Journal of Quality Engineering and Management

Abstract There are several ways to increase the competitiveness of organizations. One of the best solutions offered is to improve productivity and efficiency. Data Analysis (DEA), which is a mathematical method and one of the best non-parametric methods, measures the performance of organizations based on input and output variables. Units whose efficiency score equals one are efficient. Efficient units are also ranked using the Anderson-Peterson (AP) method. In this research, a new development method for evaluating and ranking organizations based on performance scores is presented. The case study is the evaluation of the performance of cement companies listed on the stock exchange, which were ranked using the collective model and Anderson-Peterson. Also, the rank of companies was calculated using the new development model and TOPSIS model and compared with each other. The results showed that the ranking of companies using the new development model (N-DEA) is a good solution for calculating the efficiency and ranking of decision-making units.

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 In recent years, due to increasing environmental concerns, government regulations and natural resource constraints, and the impact of green laws, the closed-loop supply chain has attracted increasing attention. Since the supplier has an important role in the supply chain, if faced with risk and disruption, it will have detrimental and important effects on the supply chain, so it seems necessary to study these conditions. Therefore, in this paper, the issue of closed-loop supply chain network design in supply risk conditions is investigated. In addition to disruption of supply, factors such as the use of excess inventory as well as contracts with reliable suppliers in periods that we have not disrupted are considered flexibility strategies in this article. The goal is to minimize chain costs with respect to location decisions, flow between levels, and lost sales. Disruption in suppliers is considered in different scenarios and in detail. The problem is modeled using mixed integer programming and a possible two-step approach is used to consider the uncertainties in the proposed model. At the end, sensitivity analysis is performed on the proposed model and suggestions are provided for using this model in the real world.

Abstract In order to improve productivity, Article 5 of the Sixth Development Plan Law mandates the implementation of the productivity management cycle, which states that "executive bodies and the armed forces are obliged to focus on productivity growth in the economy, while implementing the productivity management cycle in the complex." "Provide
the necessary arrangements for the operation of this cycle in the units under its auspices in
coordination with the National Productivity Organization of Iran and submit its annual report to the National Productivity Organization." It is also stated in the program that from the projected 8% economic growth, 2.8%, ie equivalent to 35% growth, should be obtained from the total factor productivity.
There are several models for measuring productivity, among which the model with financial ratios approach has been used in this paper. There are also various methods for measuring productivity. In this paper, the value-added method is used to calculate partial and total productivity indices in Method Company. Two financial statements, balance sheet and profit and loss statement in the period of 1391 to 1395 as input data as well as standard worksheets of the Productivity Center of Iran to measure productivity indicators are entered into a software designed to output Those productivity ratios and related graphs are similar in the method company and in the industry. Multiple regression was used to select the appropriate approach to improve productivity and show the effect of independent variables (partial productivity indices) on the dependent variable (total productivity), followed by material productivity as the first priority and productivity. Manpower, energy and capital were identified as the next priorities for improvement in Method Company.

Abstract ehavior is a function of the failure rate of some mechanical systems. The conventional Weibull model is not able to fully model the lifespan of such systems with the ohmic refractive index function. In this paper, a new generalized Weibull distribution is used to model the failure rate functions with vanity-shaped behavior. This model is evaluated on three datasets. In these three datasets, in order to reduce the execution time of the lifetime test, accelerator and censored type one tests have been used. The model parameters are also estimated based on the maximum likelihood method. The Akaike indices, the logarithm of the probability function, and the Bayesian information criterion are obtained, indicating the efficiency of this model for the data obtained from performing the lifetime tests. Therefore, the predicted average lifespan has good validity.

Abstract The main purpose of this study is to investigate the moderating role of environmental uncertainty in the relationships of ISO 9001, product innovation and financial performance in manufacturing organizations in Isfahan province. The statistical population of the present study is the production organizations of Isfahan province that have ISO 9001 certification. From 150 organizations identified with this feature, data were collected from 90 organizations in the form of a questionnaire. Data analysis was performed using the second generation of structural equations, PLS. The results of testing the hypotheses indicate a positive and significant effect of ISO 9001 on product innovation and financial performance. The results also demonstrated the moderating role of environmental uncertainty in the relationship between ISO 9001 and product innovation as well as ISO 9001 and financial performance. It was also found that product innovation improves the financial performance of organizations.

