| | SLO | ENG | Piškotki in zasebnost

Večja pisava | Manjša pisava

Iskanje po katalogu digitalne knjižnice Pomoč

Iskalni niz: išči po
išči po
išči po
išči po
* po starem in bolonjskem študiju

Opcije:
  Ponastavi


1 - 10 / 17
Na začetekNa prejšnjo stran12Na naslednjo stranNa konec
1.
ORGANIZACIJA IN NAČRTOVANJE NABAVE EMBALAŽNIH MATERIALOV V KRKI D.D.
Polona Sladič, 2009, diplomsko delo

Opis: V svoji nalogi so opredeljene teoretične osnove nabavnega poslovanja in so primerjane s praktičnim primerom nabavnega poslovanja v podjetju Krka, d.d., Novo mesto (v nadaljevanju Krka). Na začetku je predstavljeno podjetje Krka, njen začetek in razvoj, njene dejavnosti in poslovanje v letu 2008. Nato je poudarek na samem nabavnem poslovanju v farmacevtski industriji. Na konkretni organiziranosti Službe nabave je preučena skladnost teorije s prakso, ki se izvaja v nabavi za proizvodnjo, ki ga opravlja Služba nabave. Preverjeno je kako se izvaja sam proces nabave, kako poteka načrtovanje nabave v teoriji in v podjetju Krka. V sklepnem delu naloge je predstavljen in analiziran problem operativnega načrtovanja nabave. Delo nabave je tesno povezano s prodajo in logističnim centrom. Opisano je na kakšen način je Krka prišla do bistvenega izboljšanja in zmanjšanja stroškov odpisa nepotrebne embalaže z nadgradnjo že vpeljanega sistema SAP. SAP je bil nadgrajen z APO-m in dosežena je večja optimizacija proizvodnih kapacitet. Vpeljano je tudi tako imenovano »zamrznjeno« obdobje planiranja, kar pripomore k večji točnosti planiranja in daje nabavi možnost boljšega operativnega načrtovanja.
Ključne besede: - nabava - planiranje nabave - MRP (Material Requirement Planning) sistem - informacijski sistem SAP (Systems, Applications and Products) - informacijski sistem APO (Advanced Planning and Optimisation
Objavljeno: 20.07.2009; Ogledov: 3388; Prenosov: 716
.pdf Celotno besedilo (3,03 MB)

2.
Adaptive self-learning controller design for feedrate maximization of machining process
Franc Čuš, Uroš Župerl, 2007, izvirni znanstveni članek

Opis: An adaptive control system is built which controlling the cutting force and maintaining constant roughness of the surface being milled by digital adaptation of cutting parameters. The paper discusses the use of combining the methods of neural networks, fuzzy logic and PSO evolutionary strategy (Particle Swarm Optimization) in modeling and adaptively controlling the process of end milling. An overall approach of hybrid modeling of cutting process (ANfis-system), used for working out the CNC milling simulator has been prepared. The basic control design is based on the control scheme (UNKS) consisting of two neural identificators of the process dynamics and primary regulator. Experiments have confirmed efficiency of the adaptive control system, which is reflected in improved surface quality and decreased tool wear.
Ključne besede: end milling, adaptive force control, artificial intelligence, optimisation, adaptive control systems
Objavljeno: 31.05.2012; Ogledov: 870; Prenosov: 17
URL Povezava na celotno besedilo

3.
An intelligent system for structural analysis-based design improvements
Marina Novak, Bojan Dolšak, 2008, izvirni znanstveni članek

Opis: The goal of the research work presented in this paper was to collect, organize, and write the knowledge and experience about structural analysis-based design improvements into a knowledge base for a consultative advisory intelligent decision support system. The prototype of the system presented proposes possible design changes that should be taken into consideration to improve the design candidate according to the results of a prior stress-strain or thermal analysis. The system can be applied either in the design of new products or as an educational tool.
Ključne besede: computer-aided design, structural optimisation, knowledge based systems, decision support
Objavljeno: 31.05.2012; Ogledov: 1321; Prenosov: 14
URL Povezava na celotno besedilo

4.
Prediction of maintenance of sinus rhythm after electrical cardioversion of atrial fibrillation by non-deterministic modelling
Petra Žohar, Miha Kovačič, Miran Brezočnik, Matej Podbregar, 2005, izvirni znanstveni članek

