Sharif Digital Repository

Hospitals increasingly use control charts to monitor clinical processes and their outcomes. In medical context, control charts should have stable performance when different patients with different levels of risk enter the hospital. In order to monitor multi-Attribute medical processes, we propose a new control chart with entities having different levels of risk. First, risk-Adjusted multivariate cumulative sum control chart (RA-MCUSUM) is developed. Then, simulation experiences are performed to demonstrate the application and to evaluate its performance in terms of in-control average run length (ARL0) stability with the one of a standard MCUSUM chart. The results show that while the standard... 

Over the last decade, there have been an increasing interest in the techniques of process monitoring of high-quality processes. Based upon the cumulative counts of conforming (CCC) items, Geometric distribution is particularly useful in these cases. Nonetheless, in some processes the number of one or more types of defects on a nonconforming observation is also of great importance and must be monitored simultaneously. However, there usually exist some correlations between these two measures, which obligate the use of multi-attribute process monitoring. In the literature, by assuming independence between the two measures and for the cases in which there is only one type of defect in... 

In this paper, a new multi-attribute T2 control chart is initially proposed to monitor multi-attribute processes based on a transformation technique. Then, the maximum likelihood estimator of a multivariate Poisson process change point is derived for unknown changes that are assumed to belong to a family of monotonic changes. Using extensive simulation experiments, the performance of the proposed change-point estimator is compared to the ones derived for step changes and linear-trend disturbances, when the true change types are step change, linear trends and multiple-step changes. We show when the type of the change is not known a priori, the proposed estimator is an appropriate choice,... 

This paper attempts to present a method for differentiating between multi-attribute decision procedures and to identify some competent procedures for major decision problems, where a matrix of alternative-measure of effectiveness and a vector of weights for the latter are available. In this respect, several known multi-attribute analysis procedures are chosen, and the same procedures are exploited to evaluate themselves, based on some evaluation criteria. This is done from an engineering viewpoint and in the context of a transportation problem, using a real case light rail transit network choice problem for the City of Mashhad, and the results are presented. Two concepts have been proposed... 

In this study, in order to create a decision-making model on water resources projects, a hierarchy of criteria has been developed by public participation. The Value Management methodology has been used for extraction of the effective criteria and attributes in the scope of Integrated Water Resources Management (IWRM). The hierarchy is generic for water resources management in the Islamic Republic of Iran. Since the evaluations of alternatives with respect to some attributes are uncertain and vague, fuzzy set theory has been used. By merging fuzzy set theory and multi-attribute decision-making a new Decision Support System (DSS), namely FDM, has been developed to compare different... 

We propose a ranking method for fuzzy numbers. In this method a preference function is defined by which fuzzy numbers are measured point by point and at each point the most preferred number is identified. Then, these numbers are ranked on the basis of their preference ratio. Therefore, fuzzy numbers are compared relatively and not necessarily one is preferred absolutely over the others. This method is especially designed to evaluate alternatives in multi criteria or multi-attribute decision making. The method is intuitive and can be used to discriminate between numbers easily. The method is specially tailored for triangular fuzzy numbers (TFN) and an algorithm is presented to determine the... 

Identification of the change point in multi-attribute processes make the corrective measures to be employed sooner. This of course results in considerable amount of time and money savings. In real-world problems, since most of the process changes are due to instantaneous causes (step-change), a new method is proposed in this paper to derive the maximum likelihood estimator of the time of a step-change in the mean vector of multi-attribute processes. The results of a performance study based on a numerical example are encouraging  

Since multi-attribute control charts have received little attention compared with multivariate variable control charts, this research is concerned with developing a new methodology to employ the multivariate exponentially weighted moving average (MEWMA) charts for m-attribute binomial processes; the attributes being the number of nonconforming items. Moreover, since the variable sample size and sampling interval (VSSI) MEWMA charts detect small process mean shifts faster than the traditional MEWMA, an economic design of the VSSI MEWMA chart is proposed to obtain the optimum design parameters of the chart. The sample size, the sampling interval, and the warning/action limit coefficients are... 

In a production process, when the quality of a product depends on more than one correlated characteristic, multivariate quality control techniques are used. Although multivariate statistical process control is receiving increased attention in the literature, little work has been done to deal with multi-attribute processes. In monitoring the quality of a product or process in multi-attribute environments in which the attributes are correlated, several issues arise. For example, a high number of false alarms (type I error) occur and the probability of not detecting defects (type II error) increases when the process is monitored by a set of independent uni-attribute control charts. In this... 

Previous empirical research about the functions of innovative systems has been less enabled to present practical strategies for managers’ decisions. This paper aims to determine the boundaries of the innovation system in the oil industry by prioritizing strategic innovative upstream technologies for policy-making and commercializing within the framework of energy technological innovation systems. This paper proposes a novel fuzzy approach based on distance from ideals to scrutinize the effects of effective criteria on the policy-making process and rank new and essential technologies in various fields. The developed fuzzy Technique for Order of Preference by Similarity to Ideal Solution... 