Abstract  Value engineering is an organized effort that aims to review and analyze all the activities of a project from the formation of initial thinking to the stage of design and implementation and then commissioning and operation and as one of the most efficient and important economic methods in the field of engineering activities. Known. In the meantime, dam projects due to special complexities of design and implementation, high volume of investment, high volume of resources and the importance of time and cost can have a high potential for the use of value engineering studies. The purpose of this article is to implement value engineering in Ayoshan earthen dam project with the event to the resistance economy. Engineering studies of the value of Ayoshan earthen dam were carried out during construction and in order to reduce the volume of the dam body, reduce the embankment of the left backpack of the dam body, optimize the overflow plan, remove the valve crane, optimize the transmission line, reduce the length of the overflow handles and optimize the structures. Ultimately, it saved 39 billion rials and also reduced the project implementation time. 

Abstract The main purpose of this study is to identify the causes of vibration and detectable defects of bearings through sonometry using a multilayer neural network. Neural network is an intelligent method and due to its main properties, ie its high ability to estimate nonlinear functions and adaptive learning, it has been used to troubleshoot mechanical vibrations of machines, ie bearing acoustics and their frequency analysis. To collect the data, a type of healthy ball bearing cone bearing and a similar bearing with defective bullets were used and tested in desktop drills and radial-based drills in 5 different rounds. In this study, according to the network with 10 hidden layers, the signal frequency is considered as the input of the multilayer neural network and finally the bearing defects and its probable cause are determined and corrective measures are proposed.

Abstract In the past years, researchers considered the proceeds from selling items or services as the most important source of corporate profits, because there was not much competition among companies. Nowadays customers are the most important source of revenue in the business institutions and service companies. Thereupon, customer satisfaction must be plan by company managers in order to preserve current customer and develop new customer in today's competitive conditions. However forecasting the future manner of customer can be useful to allocate budget and limited resource for preservation of the most profitable customers that will do a great help to the managers in order to gain market and increase profitability. In this paper, we present the approach to determinate current customer lifetime value and introduce the developed model to predict the future of customer lifetime value. At the first, the current lifetime value of the customers is determined based on developed RFM and using hierarchy weight method. Then in order to model the downfall probability of customers based on the geometric probability distribution for waiting time, customers must be group based on their characteristics by clustering approach. In this research, it is compared some clustering criteria for determining the best number of clusters. We are used some technical instruments such as Rapid Miner software for data preprocessing and also such as IBM SPSS and expert Choice for clustering analysis and compared theirs abilities. After that, we are modelled customer behavior via Markov chain procedure. Then customer lifetime value estimated for the future customers. The power of this research is the usage of developed RFM in order to weight customers before grouping. Because of this, the optimum number of clusters can be carefully determined. In order to demonstrate the applicability of this approach, the research used on the insurance company employed as the case study.

Abstract The purpose of this study is to help buyers of liquefied natural gas to select different contracts and the level of purchase in different time periods. Some of these contracts have a general discount and some have a promotion. Important factors in contracts are evaporation rate, quality and operating costs. Using Linamp technique, the weight and the best level of each of the above factors are determined. Then, with a mathematical model of mixed integer, the contract selection, the optimal purchase amount of each contract and the type of discount used in each period are determined by considering the purchase amount from the current market by the buyer. The numerical model is based on real data and the mathematical model is solved based on Gomez software. The results show that out of 12 contracts offered to the buyer, only 5 contracts have been selected, of which 2 contracts have used the development discount and 3 contracts have used the general discount.

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.

Abstract  Typically, in order to evaluate the performance of control charts in the healthcare, the parameters of the control chart are assumed to be known; although usually in practice, these parameters are unknown, and the process parameters should be estimated in Phase I for process monitoring. When the estimated parameters are used instead of their known values, the performance of the control chart is affected. In this paper, first, a risk-adjusted Bernoulli EWMA control chart is proposed. Then, the effect of parameter estimation on in-control performance and out-of-control performance of the proposed control chart is examined. After that, the methods of increasing sample sizes as well as modifying the control limits are used to reduce this effect. The results of simulation studies are reported in terms of average run length, standard deviation of run length and coefficient of variation of run length criteria. The simulation results confirm the reduction of the effect of the parameters estimation by increasing the sample size and correcting the control limits. 

Abstract  The issue studied in this paper, considering redundancy allocation and buffer allocation problems simultaneously in a series-parallel production system. The purpose of this research is to improve the availability, total system costs and buffer capacity through determining the optimal buffers size between work stations, selecting high reliability machines and assigning them to work stations, and developing a proper maintenance and repair plan. In this paper, the preventive and emergency repairs to machines are allowed and their cost is considered in the cost function. Furthermore, it is assumed that machine failure rates are random and follows a distribution function such as Weibul. Given these assumptions, it is very difficult to obtain the availability and cost functions via mathematical relations, explicitly. Thus, a hybrid simulation, design of experiments, and neural network approach are applied to estimate the availability and cost functions. In order to analyze the proposed model, a numerical example was used
 and based on the proposed methodology, was analyzed and evaluated. The model related to the problem was coded and solved by the NSGA-II algorithm and the Pareto set of answers was obtained. The results of the research indicated the validity of the proposed methodology for the problem under study. 