Opis: Atrial fibrillation (AF) is the most common rhythm disorder. Because of the high recurrence rate of AF after cardioversion and because of potential side effects of electrical cardioversion, it is clinically important to predict persistence of sinus rhythm after electrical cardioversion before it is attempted. The aim of our study was the development of a mathematical model by"genetic" programming (GP), a non-deterministic modelling technique, which would predict maintenance of sinus rhythm after electrical cardioversion of persistent AF. PATIENTS AND METHODS: Ninety-seven patients with persistent AF lasting more than 48 h, undergoing the first attempt at transthoracic cardioversion were included in this prospective study. Persistence of AF before the cardioversion attempt, amiodarone treatment, left atrial dimension,mean, standard deviation and approximate entropy of ECG R-R intervals were collected. The data of 53 patients were randomly selected from the database and used for GP modelling; the other 44 data sets were used for model testing. RESULTS: In 23 patients sinus rhythm persisted at 3 months. In the other 21 patients sinus rhythm was not achieved or its duration was less than 3 months. The model developed by GP failed to predict maintenance ofsinus rhythm at 3 months in one patient and in six patients falsely predicted maintenance of sinus rhythm. Positive and negative likelihood ratiosof the model for testing data were 4.32 and 0.05, respectively. Using this model 15 of 21 (71.4%) cardioversions not resulting in sinus rhythm at 3 months would have been avoided, whereas 22 of 23 (95.6%) cardioversions resulting in sinus rhythm at 3 months would have been administered. CONCLUSION: This model developed by GP, including clinical data, ECG data from the time-domain and nonlinear dynamics can predict maintenance of sinus rhythm. Further research is needed to explore its utility in the present or anexpanded form.
Ključne besede: optimisation methods, evolutionary optimisation methods, genetic algorithms, genetic programming, defibrillation, cardiac arrest prediction, atrial fibrillation, electrical cardioversion, prediction
Objavljeno: 01.06.2012; Ogledov: 1129; Prenosov: 21
URL Povezava na celotno besedilo

5.
Software tools overview : process integration, modelling and optimisation for energy saving and pollution reduction
Hon Loong Lam, Jiri Klemeš, Zdravko Kravanja, Petar Varbanov, 2011, izvirni znanstveni članek

Opis: This paper provides an overview of software tools based on long experience andapplications in the area of process integration, modelling and optimisation. The first part reviews the current design practice and the development of supporting software tools. Those are categorised as: (1) process integration and retrofit analysis tools, (2) general mathematical modelling suites with optimisation libraries, (3) flowsheeting simulation and (4) graph-based process optimisation tools. The second part covers an assessment of tools which enable the generation of new sustainable alternatives to adapt to the future needs. They deal with waste, environment, energy consumption, resources depletion and production cost constrains. The emphasis of the sustainable process design tools is largely on the evaluation of process viability under sustainable economic conditions, synthesis of sustainable process and supply chain process maintenance and life cycle analysis. Major software tools development and the potential of the research-based tools for sustainable process design task are overviewed in theconcluding part.
Ključne besede: software tools, process integration, process modelling, process optimisation, energy saving
Objavljeno: 01.06.2012; Ogledov: 1105; Prenosov: 34
URL Povezava na celotno besedilo

6.
Optimisation of tree path pipe network with nonlinear optimisation method
Danijela Urbancl, Darko Goričanec, 2009, izvirni znanstveni članek

Opis: In this paper, the optimisation of pipe network with hot water is presented. The mathematical model, consisting of the nonlinear objective function and system of nonlinear equations for the hydraulics limitations is developed. On its basis, the computer program for determination optimal tree path with the use of simplex method was solved. For economic estimation the capitalised value method, which consider all costs of investment and operation was used. The results are presented for real case study network with 24 nodes and 33 pipe sectors.
Ključne besede: district heating, pipe network, optimisation, non-linear programming, simplex method
Objavljeno: 01.06.2012; Ogledov: 1267; Prenosov: 43
URL Povezava na celotno besedilo

7.
A model of data flow in lower CIM levels
Igor Drstvenšek, Ivo Pahole, Jože Balič, 2004, izvirni znanstveni članek

Opis: After years of work in fields of computer-integrated manufacturing (CIM), flexible manufacturing systems (FMS), and evolutionary optimisation techniques, several models of production automation were developed in our laboratories. The last model pools the discoveries that proved their effectiveness in the past models. It is based on the idea of five levels CIM hierarchy where the technological database (TDB) represents a backbone of the system. Further on the idea of work operation determination by an analyse of the production system is taken out of a model for FMS control system, and finally the approach to the optimisation of production is supported by the results of evolutionary based techniques such as genetic algorithms and genetic programming.
Ključne besede: computer integrated manufacturing, flexible manufacturing systems, evolutionary optimisation techniques, production automation, CIM hierarchy, technological databases, production optimisation, genetic algorithms, genetic programming
Objavljeno: 01.06.2012; Ogledov: 1066; Prenosov: 31
URL Povezava na celotno besedilo

