematic performance capabilities can be determined accurately and simply using this method, adjusted specifically for robotic surface machining purposes. In this study, we present the numerical results that prove the effectiveness of the DTF method in identifying the optimal placement of predetermined machining tasks within the robot’s workspace that requires lowest possible joint velocities for task execution. These findings highlight the practicality of the DTF method in enhancing the feasibility of complex robotic surface machining operations. Ključne besede: workpiece placement optimization, robotic surface machining, feasible kinematic directional capabilities, decomposed twist feasibility (DTF) method, manipulability, non-linear optimization Objavljeno v DKUM: 12.08.2024; Ogledov: 64; Prenosov: 22
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4. Empirical modeling of liquefied nitrogen cooling impact during machining Inconel 718Matija Hriberšek, Lucijano Berus, Franci Pušavec, Simon Klančnik, 2020, izvirni znanstveni članek Opis: This paper explains liquefied nitrogen’s cooling ability on a nickel super alloy called Inconel 718. A set of experiments was performed where the Inconel 718 plate was cooled by a moving liquefied nitrogen nozzle with changing the input parameters. Based on the experimental data, the empirical model was designed by an adaptive neuro-fuzzy inference system (ANFIS) and optimized with the particle swarm optimization algorithm (PSO), with the aim to predict the cooling rate (temperature) of the used media. The research has shown that the velocity of the nozzle has a significant impact on its cooling ability, among other factors such as depth and distance. Conducted experimental results were used as a learning set for the ANFIS model’s construction and validated via k-fold cross-validation. Optimization of the ANFIS’s external input parameters was also performed with the particle swarm optimization algorithm. The best results achieved by the optimized ANFIS structure had test root mean squared error (test RMSE) = 0.2620, and test R$^2$ = 0.8585, proving the high modeling ability of the proposed method. The completed research contributes to knowledge of the field of defining liquefied nitrogen’s cooling ability, which has an impact on the surface characteristics of the machined parts. Ključne besede: cryogenic machining, cooling impact, Inconel 718, machine learning, adaptive neuro-fuzzy inference system, particle swarm optimization Objavljeno v DKUM: 14.07.2023; Ogledov: 564; Prenosov: 39
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5. Comparative model analysis of two types of clamping elements in dynamic conditionsPetar Todorovic, Borut Buchmeister, Marko Djapan, Djordje Vukelić, Marko Milosevic, Branko Tadic, Milan Radenkovic, 2014, izvirni znanstveni članek Opis: This paper studies the compliance of the fixture-workpiece system. Workpiece clamping case with two types of clamping elements is considered. The first type of clamping element is standard, with flat top, while the second one is specially designed, with round cutting insert. Analyzed was the case of workpiece clamping using small forces, whereby the deformations in the workpiece/clamping element interface are predominantly on the order of magnitude of roughness height. A comparative analysis of dynamic behaviour of both types of clamping elements is also presented. In comparison with its standard counterpart, the specially designed clamping element with round cutting insert has superior clamping performance regarding both tangential load capacity and compliance. Ključne besede: clamping, clamping element design, product development, machining, cutting, compliance, fixture, roughness, analysis, dinamical behaviour Objavljeno v DKUM: 11.07.2017; Ogledov: 1193; Prenosov: 111
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6. Določevanje značilnih tehnoloških in gospodarskih parametrov med postopkom odrezovanjaUroš Župerl, Franc Čuš, 2004, izvirni znanstveni članek Opis: V prispevku je predlagan nov ne-deterministični optimizacijski postopek za kompleksno optimizacijo rezalnih parametrov pri odrezavanju. Ta postopek uporablja umetne nevronske mreže (ANN) za reševanje problema optimiranja rezalnih pogojev. Predlagan pristop temelji na kriteriju maksimalne stopnje proizvodnje in vključuje štiri tehnološke omejitve. Z izbiro optimalnih rezalnih parametrov je možno doseči ugodno razmerje med nizkimi obdelovalnimi stroški in visoko produktivnostjo ob upoštevanju podanih omejitev procesa rezanja. Eksperimentalni rezultati kažejo, da je predlagani algoritem pri reševanju nelinearnih optimizacijskih problemov s postavljenimi omejitvami učinkovit in ga je možno vključiti v inteligentne obdelovalne sisteme. Najprej je formuliran problem določitve optimalnih parametrov odrezavanja, kot več-ciljni optimizacijski problem. Nato so predlagane nevronske mreže za predstavitev proizvajalčevih prioritetnih struktur. Za demonstracijo zmogljivosti predlaganega pristopa je detajlno obravnavan nazoren primer. Ključne besede: odrezovanje, pogoji rezanja, struženje, optimiranje, nedeterministični postopki, machining, cutting parameters, turning, nondeterministic optimization Objavljeno v DKUM: 10.07.2015; Ogledov: 1226; Prenosov: 53
