جستجوی مقالات مرتبط با کلیدواژه "quality control" در نشریات گروه "مدیریت"

In light of recent advancements in the modern world, multivariate-multistage quality control patterns are increasingly recognized as vital and indispensable in manufacturing industries. This study delves into the significance and necessity of multivariate-multistage quality control in manufacturing, specifically focusing on motor oil production. As a foundational factor, motor oil quality considerably influences engine performance, lifespan, customer satisfaction, and market positioning.

This research employs deep learning algorithms for monitoring and fault detection in quality components. The primary rationale for opting for deep learning algorithms over conventional statistical methods is the non-normal distribution of data and the large sample sizes, which can lead to inaccurate estimations and unstable analyses. Conversely, the unique capabilities of deep learning algorithms in handling complex data and extracting meaningful features from extensive motor oil production data justify their selection. To bolster accuracy and effective quality control, a combination of deep learning algorithms is utilized, including Long Short-Term Memory (LSTM) networks, Convolutional Neural Networks (CNN), and hybrid models such as LSTM-CNN, as well as Residual Networks (ResNet) with Dense Networks (DenseNet). The LSTM-CNN algorithm is applied to control numerical quality variables and identify temporal and sequential patterns in the data. Meanwhile, ResNet-DenseNet manages and analyzes visual data with non-uniform and intricate distributions.

By integrating LSTM networks, CNNs, and residual connections, these algorithms excel at extracting meaningful features and capturing complex relationships within the data. This enhances performance and efficiency in quality control processes and facilitates intelligent decision-making. Such an approach is adept at uncovering latent patterns and intricate relationships between variables and quality attributes, enhancing quality control procedures and intelligent decision-making. The amalgamation of these algorithmic capabilities enhances the efficacy of quality control processes, outperforming single-algorithm approaches. Additionally, the Bee Colony Clonal Algorithm (BCC) is employed to fine-tune the parameters of the LSTM-CNN and ResNet-DenseNet algorithms. This hybrid approach harnesses the Artificial Bee Colony (ABC) and Genetic Algorithm (GA) strengths, markedly improving the performance of deep learning algorithms in quality control and reducing the time required to achieve desired outcomes. To illustrate the practical applicability of the proposed algorithms, a case study in the motor oil production industry is examined. The proposed LSTM-CNN hybrid algorithm in fault detection demonstrated superior results compared to standalone CNN and LSTM algorithms, achieving performance improvements of approximately 15% and 8%, respectively. Furthermore, the proposed ResNet-DenseNet hybrid algorithm exhibited higher accuracy in visual components, enhancing performance by approximately 10% and 15% compared to ResNet and DenseNet algorithms, respectively.

From both academic and practical standpoints, this research scrutinizes deep learning algorithms' influence on enhancing motor oil quality and efficiency. Advanced data analysis methods, particularly hybrid deep learning algorithms, are employed to identify quality patterns in production data.

The main goal is to propose a model for quality control in the defense industry, utilizing image processing and fuzzy transform. Emphasis is on selecting the optimal generalized fuzzy transform section for image compression to enhance the performance of defense and combat weapons.

The methodology employs modern image processing and fuzzy transform techniques for statistical quality control. High-volume data analysis occurs in production lines, managing processes for defense and combat weapon products like glass and metals. MATLAB is the implementation platform, emphasizing the optimal selection of the generalized fuzzy transform section for image compression and processing.

MATLAB validation confirms the success of our model in quality control for defense systems. Comparative studies show the triangular fuzzy section model excels, especially in defect detection post-illumination changes, surpassing Kusha et al. in most cases.

In conclusion, our study emphasizes the vital role of image processing and fuzzy transform techniques in defense. The developed model successfully achieves quality control goals, optimizes processes, and enhances defense and combat weapon quality. This reflects a growing industry trend, with an increasing adoption of these methods to meet goals and address challenges.

Today, most industries and factories in the country use statistical quality control tools to improve product quality, but due to the high volume of data, now there is a need for a more powerful tool that can control statistical quality control processes, given the extent Data Mining Algorithms and Its Ability to Discover Rules In this research, data mining tools have been used to improve the quality control process and increase it. The method is that first the failure database is formed and after collecting quality control data, the accuracy of predicting the quality of parts is determined using different decision tree algorithms and in the next step using Modeling, Coverage Analysis, Data Each of the rules is evaluated, and finally the workstations are evaluated using the rules that apply to each workstation. Accordingly, in this study, the statistical population of all Tiba surge arresters in 1398. The attributes consist of 9 workstations. Based on the results, the best algorithm in predicting C5 failure is and the most important attributes selected by it are determined as the most important attributes, which are: Cooling quality, hole quality and cutting quality. Also, the evaluation of the rules has been done using the model of cover analysis, data and the most important rules have been extracted. Finally, based on solving the model, the devices that will be in the corrective priority for the current year are: Rowling , Solder and cutting

