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 Statistical quality control methods are the basis for measuring process performance and productivity. Control charts are one of the most widely used statistical control tools and play an important role in improving the quality of processes and products. The main purpose of their implementation is to identify the deviation (s) and take corrective measures to eliminate the root of the deviation. The technical applications of control charts are to determine the sample size, sampling frequency and control limits, which is called control chart design. In most nP chart design research, only one reason deviation is considered as the cause of the chart getting out of control, while several industry deviations can play a role. For this purpose, in this research, the design and statistical-economic development of nP control diagram, in order to reduce costs and average detection time and increase the power of the diagram by using gray values ​​and considering deviations for various reasons. In this regard, in order to achieve the optimal values ​​of these parameters, a multi-objective problem with three constraints has been defined, in which we have considered each possible combination of parameters as a decision unit. Then, using data envelopment analysis and ranking methods, the most efficient design for the decision maker is determined. In the continuation of the research, sensitivity analysis has been performed on some parameters of the model and the effect of these parameters on the optimal values ​​has been analyzed.

Abstract Quality of service is the distinguishing factor and the most powerful competitive weapon that many service organizations such as hospitals have. The purpose of this study was to rank selected hospitals in Iran in terms of service quality using a combination of SERVQUAL methods and data envelopment analysis. In this study, first, a systematic search in various scientific databases, to find the research conducted to assess the quality of services provided in Iranian hospitals using the SERVQUAL model, which found 22 related studies. Then, with the help of data envelopment analysis method and considering the five dimensions of service quality as its outputs and considering hospitals as decision-making units by DEAP 2.1 software, the scores related to each were calculated. Most of the published researches were related to 2016 in terms of time and related to Tehran province in terms of location. Zabol Shahid Elmi Field Hospital with a score of 1.000 and D Hospital affiliated to Qazvin University of Medical Sciences with a score of 0.364 won the first and last ranks, respectively. The average score of all hospitals was 0.796. Scores calculated by data envelopment analysis showed that there is an average increase of 20.4% in the quality of hospital services. Also, Shahid Elmi Field Hospital in Zabol can be considered a model for other hospitals under study due to its superior ranking.