Abstract 

     The aim of this work is to create a power control system for wind turbines based on fuzzy logic. Three power control loop was considered including: changing the pitch angle of  the blade, changing the length of the blade and turning the nacelle. The stochastic law was given for changes and instant inaccurate assessment of wind conditions changes. Two different algorithms were used for fuzzy inference in the control loop, the Mamdani and Larsen algorithms. These two different algorithms are materialized and developed in this study in Matlab-Fuzzy logic toolbox which has been practically implemented using necessary intelligent control system in electrical engineerin

This research investigated the importance and priorities of the project overhead costs in Iraq via a questionnaire using the fuzzy analytic hierarchy process technique (FAHP). Using this technique is very important in the uncertain circumstances as in our country. The researcher reached to frame an equation through the results of the priorities of weights include the percentages of each of the main items of the project overhead costs. The researcher tested this equation by applying it to one of the completed projects and the results showed suitability for the application. The percentages of the (salaries, grants, and incentives) and (fieldwork requirements) in equation represent approximately two-thirds of project overhe

The production companies in the Iraqi industry environment facing many of the problems related to the management of inventory and control In particular in determining the quantities inventory that should be hold it. Because these companies  adoption on personal experience and some simple mathematical methods which lead to the identification of inappropriate quantities of inventory.

       This research aims to identify the economic quantity of production and purchase for the Pepsi can 330ml and essential components in Baghdad soft drinks Company in an environment dominated by cases of non ensure and High fluctuating as a result of fluctuating demand volumes and costs ass

ABSTRUCT

This research aims at examining the expected gap between the fact of planning and controlling process of production at the State Company for Electric Industries and implementation of material requirements planning system in fuzzy environment. Developing solutions to bridge the gap is required to provide specific mechanisms subject to the logic of fuzzy rules that will keep pace with demand for increased accuracy and reduced waiting times depending on demand forecast, investment in inventory to reduce costs to a minimum.

The proposed solutions for overcoming the research problem has required some  questions reflecting the problem with its multiple dimensions, which ar

        In real situations all observations and measurements are not exact numbers but more or less non-exact, also called fuzzy. So, in this paper, we use approximate non-Bayesian computational methods to estimate inverse Weibull parameters and reliability function with fuzzy data. The maximum likelihood and moment estimations are obtained as non-Bayesian estimation. The maximum likelihood estimators have been derived numerically based on two iterative techniques namely “Newton-Raphson” and the “Expectation-Maximization” techniques. In addition, we provide compared numerically through Monte-Carlo simulation study to obtained estimates of the parameters and reliability function i

The process of evaluating business processes, complex, repetition of procurement processes, need for raw materials and frequency of demand, which makes dealing with suppliers in the evaluation process, making the need for a process intervention in the process. Lighter on the other hand.

Many Iraqi companies suffer from problems related to suppliers, and cases of administrative and financial corruption are often raised regarding this type of contract and from this reality the necessity of researching this problem and trying to develop some solutions to reduce its impact on the companies' work, by using a method that works according to the standards adopted in Evaluation and selection of the supplier in the

Grass trimming operation is widely done in Malaysia for the purpose of maintaining highways. Large number of operators engaged in this work encounters high level of noise generated by back pack type grass trimmer used for this purpose. High level of noise exposure gives different kinds of ill effect on human operators. Exact nature of deteriorated work performance is not known. For predicting the work efficiency deterioration, fuzzy tool has been used in present research. It has been established that a fuzzy computing system will help in identification and analysis of fuzzy models fuzzy system offers a convenient way of representing the relationships between the inputs and outputs of a system in the form of IF-THEN rules. The paper presents

The research endeavors to harness the benefits stemming from the integration of constraint theory into construction project management, with the primary goal of mitigating project completion delays. Additionally, it employs fuzzy analysis to determine the relative significance of fundamental constraints within projects by assigning them appropriate weights. The research problem primarily revolves around two key issues. Firstly, the persistent utilization of outdated methodologies and a heavy reliance on workforce experience without embracing modern computerized technologies. Secondly, the recurring problem of project delivery delays. Construction projects typically encompass five fundamental constraint types: cost restrictions, tim

Ration power plants, to generate power, have become common worldwide. One such one is the steam power plant. In such plants, various moving parts of heavy machines generate a lot of noise. Operators are subjected to high levels of noise. High noise level exposure leads to psychological as well physiological problems; different kinds of ill effects. It results in deteriorated work efficiency, although the exact nature of work performance is still unknown. To predict work efficiency deterioration, neuro-fuzzy tools are being used in research. It has been established that a neuro-fuzzy computing system helps in identification and analysis of fuzzy models. The last decade has seen substantial growth in development of various neuro-fuzzy systems

Quality control charts are limited to controlling one characteristic of a production process, and it needs a large amount of data to determine control limits to control the process. Another limitation of the traditional control chart is that it doesn’t deal with the vague data environment. The fuzzy control charts work with the uncertainty that exists in the data. Also, the fuzzy control charts investigate the random variations found between the samples. In modern industries, productivity is often of different designs and a small volume that depends on the market need for demand (short-run production) implemented in the same type of machines to the production units. In such cases, it is difficult to determine the contr