Harun Taşkın

Technological intelligence and competitive strategies: An application study with fuzzy logic

During the last few decades, technology and strategies have become one of the most important factors for the countries, firms and for their competitive properties. Technological intelligence, management, forecasting and innovation are big problems for undeveloped countries but considerable strengths for the developed ones and the firms that attach importance to these concepts. This paper describes technology and its concepts and their integration of competitive factors and strategies, also based on the findings and comments of a sample survey of technological intelligence and activities in Turkish Manufacturing Industry.

FUZZYFCC: Fuzzy logic control of a fluid catalytic cracking unit (FCCU) to improve dynamic performance

Abstract In this paper, fuzzy logic control of a fluid catalytic cracking unit (FCCU) is proposed. Fluid catalytic cracking (FCC) process is a unit that converts heavy distillates like gas oil or residues to gasoline and middle distillates using cracking catalyst. About 45% of worldwide gasoline production comes from FCC processes and its ancillary units. Since a typical FCC unit can process a large amount of the feedstock into more valuable products, the overall economic benefits of a refining could be considerably increased if proper control and optimization strategies are implemented. FCC processes are known to be very difficult to model and control because of the large process scale, complicated hydro-dynamics and complex kinetics of both cracking and coke burning reactions. One of the more heavily investigated terms of nonlinear control, in the field of “intelligent control”, is that due to fuzzy logic controllers (FLCs). FLCs have been successfully applied to a stream of difficult, nonlinear dynamical process such as FCC. Here, with an application to a Turkish refinery FCC unit of FLC fuzzy results obtained using Matlab-Fuzzy Logic Toolbox version 6.5 were found to be acceptable. The paper indicates how fuzzy logic control (FLC), as a promising control technique, would be effectively used for improved process control of FCC in refinery process industry.

Bofy-fuzzy logic control for the basic oxygen furnace (BOF)

Abstract In this paper, fuzzy modeling for the control of basic oxygen furnace (BOF) processes is proposed. BOF is a widely preferred and effective steel making method due to its higher productivity and considerably low production cost. Therefore, today almost 65% of the total crude steel production in the world is met by using the BOF method. Higher steel output at lower cost is one of the main objectives of modern steel making methods. In order to accomplish this objective, fuzzy modeling was employed in this study in order to control some variables related to the BOF process. Fuzzy modeling and control in BOF promise a solution to the strongly non-linear problems associated with the process, which have so far proven extremely difficult to be solved by conventional control methods. Data set was selected as inputs from the real empirical BOF data in an integrated steel plant based in Turkey. Although there were negligible deviations from the target values, most of the fuzzy results obtained using MATLAB-Fuzzy Logic Toolbox version 5.0 were found to be acceptable. As a result of the application of the proposed modeling, acceptable levels of compatibility were achieved compared to the empirical BOF data and targeted steel composition. The paper indicates how fuzzy logic would be effectively used for improved process control of BOF furnace in steel making industry.

Selecting the optimal shift numbers using fuzzy control model: a paint factory’s facility application

Number of shifts is one of the most important criteria for the production planners to minimize the production costs. The first measurement of the facility, where we executed the application, is optimizing the manpower rotation in B12 production, a special kind of chemical, which is used for paint binders. Seasonal variations in demand of B12 add more importance to the number of shifts in the facility. The purpose of this article is to optimize the shift periods subject to raw material, shipping date, inventory and demand constraints. The model is developed for a paint factory’s reactor facility. The production system has a raw material inventory, a reactor, and a finished goods inventory. We use fuzzy control to optimize the number of shifts under the constraints, given before.

Fuzzy goal programming for health-care organization

Abstract This paper presents fuzzy goal programming using with exponential membership function, which uses the modeling, and solving of health care system for optimal efficient management. The limited human resources and budget in a health-care organization are described with fuzzy conditions for determine the future strategies for unknown situations. In this study, the exponential membership function is preferred dynamic situation in next period. The study aims to assign the resources for optimization with enable management to meet the fuzzy objective of minimizing the system costs while patients are satisfied. The fuzzy goals are identified and prioritized for the strategic planning and resource allocation. A fuzzy goal-programming model is illustrated using the data provided by a health-care organization in Turkey-Sakarya private hospital.

