Journal of Quality Engineering and Management

Abstract Nowadays, statistical analysis and monitoring of networks and early detection of anomalies with a significant growth rate have received more attention than before in recent years. In the real world, there is a wide range of networks analyzed and improved through network monitoring solutions, such as transportation, supply-demand, financial exchanges, health care, as well as the social ones, the analysis of the results can be beneficial to the stakeholders. The basis of the research is on identifying and solving the real problem. In other words, a real problem is identified in the country and a methodology is developed to solve it. The case study is the monitoring of a network of centers that provide emergency services in cities. The nature of this network is dynamic, feature-based, directed and weighted. The results of this study show that by modeling complex systems as a network and its continuous monitoring, abnormal situations can be identified and managed early and crises in cities can be prevented.

Abstract Reliability studies are an essential part of every management program for equipment maintenance. As systems become more complex, maintenance strategies become critical for making sustainable management decisions. Unexpected failures in a system can be the primary reason for the poor performance of industrial machinery and equipment. Various fault resistance mechanisms are utilized to make critical decisions for the system. In the present paper, a two-parameter Weibull distribution approach is considered to evaluate the heat exchanger datasets in the petrochemical industry using Isograph Hazop + v7.0 software. As the effective execution of a system depends on its reliability and planning under suitable conditions, this paper presents a strategy for finding the reliability to calculate the preventive maintenance intervals in actual systems. This approach leads to fewer number of inspections and fewer repair activities, higher safety and reliability of industrial units and also, higher economic benefit.
 

Abstract  Stroke and heart attack are the most important causes of mortality in the world. Identifying communities at risk for stroke and heart attack is an important step in improving the care systems of these patients, strokes and heart attacks are important to the emergency department, The aim of this study is to improve emergency department performance and improve the quality of emergency and hospitals resource allocation. Therefore, the spatial autocorrelation of stroke and heart attack was investigated using spatial statistics. Distribution of these two types of complications in different parts of Tehran was identified by using hot spots analysis and Moran's local autocorrelation index. Also, considering the spatial autocorrelation, to investigate the factors affecting the occurrence of this event, the relationship between the incidence rate of stroke and heart attack with AQI air pollution index And the level of development in different region of Tehran was investigated using Spearman correlation coefficient. 
 

Abstract In some Problems, quality of a process or a product is described by a relationship between one or more response variables and one or more explanatory variables. In the case that the response variables are correlated, quality of a process or a product can be characterized by a multivariate Profile. In some situations, the values of response variables in a Profile are auto-correlated due to the time collapse between two successive samples. The autocorrelation affects the regression parameters estimates and as a result, the performance of control charts in detecting shifts deteriorates. In this paper, an auto-correlated multivariate simple linear profile is considered and assumed that the autocorrelation can be described by AR (1) and MA(1) models. Then, two control charts for monitoring the multivariate simple linear profiles are suggested. The Performance of the proposed control charts are compared in Phase I by using simulation in terms of Power criterion.

Abstract In this article, we intend to look at the concept of quality management and the role of the organization's work units, to identify and introduce the main criteria of the excellence model of work units and introduce them. How the key factors of TQM can improve a management system in the work units of organizations, and evaluate their performance. Therefore, first, by searching in various researches and models of performance management and excellence, the relevant criteria were reviewed and identified, and through a Delphi panel, the most important ones in the excellence of the work unit were determined several times by consulting experts. Then using the concepts of quality management, production management, process and project management, risk management, etc. in models such as EFQM Excellence Model, ISO 9001, Lean Production, Integration Capability Evolution Model, etc. to identify the following The criteria of each of them were discussed through the same Delphi panel, and finally we presented the main criteria of the conceptual model of excellence of work units. This article seeks to bridge the gap in research on performance management of work units and to help workforce leaders discover the variables that can improve the results of customer satisfaction and stakeholders of a work unit.

