Journal of Quality Engineering and Management

Abstract Couplings are widely used in the industry and this equipment are always subject to defects and failures due to continuous rotation. Vibration analysis is a suitable technique for failure analysis and failure detection of rotating equipment. The purpose of this research is to analyze the failures that occurred in a coupling, whose data was collected in normal state and three failure states with four sensors connected to the coupling. For this purpose, two different types of feature extraction have been used, and seven machine learning algorithms and one deep learning algorithm have been used to classify situations. In this research, the performance of each of the implemented algorithms and the importance of extracted features have been investigated, and the role of sensors and their importance to reduce the number of sensors have been investigated. From the results of this research, we can point out the high importance of the features of the frequency domain in the accuracy of the implemented models, as well as the high efficiency of two sensors for classification.

Abstract Knowing the real costs of a project, correctly estimating them and identifying the risks involved in resource allocation for projects such as the construction of a petrochemical unit whose resources are expensive or difficult to access, is of particular importance. By using costing methods in conditions of risk and uncertainty, more reliable cost information can be obtained. By examining past studies and researches in the field of costing, it was found that their focus was mostly on carrying out activities, and less attention was paid to the risk factor. In this article, the use of the ABC approach, which focuses on identifying activities and cost centers, has been discussed in the form of a mathematical model whose purpose is to minimize the risk of resource allocation to activity centers based on the desired limitations in costs and resources. Due to the fact that the numerical values of the parameters in the general model, such as cost and time, have uncertainty, risk-based resource allocation modeling has been considered. To test the proposed model, the main activities of the construction and installation stage of a petrochemical unit were considered, and after collecting the necessary data, the steps of the compiled model for resource allocation and the steps of the activity-based costing approach have been implemented. The results show that there is a difference between the costs calculated based on the allocation of resources of the proposed model for the activity centers and the costs estimated according to the past data.

Abstract As time goes on and crises increase in societies, organizations are increasingly exposed to disruption. These crises can be of natural (such as earthquakes, floods, and fires) or human (such as terrorist attacks, infectious diseases, and intentional or inadvertent employee errors). Therefore, organizations need to be resilient to protect themselves from harmful consequences. The basic aspect of resilience involves the ability of an element to return to normal after disruption and resource allocation. Obviously, in any organization, the primary goal is to allocate the least resources to recover operations and to bring activities back to the tolerance threshold so that destructive events do not stop vital activities. In this paper, a quantitative model for resource allocation is presented, which minimizes the lack of resilience. The problem has a basic assumption, that there is a shortage of resources in at least one of the available resources due to excessive demand. After solving the model by numerical experiment, the results of the model were described and it was found that destructive events were retrieved before the tolerance threshold.

Abstract Process analysis is closely related to process optimization and in the optimization, the discussion of resources plays a major role. Since the optimal set of resources, especially in the event of unexpected events will have variable effects on risk, process performance and efficiency can be similar to the optimal stock portfolio selection model. The purpose of this paper is to provide a mathematical model for allocating human resources using the Markowitz model to the days of the week based on skills and costs, which the objective function minimizes the risk and maximizes the efficiency of resources. The proposed model includes a combination of risk and return assessments to find the best resource portfolio in critical situations. The study also used the Epsilon constraint method. The innovations of this research is the application of Markowitz model to optimize resource allocation and risk-based allocation of resources in the process. The proposed model has been used in a case study of a urology subspecialty kidney center. Numerical results show that using the designed model, resources can be allocated in such a way that it has optimal returns and risk, in order to produce the maximum amount of output in critical situations.
 

Abstract  In recent years, many efforts have been made to achieve comprehensive criteria and models for evaluating companies. In this article, the aim is to obtain the efficiency of petrochemical companies based on human resource functions, operations and sales. The efficiency model can show better performance for calculating efficiency by considering human resource functions, operations and sales. 14 active petrochemicals are considered in the stock exchange and the concept model is based on three units of human resources, operations unit and sales unit. Data extracted from Codal site. The efficiency ranking of petrochemical industries is calculated with the same data by three methods. A network model is used to obtain efficiency and the results show the efficiency of petrochemicals 1, 10 and 11 in each model. The implementation of models shows that human resource functions, operations and sales can perform better. Also, the different results of the three models from each other show the importance of choosing a performance appraisal model for organizations. 
  