8.
Relational database as a cogitative part of an intelligent manufacturing system
Igor Drstvenšek, Mirko Ficko, Jože Balič, 2004, izvirni znanstveni članek

Opis: An intelligent manufacturing system is intended to produce one or more subjects that it is designed for in an optimal way. This means that it has to find a proper production process to produce the subject in an optimal way. The manufacturing system can be called "intelligent" when it is able to find applicable optimisation criteria upon its past experiences thus improving its performance in future. Therefore, an intelligent manufacturing system needs capabilities to store data and make decisions upon them. Such a "brain" can be established by a proper design of a technological database and its database management system (DBMS). Examining all constitutive parameters of a work operation a model of a production process organization can be made, which can serve as a basis for a suitable database design. In addition, an application programme that will check the existence and availability of work operations in the database has to be added to the DBMS. What remains are some optimisation criteria upon which we will choose an operation among suitable and available work operations. This task is fulfilled by a genetic algorithm optimisation technique that would consider work operations' data as parameters of optimisation and on this basis search the optimal one out of the set of available operation.
Ključne besede: production processes, optimisation, relational database, database management systems, production automation, manufacturing system
Objavljeno: 01.06.2012; Ogledov: 1011; Prenosov: 33
URL Povezava na celotno besedilo

9.
Predicting defibrillation success by "genetic" programming in patients with out-of-hospital cardiac arrest
Matej Podbregar, Miha Kovačič, Aleksandra Podbregar-Marš, Miran Brezočnik, 2003, izvirni znanstveni članek

Opis: In some patients with ventricular fibrillation (VF) there may be a better chance of successful defibrillation after a period of chest compression and ventilation before the defibrillation attempt. It is therefore important to know whether a defibrillation attempt will be successful. The predictive powerof a model developed by "genetic" programming (GP) to predict defibrillation success was studied. Methods and Results: 203 defibrillations were administered in 47 patients with out-of-hospital cardiac arrest due to a cardiac cause. Maximal amplitude, a total energy of power spectral density, and the Hurst exponent of the VF electrocardiogram (ECG) signal were included in the model developed by GP. Positive and negative likelihood ratios of the model for testing data were 35.5 and 0.00, respectively. Using a model developed by GP on the complete database, 120 of the 124 unsuccessful defibrillations would have been avoided, whereas all of the 79 successful defibrillations would have been administered. Conclusion: The VF ECG contains information predictive of defibrillation success. The model developed by GP, including data from the time-domain, frequency-domain and nonlinear dynamics, could reduce the incidence of unsuccessful defibrillations.
Ključne besede: optimisation methods, evolutionary optimisation methods, genetic algorithms, genetic programming, defibrillation, cardiac arrest prediction
Objavljeno: 01.06.2012; Ogledov: 887; Prenosov: 29
URL Povezava na celotno besedilo

10.
Modeling of forming efficiency using genetic programming
Miran Brezočnik, Jože Balič, Zlatko Kampuš, 2001, izvirni znanstveni članek

Opis: This paper proposes new approach for modeling of various processes in metal-forming industry. As an example, we demonstrate the use of genetic programming (GP) for modeling of forming efficiency. The forming efficiency is a basis for determination of yield stress which is the fundamental characteristic of metallic materials. Several different genetically evolved models for forming efficiency on the basis of experimental data for learning were discovered. The obtained models (equations) differ in size, shape, complexity and precision of solutions. In one run out of many runs of our GP system the well-known equation of Siebel was obtained. This fact leads us to opinion that GP is a very powerful evolutionary optimization method appropriate not only for modeling of forming efficiency but also for modeling of many other processes in metal-forming industry.
Ključne besede: metal forming, yield stress, forming efficiency, mathematical modeling, adaptation, genetic methods, genetic algorithm, genetic programming, artificial intelligence, process optimisation
Objavljeno: 01.06.2012; Ogledov: 967; Prenosov: 40
URL Povezava na celotno besedilo

Iskanje izvedeno v 0.27 sek.
Na vrh
Logotipi partnerjev Univerza v Mariboru Univerza v Ljubljani Univerza na Primorskem Univerza v Novi Gorici