Journal of Quality Engineering and Management

Abstract Purpose: In today's world, the role of the economy in shaping business models and the power of nations is highly significant. Exports play a vital role in enhancing productivity and economic development, particularly in developing countries. The automotive industry, as a key sector, contributes considerably to this process. This study aims to identify the key influencing variables on non-oil exports and explore how they affect productivity growth and export improvement.
Methodology: This research employs a system dynamics approach to model the interactions among key economic variables. The study utilizes VENSIM software to simulate the system dynamics model of the automotive industry and non-oil exports. Causal loop diagrams and stock and flow diagrams were developed to analyze the relationships.
Findings: The main variables analyzed in this study include exchange rate, inflation, productivity, and competitiveness. The developed model was validated and tested under various scenarios. Results indicate how changes in these variables impact productivity and the performance of non-oil exports in the automotive industry.
Originality/Value: This study offers a dynamic model tailored to the automotive sector in developing economies like Iran, where over-reliance on oil has led to inefficiencies in other export sectors. The model helps policymakers and industry stakeholders understand complex interactions and make informed decisions to boost non-oil exports and overall productivity.

Abstract Nowadays one of most important organizations’ goals is to access compatibility to increase their market share and higher profitability. Therefore, it can be claimed that compatibility is considered as one of the most general organizations’ and industries’ outputs. The purpose of writing the current paper is to represent a model to measure carpet industry compatibility emphasizing quality and innovation. Statistical society in qualitative part includes 14 top managers and 582 employees in quantitative part from which 232 ones were selected as statistical sample. First of all, by the research model was obtained with three main dimensions resources and capabilities, quality and innovation with 30 indices through semi-structured and unstructured interviews with experts and during the coding process. Meanwhile resources and capabilities includes spiritual capital, human capital and technological capabilities, quality dimension includes raw materials, pre-production phase and production phase and finally innovation dimension includes product innovation, process innovation and sale innovation.

Abstract Today, the increasing progress in technology, the expansion and development of human needs for sustainable technologies have caused attention to electric energy to be in the center of attention more than in the past. Therefore, increasing the reliability of electrical systems in the power industry is very important. The purpose of this research is to provide a mathematical model to calculate and increase reliability in the power distribution network. This research is practical in terms of its purpose and results, and in terms of the method and nature of implementation, it is based on operational research that was conducted using mathematical modeling and using Python software based on data from 1398 to 1402. The findings show that parameters such as generators, high pressure and low pressure busbars, 20 kV to 400 V power transformers, communication cables, capacitors, generators and UPS are more important in calculating the reliability of this network. Therefore, according to the purpose and the corresponding limitations, a suitable mathematical model has been presented for each parameter. The results show that after 50 repetitions and simulations, the ultra-emergency line has a higher importance and rank in reliability among the four output feeders. Also, based on the presented model, it has been observed that the entire 20 kV line under investigation has 0.67 degrees of reliability. The results of this research can be considered as a suitable basis for the implementation of research and operational projects in wide radial networks in the electricity industry.

Abstract
 The purpose of this article is to examine the quality of goods in the process of transfer between members of the supply chain. For this purpose, a suitable mathematical model has been designed to manage the supply channel route of the supply chain problem and the problem has been solved using a genetic algorithm. In the present study, real-world conditions such as vehicle traffic constraints as well as product quality are considered by considering returned items, and also the Markov chain is used to investigate the possibility of transfer between members of the supply chain. The innovation of this research is the introduction of the channel selection system for transportation planning in the supply chain. The results show that the method used in this study has a good performance and the optimal way of product flow in a distribution network using genetic algorithm is presented. 

Abstract The purpose and background of this research is to investigate the intensification of changes in demand from the customer to the manufacturer. A beverage factory with two products whose production reaches distributors in different ways was studied. Inventory, communication and participatory models were designed to calculate the whipping effect. Communication and participatory models were also written with the ANFIS MATLAB program to enter information and calculate the whipping effect. For the producer factor, the level of the whip effect has decreased by an average of 22.31%, which is 33.33% for product A and 1.97% for product B. The results shown in the study show an appropriate reduction in the level of the whip effect. For distributors, there is an average decrease of 92.17%. For the producer factor, the level of the whip effect has decreased by an average of 22.31%. 
 

Abstract The purpose of this article is to design a Non-Linear Mixed Integer Multilevel TwoObjective Mathematical Model to minimize the costs and maximize the reliability of blood supply chain. In this research, the reliability is measured according to the conditions and safety of transportation, temperature fluctuations, packaging standards, laboratory equipment and the demand. To test the model, the problem is modeled and solved by different dimensions using real data. In addition, the sensitivity analysis of the outputs is carried out to parameters changes. To solve the proposed mathematical model, Baron Solver of GAMS 24.9 is used. This model determines the product sent from blood center to hospital, the amount of production in blood center, the amount of blood donated from donors, the number of collection centers, the amount of product inventory in each center and hospital to minimize the costs and maximize the reliability. Given the fact that the first objective function is the maximization and the second one the minimization, there is a conflict between these two functions. That is, the costs will be minimized by maximizing the reliability. The model developed in this study determines the variables of decision so that by maximizing the reliability of supply chain, the costs will be well controlled and the waste and lack of blood minimized.  

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 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.