Abstract  Control charts are the most popular statistical process control tools for quickly discovering process changes. Among the univariate control charts, the 𝑋 ̅ control chart is more popular. In the economic and the economic-statistical design of control charts, constant and known values are often assumed for input parameters (cost and process parameters). In the real world, these parameters are not fully known and are unknown. The purpose of this paper is to present a simple model for the design of economic and economic-statistical robustness control charts using the Lorenzen and Vance cost model under multiple scenarios and then compare it with other robust economic and economic-statistical designs. The optimal values of the parameters are obtained by genetic algorithm. Comparison economic, robust economic, and robust economic-statistical designs shows that a weighted economic-statistical robustness design performs better than other robust designs. The proposed design is economically weaker, but its statistical performance is better than other robust designs. In addition, it is much easier to use in practice than other methods. 
 
 

Abstract Supply chain quality management as a systematic approach is defined to improve the performance of organizations by developing the opportunities created by the downstream and upstream communication with suppliers and customers in the organization. Today, companies are compelled to upgrade their product quality in order to establish extensive cooperation with other companies involved in the supply chain. The supply chain quality management provides the necessary conditions for establishing an effective cooperation in the field of supply chain. This article focuses on the critical success factors (CSFs) of supply chain quality management and performance measurement in organizations. For this purpose, first by surveying the literature the key factors were identified; later, seven key factors and 40 sub-factors were modified and verified by interviewing chain management executives and experts. Consequently, in the present study, seven key factors and 40 sub-factors for evaluating supply chain quality management are provided. In this study, in consultation with 30 experts and professors in the field of supply chain a questionnaire was prepared and its reliability was assessed. Further, based on paired comparisons and hierarchical analysis process the prioritization of indices was performed using Expert Choice software and, finally, the status of the company was examined. According to the results, the position of the company with regard to SCQM is not favorable, and more attention should be paid to it. The seven CSFs found in this paper demonstrate that the companies involved in the supply chain of a product should focus on seven domains for the implementation of SCQM. Considering the existing correlation between these domains, they should develop these seven domains simultaneously and with the help of each other. The 40 identified sub-criteria, also known as improvement points or critical points, are considered to be the axis of coordination of chain members in this field. 

  

Abstract The purpose of this paper is to design a multi-objective mathematical programming model for scheduling multifunctional machines in a production cell. For this purpose, a multiobjective invasive weed algorithm was proposed and its solution results were compared with multi-objective and genetic particle swarm algorithms. Algorithm parameters were adjusted according to Taguchi method. The innovation of this article, on the one hand, is in implementing the idea of machine processing speed in the production of parts with different qualities. In other words, to ensure quality, processing speed and loading rate are adjusted in the machine, and on the other hand, a multi-objective algorithm with a new chromosome structure was designed to optimize the model. To analyze the performance of solution algorithms, thirty sample problems with different dimensions were designed and performed ten times each. The analysis of the results showed that the multi-objective invasive weed-based algorithm was able to solve and answer problems more than other algorithms. 
 
 

Abstract  Today, with the planning of a sustainable supply chain, in addition to achieving economic goals, it can satisfy the social and environmental objectives and considerations, which result in a competitive advantage and increase chain power. However, the effects of implementing the principles of sustainability on the resilience of a supply chain in various disruptions have not yet been deeply studied by the researchers. The resilience supply chain, with the benefit of a resilient supply portfolio, can reduce the risk and vulnerability of supply chains to the extent possible in the face of disturbances such as supply disruptions. In this research, modeling and problem solving of a sustainable resilience planning problem of a four-level supply chain network are discussed. For this purpose, a multi-objective optimization model is developed for this problem. The objectives of the proposed model include minimizing cost, maximization of social and environmental outcomes of the suppliers, as well as minimizing delays in the delivery of products. Two methods of Augmented Epsilon constraint and Lp metric are used for balancing goals. Finally, in the final section of the study, a numerical study is considered. Finally, in the final section of the study, the numerical study is considered. The outputs of the model and the sensitivity analysis indicated that the model was efficient. 
 