Managers, in addition to providing their organization's interests and rights,  They should consider the welfare, comfort, needs and interests of the people of community as a moral issue.In the other hand, decisions and management behaviors should not lead to damage, damage or harm to society and its people. The purpose of this study was to investigate the role of obtaining international certificates on the risk of financial crisis and the performance of Tehran Stock Exchange's affiliated companies with an emphasis on the role of political communication. On the one hand, according to the innovation of this research in Iran, there has been no research on the financial analysis of obtaining international certificates of companies. For this purpose, 1155 observations of companies listed on the Tehran Stock Exchange for a period of ten years were examined. In order to analyze the data, a significant test was used in multiple regression software using Eviews Software. The results of this study showed that there is a relationship between obtaining international certification of the company and stock returns in which the relationship with the company's corporate managers is changing, but obtaining an international certificate for the corporate financial crisis does not contain information content.

Nowadays, the level of readiness of specialized equipment and items in military-police enforcement organizations is very important because increasing the life and quality of the items in question will save a lot in the country. The main purpose of this study was to investigate the complications in the quality control processes of the specialized items of the organization under study; The sub-objectives were to investigate the complications of quality control processes in the design axis, to investigate the complications of quality control processes in the compliance axis, to investigate the complications of quality control processes in the performance axis, and to investigate the damages of quality control processes in the service quality axis. This research is of descriptive-analytical type and is in the category of applied research and has been done by survey method. A researcher-made questionnaire was used to collect field information. The statistical population of the study was 50 managers, commanders and senior experts of one of the military-police enforcement organizations, from all of whom information was collected. The results showed that out of 43 items examined in four axes (design, adaptation, performance and service), 14 of them are damaged.

Corporate governance explains the relationships between company managers, shareholders and other stakeholders and outlines the survival of the organization in a broad perspective and its establishment leads to optimal resource allocation, quality and transparency, information disclosure and accountability, protection of stakeholder rights and thus It leads to economic growth and development. On the one hand, the risk-taking of organizationsand companies has played a significant role in determining more benefits and on the other hand, expanding market share. With components such as market forecast, competition level forecast, profit quality forecast and growth opportunity forecast, shows howmuch the manager accepts investments for a forecasted profit level.. In this paper, the consequences and effects of corporate governance on risk-taking in order to increase market share with respect to inspections and quality control have been studied. The results of the study show that there is a significant relationship between corporate governance and risk-taking, inspection and quality control performance, maintaining the interests of stakeholders, increasing market share and increasing corporate governance with the use of SPSS software and regression test. Variables increase. In order to prepare this article, the library method and documentary study and field research have been used.

Quality control in High-Tech industries is one of the most sensitive types of quality control in manufacturing industries. Turbine industries are considered as High-Tech industries given their diversity, sophisticated technologies, need for complicated manufacturing machineries and equipment, expensive and special consumables, nead for experienced engineers and experts, and need for new technical knowledge. Current research aims at identifying factors affecting quality control of High-Tech products in turbine industry in order to design a quality control model. Research statistical population included senior and middle managers, engineering and technical experts of turbine industry quality and production, and specifically, Oil Turbocompresor Engineering Company (OTEC). Confirmatory factor analysis and Structural Equation Modeling (SEM) and Smart PLS software were used for validation and fitting indices and research model. Given results obtained in this research, 34 indices were identified as the final indices in the form of 7 factors as factors affecting High-Tech product quality control in turbine industry, and a quality control model was proposed accordingly

Developments of recent decades shows that for reducing the financial and opportunities costs as well as increasing productivity, it is necessary to improve the quality of components and systems in organization. Information systems based on these rules should be considered and for improving their productivity, user’s satisfaction and effectiveness it is necessary to quality aspects of these systems are considered too. In this research a quality assurance system is developed to all parts of an information system from data gathering, data entry to indexing and dissemination of information for assuring of quality are included. This model based on continual improvement approach of Deming cycle will change all of its systems and processes so that each development in the system with considering current standards and quality guidelines are done

Organizational culture is that has attracted the attention of a large number of specialists and interested people to management science because of its publicity، and the term “culture “alone with is synonyms has arrived into management literature in last decades. This topic has attracted such a great attention that has made managers very careful in decision making in all organization fields. On the other hand، because of high cost in organization and allocation of large amount of budget to properties the need for properly use of properties and equipment have been emphasized، and many theories and ideas have aroused in this respect. In Iran no systematic research has been made about the relationship between culture and property maintenance so far. Or at least it has been limited. Therefore we recognized the necessity for an exclusive research in this field. This research has been designed and performed to understand the relationship between cultural characteristic and quality of property maintenance in government agencies. A sample of 220 of the staff of the organization under research participated in the research all of them have been chosen randomly and according to classified sampling method. The research made questionnaire was used the collecting of information which its validity and reliability were proved data acceptable after performance. Statistical data were analyzed by means of descriptive statistical methods and perspective statistical methods In SPSS program research finding show that there is meaningful relationship between current cultural characteristics and the quality of property maintenance i. e. the better cultural characteristics، the better quality of properties maintenance.