تعد لوحات السيطرة الخاصة بالمراقبة والسيطرة على نوعية الانتاج احدى الاساليب العلمية الاحصائية التي تستخدم لمراقبة سير العملية الانتاجية اثناء سيرالعنلية الانتاجية اثناء سيرها في مراحل الانتاج والتي عادة ما تتكون من حد وسطي وحدين اعلى وادنى للسيطرة على نوعية ودقة الانتاج متمثلا بقيم عددية . ومن ثم فان العملية الانتاجية اما ان تكون تحت السيطرة او خارجها بالاعتماد على قيم المشاهادات العددية. وفي بعض الاحيا

Quality control is an effective statistical tool in the field of controlling the productivity to monitor and confirm the manufactured products to the standard qualities and the certified criteria for some products and services and its main purpose is to cope with the production and industrial development in the business and competitive market. Quality control charts are used to monitor the qualitative properties of the production procedures in addition to detecting the abnormal deviations in the production procedure. The multivariate Kernel Density Estimator control charts method was used which is one of the nonparametric methods that doesn’t require any assumptions regarding the distribution o

Linear discriminant analysis and logistic regression are the most widely used in multivariate statistical methods for analysis of data with categorical outcome variables .Both of them are appropriate for the development of linear  classification models .linear discriminant analysis has been that the data of explanatory variables must be distributed multivariate normal distribution. While logistic regression no assumptions on the distribution of the explanatory data. Hence ,It is assumed that logistic regression is the more flexible and more robust method in case of violations of these assumptions.

In this paper we have been focus for the comparison between three forms for classification data belongs

Research summarized in applying the model  of fuzzy goal programming for aggregate production planning , in General Company for hydraulic industries / plastic factory to get an optimal production plan  trying to cope with the impact that fluctuations in demand and  employs all available resources using two strategies where they are available   inventories  strategy and  the strategy of  change in the level of the workforce, these   strategies  costs are usually imprecise/fuzzy. The plant administration trying to minimize total production costs, minimize carrying costs and minimize changes in labour levels. depending on the gained data from th

    The attribute quality control charts are one of the main useful tools to use in control of quality product in companies. In this paper utilizing the statistical procedures to find the attribute quality control charts for through fuzzified the real data which we got it from Baghdad Soft Drink Company in Iraq, by using triangular membership function to obtain the fuzzy numbers then employing the proposed ranking function to transform to traditional sample. Then, compare between crisp and fuzzy attribute quality control.

In this paper, we will illustrate a gamma regression model assuming that the dependent variable (Y) is a gamma distribution and that it's mean ( ) is related through a linear predictor with link function which is identity link function g(μ) = μ. It also contains the shape parameter which is not constant and depends on the linear predictor and with link function which is the log link and we will estimate the parameters of gamma regression by using two estimation methods which are The Maximum Likelihood and the Bayesian and a comparison between these methods by using the standard comparison of average squares of error (MSE), where the two methods were applied to real da

Quality is one of the important criteria to determine the success of product. So quality control is required for all stages of production to ensure a good final product with lowest possible losses. Control charts are the most important means used to monitor the quality and its accuracy is measured by quickly detecting unusual changes in the quality to maintain the product and reduce the costs and losses that may result from the defective items. There are different types of quality control charts and new types appeases involving the concept of fuzziness named multinomial fuzzy quality control chart (FM) , dividing the product to accepted and not may not be accurate therefore adding fuzziness concept to quality charts confirm and a

  Many production companies suffers from big losses because of  high production cost and low profits for several reasons, including raw materials high prices and no taxes impose on imported goods also consumer protection law deactivation and national product and customs law, so most of consumers buy imported goods because it is characterized by modern specifications and low prices.

  The production company also suffers from uncertainty in the cost, volume of production, sales, and availability of raw materials and workers number because they vary according to the seasons of the year.

  I had adopted in this research fuzzy linear program model with fuzzy figures

    Multivariate Non-Parametric control charts were used to monitoring the data that generated by using the simulation, whether they are within control limits or not. Since that non-parametric methods do not require any assumptions about the distribution of the data.  This research aims to apply the multivariate non-parametric quality control methods, which are Multivariate Wilcoxon Signed-Rank ( ) , kernel principal component analysis (KPCA) and k-nearest neighbor ( −

The Purpose of this research is a comparison between two types of multivariate GARCH models BEKK and DVECH to forecast using financial time series which are the series of daily Iraqi dinar exchange rate with dollar, the global daily of Oil price with dollar and the global daily of gold price with dollar for the period from 01/01/2014 till 01/01/2016.The estimation, testing and forecasting process has been computed through the program RATS. Three time series have been transferred to the three asset returns to get the Stationarity, some tests were conducted including Ljung- Box, Multivariate Q and Multivariate ARCH to Returns Series and Residuals Series for both models with comparison between the estimation and for