This paper proposes a system for the automatic programming of a CNC milling machine by particle swarm optimization (PSO). In the presented research, each individual swarm particle presents a possible NC programme. Voxel representation of machining area was used. Bresenham's algorithm was implemented, for the rasterisation of the cuts. Optimisation with PSO was carried out within avoxelised machining area. The system automatically finds the NC programme for optimal machining. The NC programme guarantees an optimal selection of tools, the shortest possible work and rapid motions, and minimisation of the manufacturing time. Thus,achieving a reduction in machining costs and increased productivity. Testing using test work-pieces and 2.5 D milling confirmed the efficiency of the proposed approach. The proposed intelligent system is easily adaptable for programming other types of CNC machines, by PSO.
COBISS.SI-ID: 16252694
This paper proposes the modelling of a turning process using a gravitational search algorithm (GSA). GSA is an optimization algorithm based on Newton's law of universal gravitation and mass interactions. In order to sufficiently describe the turning process, at least three independent variables are required: cutting speed, feed-rate, and cutting depth. Independent variables have impacts on dependent variables, which were in our case cutting force, surface roughness, and tool-life. The values of independent and dependent variables obtained by measurements serve as a knowledge database for feeding the GSA optimization process. During our research the GSA was used for optimizing the numerical coefficients of predefined polynomial models for describing the observed output variables. The accuracies of the obtained prediction models were proved by means of a testing data set that was excluded from the training data. The research showed that the obtained results were comparable with the other optimization algorithms such as particle swarm optimization (PSO). However, the optimization time required for GSA optimization was, in certain cases, significantly shorter.
COBISS.SI-ID: 17680662
The contribution discusses the use of combining the methods of neural networks, fuzzy logic and PSO evolutionary strategy in modeling and adaptively controlling the process of ball-end milling. On the basis of the hybrid process modeling, off-line optimization and feed-forward neural control scheme (UNKS) the combined system for off-line optimization and adaptive adjustment of cutting parameters is built. This is an adaptive control system controlling the cutting force and maintaining constant roughness of the surface being milled by digital adaptation of cutting parameters. In this way it compensates all disturbances during the cutting process: tool wear, non-homogeneity of the workpiece material, vibrations, chatter, etc. The basic control principle is based on the control scheme (UNKS) consisting of two neural identifiers of the process dynamics and primary regulator. An overall procedure of hybrid modeling of cutting process used for creating the CNC milling simulator has been prepared. The experimental results show that not only does the milling system with the design controller have high robustness, and global stability, but also the machining efficiency of the milling system with the adaptive controller is 27% higher than for traditional CNC milling system.
COBISS.SI-ID: 14723350
Predstavljen je izjemni znanstveni dosežek programske skupine v letu 2012. Za izjemni znanstveni dosežek je izbran razvoj mehatronskega sistema posrednega optimiranja in adaptivnega vodenja visokohitrostnega frezanja. Rešitev problema izdelave transfernih orodij v orodjarnah je v uporabi inteligentnega sistema za korekcijo rezalnih parametrov.
COBISS.SI-ID: 17247766
The most important purpose of this book is to incorporate diverse tools and principles within the development stages of functional products. The book was prepared with the aim of providing researchers from different fields with the basic principles and essential knowledge related to protection under lifethreatening conditions by means of textile and clothing engineering and production technologies. Another purpose of this book is to stress the importance of attaining knowledge from different research areas or work fields. For example, the optimal protective clothing ensemble is an important factor for protection and for survival, both in terms of the time required for a successful outcome. Instead of testing each clothing ensemble on human subjects under various conditions, it is preferable to use a thermal manikin for testing and to carry out the simulations using existing numerical models. On the other hand, researchers are always challenged by the developments of appropriate testing and modelling tools. As a basis, we hope that readers will be encouraged enough to evaluate, develop, and where necessary critique the functional products, no matter whether they were made according to the prescribed standards or not. When considering this, it is obvious that knowledge of this interdisciplinary field will increase, will stay connected, and only such a connection can result in the best functional products.
COBISS.SI-ID: 75503873