Purpose: The purpose of this paper is to propose two control charts to monitor multi-attribute processes and then a maximum likelihood estimator for the change point of the parameter vector (process fraction non-conforming) of multivariate binomial processes. Design/methodology/approach: The performance of the proposed estimator is evaluated for both control charts using some simulation experiments. At the end, the applicability of the proposed method is illustrated using a real case. Findings: The proposed estimator provides accurate and useful estimation of the change point for almost all of the shift magnitudes, regardless of the process dimension. Moreover, based on the results obtained... 

Users often have very specific visual content in mind that they are searching for. The most natural way to communicate this content to an image search engine is to use key-words that specify various properties or attributes of the content. A naive way of dealing with such multi-attribute queries is the following: train a classifier for each attribute independently, and then combine their scores on images to judge their fit to the query. We argue that this may not be the most effective or efficient approach. Conjunctions of attribute often correspond to very characteristic appearances. It would thus be beneficial to train classifiers that detect these conjunctions as a whole. But not all... 

Information technology (IT) outsourcing has been recognized as a new methodology in many organizations. Yet making an appropriate decision with regard to selection and use of these methodologies may impose uncertainties and risks. Estimating the occurrence probability of risks and their impacts organizations goals may reduce their threats. In this study, an extended analytical hierarchical process method is tailored based on interval-valued hesitant fuzzy information to assess the risks in IT outsourcing. In the proposed approach, the weight of each decision maker is implemented in process of the proposed method by considering the concept of simple additive weighting method to decrease the... 

Since the product quality of many industrial processes depends upon more than one dependent variable or attribute, they are either multivariate or multi-attribute in nature. Although multivariate statistical process control is receiving increased attention in the literature, little work has been done to deal with multi-attribute processes. In this article, we develop a new methodology to monitor multi-attribute processes. To do this, first we transform multi-attribute data in a way that their marginal probability distributions have almost zero skewness. Then, we estimate the transformed covariance matrix and apply the well-known T2 control chart. In order to illustrate the proposed method... 

In multi-attribute process monitoring, when a control chart signals an out-of-control condition indicating the existence of a special cause, knowing when the process has really changed (the change point) accelerates the identification of the source of the special cause and makes the corrective measures to be employed sooner. This, of course, results in a considerable amount of savings in time and money. Since many real world multi-attribute processes are Poisson and most process changes are step-change, a new method is proposed, in this paper, to derive the maximum likelihood estimator of the time of a step-change in the mean vector of multivariate Poisson processes. In this method, two... 

The quality characteristics of both manufacturing and service industries include not only the variables but the attributes as well. While a substantial research have been performed on auto-correlated variables, little attempt has been fulfilled for auto-correlated attributes. Ignoring the imbedded autocorrelation structure in constructing control charts cause not only the in-control run length to decrease, but also the false alarms to increase. To overcome these shortcomings, in this research, an autoregressive vector first models the autocorrelation structure of the process data. Then, a modified Elman neural network is developed to generate simulated data using the ARTA algorithm. Next, a... 

One of the most important aspects of a successful space mission is the transition to the correct orbit and maintaining it. As a result, many modern orbit transfer techniques have been developed in space industry in order to accomplish this task in a more reliable and less expensive way. However, when it comes to the design of student satellites, usually there are serious limitations on the financial resources, technical database and satellite industry experts. These limitations may compromise the access to advanced methods and techniques. Therefore, reliability and expenses may no longer be the only criteria to be met in the process of design. As a result, at each step of the design, a... 

Quality characteristics are subject of both manufacturing and service industries, which include not only the variables but the attributes as well. In Quality Control area substantial research has been done for Auto-correlated variables; however, no attempt was done for Auto-correlated attributes. Ignoring the autocorrelation structure in constructing control charts cause the in-control run length to decrease, and the false alarms to increase as such. In this article we develop a new methodology based upon the modified Elman neural network capabilities to overcome this problem. Moreover, instead of back propagation, simulated annealing is suggested as an alternative training technique that is... 

Security constrained Preventive Maintenance (PM) scheduling is addressed as a crucial issue especially coping with new challenges of smart grids. Under the smart grid environment, Demand Response Resources (DRRs) are considered as virtual power plants in energy policy decisions which affect the controllability of power system ranging from short-term to long-term. Here, DRRs are regarded as a virtual resource of capacity reserve acquisition. Furthermore, under new environment, multifarious objectives will be imposed to PM scheduling which can be replicated into a single objective problem via a weighted approach with consideration of arbitrary weighting coefficients. In this paper, a new...