Journal of Quality Engineering and Management

Abstract Nowadays, the process of producing most products is such that the products are created in different and interdependent stages. . One of the most widely used and specialized control charts used to monitor multi-stage processes is the selection diagrams of deviant agents. These control charts have been further developed and used for high quality characteristics. In this paper, two control diagrams based on generalized linear patterns are proposed to monitor a two-step process with a two-sentence qualitative characteristic in the second step. In the proposed approach for monitoring binomial variables, a cumulative sum control control diagram and a dual-balance moving average control diagram are designed considering the relationship between qualitative characteristics in two stages. The proposed control diagrams are based on the residual values ​​of the deviation. In order to establish the relationship between the qualitative characteristics of the first and second stages, a new interface function has been used in the framework of the generalized linear pattern. The performance of the proposed control diagrams is evaluated using simulation based on the average sequence length criterion. The results show that the ability to detect cumulative summand control charts and the proposed dual rhythmic moving average is far better than the control charts in the literature.

Abstract The main purpose of this study is to evaluate the performance of the physical asset management system in the South Pars Oil and Gas Complex. In this research, the combined method of balanced scorecard evaluation system and fuzzy hierarchical analysis process model has been used. Evaluation criteria according to the hexagonal system of balanced scorecard include internal processes, financial, organizational stakeholders, learning, employee satisfaction and the organization's environment. The measurement of the effectiveness coefficients of the evaluation criteria has been done through the fuzzy hierarchical analysis process model. Data were collected through interviews with oil industry experts in the field of physical asset management. Using a hexagonal scorecard system increases the likelihood of correct output from the evaluation system. The results show that internal and financial processes with a weight of 29%, organizational environment with a weight of 18%, learning with a weight of 17%, stakeholders of the organization with a weight of 5% and satisfaction with a weight of 2%, respectively, the performance of the physical asset management system in the organization Is. The performance of traditional equipment protection systems is generally measured by key performance indicators such as reliability or accessibility. However, in this study, the performance of physical asset management system is measured by a combination of balanced scorecard evaluation system and fuzzy hierarchical analysis process model, which in its kind can be considered a creativity and innovation in the field of physical asset management.

Abstract Identifying significant changes in key indicators of financial processes is one of the points of interest in recent years and after the financial crisis. Control charts are one of the most powerful tools used in this field. A noteworthy point in the practical use of control charts is the estimation of process parameters based on available data. Despite extensive research into the effect of parameter estimation on the performance of control charts, little research has been done on processes with time-dependent observations. Due to the importance and widespread use of the Auto Regressive Conditional Heteroskedasticity (ARCH) time series model in monitoring financial processes, in this paper, the effect of prototype size for estimating model parameters on the performance of phase 2 control charts is investigated. The performance of each control diagram is evaluated using simulation studies based on AARL and SDARL criteria and the results are described.

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 The main function of a control chart is to help manage the detection of various sources of variability in a production process. Control charts are also widely used in the industry as a tool to monitor a production process to improve product quality. The most common control chart with one characteristic in mind is the control chart. In this paper, we propose and present an economic design model and statistical-economic design in order to optimally design control charts by considering the new generalized two-parameter Weibull distribution as a process failure mechanism. . From the comparison, we conclude that the statistical-economic model is better but more expensive than the economic model in terms of achieving the statistical properties of the desired control chart.

Abstract Productivity and related indicators are very important for organizations because of their direct impact on the performance and efficiency of the organization. Today, companies and organizations attach great importance to the discussion of the environment and the standards in this field to gain a competitive advantage. In the field of environmental environment, the ISO 14001 standard is proposed. In this article, first, each of the concepts of productivity and environment is examined separately, then the dimensions and criteria of each of them are extracted. Accordingly, 20 indicators for productivity and 13 indicators for the environment have been extracted from articles and books. This article has been done in two methods of descriptive and exploratory study. In the descriptive study, the indicators and concepts affecting the two issues of productivity and environment have been extracted separately and the exploratory study has expressed the relationship between the concepts and indicators proposed in the two areas of productivity and biology. Environment, which is taken from the literature review and according to the concepts and issues raised, questionnaires were developed to find a meaningful relationship between the two issues of productivity and environmental life, which were distributed among industry experts and the university. And the results were collected and using t-test at the level of α = 0.05, we were able to extract the relevant indicators and among them, the indicators that have a stronger relationship in different areas were identified.