Comparison of OR and AI methods in discrete manufacturing using fuzzy logic

Since 1950s the techniques of Operations Research (OR) and Optimization have been utilized to increase the efficiency of the production systems. With the widespread use of computers, it has even become easier to deal with industrial problems. However the complexity of the problems still reveals the difficulty in providing solutions. The use of artificial intelligence (AI) seems to attract the attention of the researcher to overcome to the difficulties. This has already been realized with several successful applications. In this study, the use of AI and OR techniques is compared using fuzzy logic. The progress of manufacturing systems, characteristics of production processes, system managements and system behavior are taken into account. The study is focussed on only discrete manufacturing.

An elective course suggestion system developed in computer engineering department using fuzzy logic

Besides required courses which are compulsory for each student to be taken, universities also offer elective courses chosen by the students themselves. In their undergraduate study, since students are not guided about the elective courses, they lack information about the description and content of the course and generally fail to take the appropriate ones for their course of study. As a solution, using the knowledge of the previous required courses taken by the student it is possible to guide the student about elective courses appropriate for him/her. In this study, information from the transcripts of students are analyzed, and using this information a relationship is conducted between the required courses and the elective courses taken previously by the student. Rules are extracted by the help of data mining and an elective course suggestion system is developed using fuzzy logic. Successful results are obtained from the tests; it is observed that the students successful from the required courses are also successful in the related elective ones.

Control and synchronization of chaotic supply chains using intelligent approaches

Intelligent control and synchronization of chaotic supply chain are applied.Artificial neural networks based controllers are used for the control.Adaptive neuro-fuzzy inference system based controllers are used for synchronization.Linear feedback and active control signals are also used.Computer simulations show that the proposed approach is very effective. This paper presents the control of chaotic supply chain with Artificial Neural Network (ANN) based controllers and the synchronization of two identical chaotic supply chains that have different initial conditions with Adaptive Neuro-Fuzzy Inference System (ANFIS) based controllers. A hybrid intelligent control model is designed in which the linear feedback and active control signals are also used for achieving the control and synchronization, respectively. ANN and ANFIS controllers are trained according to the model. Thereby, the advantages of classical and intelligent control methods are combined. Computer simulations show that the proposed approach is very effective for the control and synchronization of chaos in supply chain systems.

A healthcare management system for Turkey based on a service-oriented architecture

The current Turkish healthcare management system has a structure that is extremely inordinate, cumbersome and inflexible. Furthermore, this structure has no common point of view and thus has no interoperability and responds slowly to innovations. The purpose of this study is to show that using which methods can the Turkish healthcare management system provide a structure that could be more modern, more flexible and more quick to respond to innovations and changes taking advantage of the benefits given by a service-oriented architecture (SOA). In this paper, the Turkish healthcare management system is chosen to be examined since Turkey is considered as one of the Third World countries and the information architecture of the existing healthcare management system of Turkey has not yet been configured with SOA, which is a contemporary innovative approach and should provide the base architecture of the new solution. The innovation of this study is the symbiosis of two main integration approaches, SOA and Health Level 7 (HL7), for integrating divergent healthcare information systems. A model is developed which is based on SOA and enables obtaining a healthcare management system having the SSF standards (HSSP Service Specification Framework) developed by the framework of the HSSP (Healthcare Services Specification Project) under the leadership of HL7 and the Object Management Group.

Performance Evaluation of Small-Medium Enterprises Based on Management and Organization

Characterization of New U–Ni–X2 Splats and Study of their Physical Properties Z. Molčanováa,∗, M. Mihalik, M. Mihalik, Jr., M. Reiffers, A. Džubinská, M. Huráková, V. Kavečanský, M. Paukov and L. Havela Institute of Experimental Physics SAS, Watsonova 47, 040 01 Košice, Slovakia Faculty of Humanities and Natural Sciences, University of Prešov, 17. novembra 1, SK 081 16 Prešov, Slovakia Department of Condensed Matter Physics, Charles University, Ke Karlovu 5, 121 16 Prague 2, Czech Republic