Abstract  
The length of waiting time is considered as a key determinant of patient satisfaction level; besides, it has a significant impact on the effectiveness and quality of services which are provided to patients. In addition, Simulation study is also considered as an effective tool for improving patient flow, reducing waiting time and increasing patient satisfaction. Hence, in the present study we made use of simulation to improve the quality of health care in a urology unit which is a part of a kidney center in Tehran. Put differently, the aim of the current study was increasing the efficiency of Extracorporeal Shock Wave Lithotripsy (ESWL) method besides reducing the waiting times and the patient cancellation rates. Therefore, a Discrete-Event Simulation model was developed using iGrafx software, which was later used in conjunction with MATLAB software to form and evaluate the urology unit improvement scenarios in three categories: changing technicians’ presence schedules during different shifts, changing the schedule of patient visits, and examining the factors that reduce the patient cancellation rate. The greatest differences were resulted from the employment of scheduling scenarios of patient visits on waiting time and duration of stay with averages of 23.33 and 22.81 minutes, respectively. In addition, the results of examining the factors that reduce patient cancellation rate demonstrated that the number of cancellations were decreased with an average of 1.44 cases per day. In each category of proposed scenarios, applying changes based on the selected scenario of that category led to significant improvements in performance criteria of the urology unit. It is also worth mentioning that the impact of scheduling scenarios of patient visits was much higher than other scenarios. 

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 In today's competitive market, many products are sold under the basic warranty, and in order to increase profit margins and customer satisfaction after the end of the basic warranty, manufacturers offer warranty extensions to customers at a specific price and time. In this research, the aim is to maximize the producer profit by determining the optimal values of product price, length of basic warranty period, length of warranty renewal, repair level in incomplete repair and amount of spare parts (for demand of products under basic warranty, warranty extension and out of warranty). . In order to better model the real situation, it is assumed that the product can be repaired with three types of minimum, incomplete and complete repairs at the time of failure, and the percentage of products that are repaired each time is also considered as a decision variable. have became. The product reliability function is modeled at the time of incomplete repair with the Kijima virtual life model approach. The problem-solving approach is based on the simulation-based optimization approach in three stages. In the first stage, decision variables such as product price, basic warranty period, warranty renewal period, warranty renewal price, repair level and the probability of what kind of repair each product It is determined by a meta-heuristic algorithm. Then, using Monte Carlo simulation, the number of products that have purchased the warranty extension and the number of product failures is calculated, and finally, the production of spare parts is optimized using a dynamic programming algorithm. This model has also been analyzed for LG vacuum cleaner product and Goldiran after-sales service. 

Abstract Today, manufacturers use warranty as an important advertising tool to increase market share. Offering the product to the market with a longer warranty, although attracting more customers, increases the manufacturer's costs. In the real world, manufacturers can provide buyers with an option to renew their warranty for a specified period of time after the end of the basic warranty period. Thus, products that do not renew their warranty as products out of warranty are the main source of profitability of the manufacturer from the sale of spare parts. In this research, a new model is presented that helps the manufacturer to increase profits and considering the level of customer satisfaction and the effect of selling spare parts to products out of warranty, such as pricing of the main product, length of basic warranty period, length of warranty renewal period. Optimize the price of the warranty extension. The developed particle swarm algorithm and the sports league algorithm have been used to solve the model. Due to the fact that Goldiran Company in Iran, as the after-sales service representative of LG, has provided the possibility of extending the basic warranty for products under this brand, the proposed model has been solved with data related to the LED product. The results show that Goldiran Company can help increase the producer profit margin by changing the values of the basic warranty period and extending the warranty according to the product life cycle and planning time, while now the company has fixed the warranty period and extended warranty period for all its products. is considered.

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.