 
 

Abstract  In previous studies, in the discussion of maintenance and repair systems, the evaluation criteria, their classification and the use of different techniques for evaluation have been addressed. But the main issue of this research is to identify the metrics of the system's evaluation and determine their relationship with the processes and goals of the system, to determine the subsystems of the system, identify their relationships and their effects on each other, and provide scenarios that critical paths in the system and the conditions Affecting this Directions are specified.The present study is a qualitative approach in which the theory of data and fuzzy perceptual mapping is used. Using this theory, maintenance subsystems were identified and designed with four main categories: inspection, maintenance and maintenance, chronic failure, acute failure and its relationship. Then, for each of the categories, its characteristics and dimensions were expressed and identified using the paradigm pattern in axial coding under their categories and their relationships. These communications were used as inputs to the fuzzy perceptual mapping topic and through FCM apper software the impact of each of the causative conditions, mediators, strategies and outcomes on each other and different methods of achieving the outcome in each of the inspection, maintenance and maintenance categories, Chronic and acute failure was investigated and presented in the scenario. 

Abstract Nowadays, in line with the rapid growth of image and video-based inspection technologies such as machine vision systems, applications of image-based statistical process control are found in a wide variety of industries and processes. Considering the spatio-temporal variation of the observations in an image-driven process monitoring, the purpose of this study is to use multivariate statistical process control methods in order to evaluate and analyze the quality of samples from a dairy production process. In this research, the color content of each pixel is identified in the standard RGB format, and then the color conversion is performed to the new three-dimesnional L*a*b* color space. After estimation of the spatio-temporal autoregressive (STAR) model, multivariate control charts are employed to monitor both mean and vrainace of the estimates. Change point analysis using likelihood ratio statistic and decomposion of control statistic have improved the interpretability of the out-of-control signals on the control chart. The results of a case study related to the dairy industry reveals the capability of the propsed method in recognition of out-of-control conditions using image processing and analysis of the product surface color. 

Abstract In this study, a new bi-objective model along with a novel solving method are provided to address the non-exponential RAP in series-parallel systems with repairable components. The proposed method is based on optimization via simulation approach and artificial neural network technique. In addition, to be more realistic, discounts strategies for purchasing the components are employed during modeling. The main objective of the model is to maximize mean time to the first failure (MTTFF) of the system via allocating the best redundant components for each subsystem. Since, the components’ failure rate has non-exponential distribution, the simulation technique and ANN are applied to find the MTTFF. To solve the problem, some meta-heuristic algorithms integrated with the simulation method. Several numerical examples are carried out to test the proposed approach and as the results show, the proposed approach is much more real than previous ones and also the near optimum solutions are achieved. 
 

Abstract Many industries are not aware of the after-sales service features and their impact on customer satisfaction. Disappointed customers have become competitors in order to better compete after-sales service. Due to the specific conditions of the liquefied petroleum gas (LPG) industry (harvesting, delivery, transportation, loading, standardization, etc.), researchers have different opinions in the field of customer service. In this regard, the present study was written with the aim of designing an appropriate after-sales service model in the Iranian liquefied gas industry. The combination of fuzzy Delphi method and structural-interpretive modeling with content approach has been used in the design of this model. Since this method is based on the opinion of experts, the opinions of managers and experts involved in the field of liquefied gas industry in Iran, which included 10 people, were used. In this study, fuzzy Delphi method was used to screen the indices. Out of 20 identified indices, only 3 indices of de-fuzzy mean were less than 0.7 and 17 main indices were identified in this industry. Then, structural-interpretive modeling (ISM) and MICMAC analysis were used to cluster the identified components. After analyzing the data, the variables were classified into six different levels and plotted according to the ISM graph relationships. After MICMAC analysis, the variables were divided into three groups of independent or key variables, linked and dependent, and no variables were included in the group of autonomous variables. The results of research in determining the relationships between variables and the type of variables can help to better understand the issue and make appropriate decisions in identifying after-sales service indicators. Attention to the indicators of reliability, reactivity, quality of interactions, agencies and visits according to the output of the structural model show the impact of these indicators in the field of services and in the liquefied gas industry. 

Abstract  The present research is about the location of preventive facilities. Effective preventive health care services play an important role in reducing medical costs and mortality in all human societies, and the level of customer access to these services can be considered as a measure of their effectiveness and effectiveness. In order to solve the waiting and queuing problem, a biobjective mathematical and nonlinear problem is presented to address the issue of reducing the maximum waiting time for the visitors with the aim of increasing the maximum coverage. This research method is based on modeling. Data analysis was performed using Matlab software, and the answers obtained from the meta-heuristic algorithms were compared in the Minitab software. From the results of this study, it is possible to increase coverage by preventive facilities and increase waiting time. Another result of this study is the comparison of the effectiveness of each of the metaheuristic NSGAII and MOIWO with the defined index.