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7. Databases for technological information systemsFranc Čuš, Bogomir Muršec, 2004, izvirni znanstveni članek Opis: Organization of tool management for mixed production includes today, in particular, the computer-supported management and organization of the flow of tools and data on them. The system supports the entire flow of tools in a production process including the tool store management, commissioning, mounting, dismantling and pre-setting of tools. The system contains the management of the tool database with all vital data on tools and ensures adaption of production requirements for meeting the needs for tools. The integral model for the selection of optimal cutting conditions in the computer aided tool management system (TOMS) is proposed. The integration of technological databases and tool management systems is urgently necessary. The target function for the OPTIS programme, worked out by the programme package Microsoft Visual Basic, is selection of optimal cutting conditions from commercial databases with respect to the lowest costs of machining by taking into account the technological limitations of the metal removal process. The newly developed OPTIS programme selects optimal cutting conditions with respect to the tool maker, workpiece material, type of machining, cutting machine, smallest and greatest cutting conditions, tool, data on series, type of clamping and workpiece geometry. Ključne besede: machining processes, tool system, manufacturing systems, technological information systems, databases, tool management, machining systems, cutting conditions Objavljeno v DKUM: 01.06.2012; Ogledov: 4096; Prenosov: 99
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8. Neural-network-based numerical control for milling machineJože Balič, 2004, izvirni znanstveni članek Opis: We describe a device which uses a neural network to generate part-programs for milling, drilling and similar operations on machining centres, on the basis of 2D, 2.5D or 3D geometric models of prismatic parts, without operator intervention. The neural network consists of networks for prediction of milling strategy, for prediction of surface quality and for the optimisation of technological parameters in milling. We introduce the surface complexity index (SCI) for identifying surfaces which are very difficult to machine. The SCI takes the surface roughness and machining strategy into account. Teaching and testing of the NN is described. The device, which can be retrofitted to a CNC controller, can be trained from a set of typical parts and will then generate new NC part-programs. A case study of a tool used in the automotive supplier industry shows how a milling strategy is proposed, according to set constraints. Ključne besede: intelligent CNC control, retrofit CNC, intelligent CAD/CAM, neural networks, machining centres Objavljeno v DKUM: 01.06.2012; Ogledov: 1617; Prenosov: 94
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9. Neural network based manufacturability evaluation of free form machiningMarjan Korošec, Jože Balič, Janez Kopač, 2005, izvirni znanstveni članek Opis: Most CAD/CAM and computer-aided process planning systems manipulate all geometrical features on the part equally. In the area of free form machining, lack of efficient methodology for assessing the degree of manufacturing pretentiousness of free form features is still noticeable. Developing this methodology inside CAD/CAM systems brings the following benefits to the tool shop praxis: it minimizes the number of set-ups and tool changes and at the same time ensures the right sequence of machining strategies in order to achieve the best possible surface quality in the machining area. Based on this assessment, the CAD/CAM process will also be greatly simplified. When there are an increased number of non-prismatic and non-cylindrical features, this problem is even more exaggerated, and its solution cannot be found in the framework of analytical mathematics. This paper reports a neuro-fuzzy model that uses the concept of "feature manufacturability" to identify and recognize the degree of "pretentiousness-difficulty of machining". The model is created by means of the construction of parametric fuzzy membership functions, based on neural networks learning process. This makes possible simultaneous evaluation of features complexity in a CAD model and manufacturing capability in an environment description model. Ključne besede: index of machining complexity Objavljeno v DKUM: 01.06.2012; Ogledov: 1574; Prenosov: 100
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