Abstract In helicopter design, determining the geometric shape of the fuselage is one of the main and primary issues that affect the performance characteristics of the helicopter. The aerodynamic coefficients of the helicopter fuselage are the main criteria for determining the quality and appropriateness of the geometric shape of the helicopter fuselage. Optimal design of helicopter body geometry is a complex activity and it is necessary to determine the effects of different parameters of helicopter geometry on aerodynamic coefficients. In this paper, design of computer experiments based on simulation of computational fluid dynamics to study the effects of the main parameters of the helicopter body geometry, such as ratio of largest helicopter body width to helicopter length, ratio of largest helicopter body height to helicopter length and nose to radius of curvature radius ratio The fuselage is based on the aerodynamic coefficients of drag, lift and torsional torque. The experiments are based on Taguchi's orthogonal array L25 (53). To determine the relationship between aerodynamic coefficients and parameters of the geometric shape of the helicopter fuselage and the importance of each parameter in aerodynamic coefficients, three-dimensional procedure diagrams, signal to noise ratios, mean of main effects, response procedure methodology and analysis of variance were used. Also, mathematical models were developed to estimate the aerodynamic coefficients of drag, lift and torsional torque through the response procedure methodology. The results at 95% confidence level show that the most effective parameter in the value of the helicopter body drag coefficient is the ratio of the largest height of the helicopter body to the length of the helicopter and in the lift and torsional torque parameters is the ratio of the largest width of the helicopter to the length of the helicopter.

Abstract The measurement process is usually accompanied by error. Measurement error creates a discrepancy between the true value and the observed value of a quality characteristic, affecting the performance of control charts and reducing their ability to detect process changes. In some processes, a quality characteristic is expressed as a function, which is referred to as a profile. Over the past decade, profiles and methods for monitoring them have attracted considerable attention from statistical quality control researchers. Although the impact of measurement error on various control charts and their parameters has been investigated, there is limited information regarding its effect on profiles and their monitoring methods. In this study, the effect of measurement error on the response variable of linear profiles in Phase II is examined. Simulation results indicate that measurement error also affects the performance of profile monitoring methods, reducing the power of techniques such as EWMA-R and EWMA-3 in detecting process changes. Furthermore, this study proposes a new approach for selecting an appropriate measuring device based on profile monitoring methods in the presence of measurement error.

Abstract In image monitoring, the information contained in an image is evaluated using control charts. A spatial control chart is a type of control chart in which the horizontal axis represents the position within the image. These charts are used to detect abnormal points in an image. Thermovision is a branch of machine vision that deals with the analysis of infrared images. Although infrared cameras have long been used in preventive maintenance to identify faulty equipment, overloads, and loose connections, the images captured by these cameras are usually analyzed only through empirical methods, and the few quantitative studies conducted in this area have not utilized control charts. In identifying defects in power distribution panels, several challenges must be considered, including the variety of equipment used in electrical panels, the lack of sufficient data to train pattern recognition models, autocorrelation, and the complex behavior of heat transfer by radiation, convection, and conduction. The insufficient data for training pattern recognition models such as neural networks makes spatial control charts relatively more advantageous than these methods. In this study, a combination of spatial control charts and robust regression is employed to detect defects in power distribution panels, and the detection capabilities of various control charts for identifying these defects are compared.

Abstract Workforce health is one of the most important fundamental prerequisites for productivity and plays a crucial role in achieving sustainable socio-economic development. Therefore, preventing accidents in work environments, as a public necessity, has always attracted the attention of specialists. Given the key role of unsafe behaviors in the occurrence of accidents, some researchers have focused on monitoring unsafe behaviors using statistical process control (SPC) charts. However, human behavior is influenced by various factors such as environmental conditions and individual characteristics. These factors increase process variance and are often referred to as common causes of variation. In such processes, identifying the most influential factors contributing to variance can significantly improve process performance. Nevertheless, such sources of variability have not been adequately considered in previous related studies. The main objective of this paper is to model and monitor different levels contributing to variance in individuals’ unsafe behaviors. The proposed model was implemented in a manufacturing company. After determining the variance associated with each factor, the variability of each component was analyzed separately. The proposed approach, which demonstrates a high capability in reducing unsafe behaviors, can be used as an effective tool for safety management in organizations.

Abstract The importance of software is increasing day by day, and with this growing importance, continuous efforts are being made to develop technologies that lead to the creation of high-quality software. Software metrics are essential tools for project and quality management. In addition to selecting appropriate metrics for monitoring, detecting meaningful behaviors and changes or deviations in the process, analyzing them, and determining whether process shifts are statistically significant are also crucial.
Since statistical quality control is one of the well-established approaches for addressing these issues, this paper aims, for the first time, to identify and categorize all techniques used in the existing literature related to Statistical Process Control (SPC) in software processes. This classification helps researchers recognize practical topics and research directions and supports them in conducting useful and statistically sound studies based on the compiled material.