Industrial management
elham aghazadeh; Akbar Alem Tabriz
Abstract
In today's industrial units, operators monitor equipment performance, and the challenging coordination between units in vast operating environments with high volumes of equipment can lead to irreparable damage. Despite considerable technological advancements in inspection and surveillance, this responsibility ...
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In today's industrial units, operators monitor equipment performance, and the challenging coordination between units in vast operating environments with high volumes of equipment can lead to irreparable damage. Despite considerable technological advancements in inspection and surveillance, this responsibility can be effectively delegated to smart devices and the Internet of Things (IoT). Furthermore, the emergence of "edge computing" technology has prompted researchers to explore edge-based computing designs due to their numerous benefits. This study presents a combined model of IoT and civilian drones for intelligent monitoring of industrial equipment performance, employing an edge computing approach. The model is specifically investigated through a case study involving wind turbines. The model evaluates the performance of drones for intelligent monitoring of wind turbines in three stages: 1) Detection process, 2) UAV computational evacuation process, and 3) UAV local computation process. Given the dual purpose of the final model, which involves a combination of the aforementioned three steps, a genetic method was employed for problem-solving with negligible sorting. The amplified epsilon restriction method, utilizing random numbers, was also considered, but the combination of genetic and negligible sorting methods outperformed it, particularly in large problems where the enhanced epsilon restriction method struggled to provide timely responses due to the inherent complexity of the problem. IntroductionToday, in various industries, the productivity and efficiency of equipment contribute to the advancement of production and the profitability of production units. Beyond repair costs, equipment breakdowns also result in the expense of lost opportunities for the production unit. Without a solution to prevent these costs, bankruptcy for production units becomes a real possibility. Therefore, consideration should be given to a solution for the optimal monitoring of equipment. Clearly, swift action is crucial when any equipment is damaged, and such rapid response is unattainable through human effort alone. Despite significant technological advances in inspection and monitoring, this task can be delegated to smart tools and the Internet of Things (IoT). The IoT is regarded as one of the most crucial factors for the prosperity and progress of today's and future industrial businesses. Modernizing equipment is a priority for today's industries to quickly adapt to the evolving market changes and harness existing technologies. Businesses incorporating IoT into their infrastructure experience substantial growth in areas such as security, productivity, and profitability. As the use of industrial IoT increases, productivity levels in industries are naturally expected to rise. The IoT can accumulate massive amounts of information and data, enabling factories and companies to optimize their systems and equipment without being hindered by technological and economic limitations. However, a challenge arises from the substantial volume of data generated by the IoT, which is sent to cloud computing centers for processing. Centralized (cloud) processing results in high communication delays and lowers the data transfer rate between IoT devices and potential users, creating operational challenges in the network. To address this issue, the concept of edge computing has been proposed. Edge computing allows IoT services to process data near their own data sources and data sinks instead of relying on the cloud environment. This approach leads to reduced communication delays and more efficient utilization of computing, storage, and network resources. It also minimizes execution time and energy consumption, proving to be highly beneficial for IoT applications. Consequently, with the advent of "edge computing" technology, many researchers have embraced edge computing-based designs due to its numerous advantages.Materials and Methods In this research, a combined model of the Internet of Things and civilian drones was presented for the intelligent monitoring of industrial equipment, utilizing an edge computing approach. The model was investigated through a case study involving wind turbines. The performance of UAVs for intelligent monitoring of wind turbines was examined in three stages: 1) Detection process, 2) UAV computational evacuation process, and 3) UAV local computing process. Given the dual purpose of the final model, which involved a combination of the aforementioned three steps, the model was addressed using genetic methods with sparse sorting and the enhanced epsilon constraint method employing random numbers. The genetic method with sparse sorting outperformed the enhanced epsilon limit method, particularly in problems with large dimensions. The complexity of the problem made it challenging for the enhanced epsilon constraint method to provide timely responses in such cases.ResultsThe findings of this research offer valuable insights for the effective and accurate management and monitoring of industrial equipment across various industrial units, aiming to optimize costs, quality, and inspection time. Additionally, this research can provide guidance in considering regulatory restrictions in equipment placement before constructing an industrial unit. During the equipment arrangement phase, the model presented in this research can be utilized for optimal energy consumption and time management. As the combined model of the Internet of Things and civilian drones for intelligent monitoring of industrial equipment is a novel concept in the literature, there exist numerous opportunities for further development in this field. This may include the application of the model in additional case studies, such as enhancing the intelligent monitoring of power supply systems, fire services, etc. Moreover, there is potential for refining the mentioned model under conditions where drones operate simultaneously without a specific sequence.ConclusionFailure to monitor industrial equipment properly can result in substantial financial losses for factories and production units. The improper operation of equipment may lead to complete failure, necessitating the need for replacement. Additionally, increased equipment downtime, quality issues, reduced production speed, safety hazards, and environmental pollution can be consequences of equipment failure, ultimately diminishing the profitability of the production unit. Considering factors such as embargoes, emphasis on domestic production, and self-sufficiency, accurate supervision becomes economically crucial for factories.Effective management of the proper operation of industrial equipment is a fundamental requirement for every production unit, given that industrial equipment represents a significant investment for the unit. If device maintenance is limited to repairs only after breakdowns occur, production devices will consistently face unexpected halts, preventing production productivity from reaching its predetermined goals. Therefore, designing a framework for the "intelligent monitoring of the performance of all relevant industrial equipment" stands as one of the most crucial actions for any production unit. Depending on the type of equipment, monitoring the performance of industrial equipment may encompass periodic inspections, maintenance and repair planning, and scheduling the optimal operational time for the equipment
Ehsan Yadegari; Akbar Alem Tabriz; Mostafa Zandieh
Abstract
Over the past decade, due to environmental laws and the competitive environment, development of an effective tactical plan for efficient and integrated supply chain and considering the responsibility of organizations to collect defective goods seems impossible. In this paper a mixed-integer linear programming ...
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Over the past decade, due to environmental laws and the competitive environment, development of an effective tactical plan for efficient and integrated supply chain and considering the responsibility of organizations to collect defective goods seems impossible. In this paper a mixed-integer linear programming is considered to mathematically model the essentially five stages along our supply chain network: suppliers, manufacturers, DCs, customers, and Dismantlers.Delivers raw materials from suppliers to factories and then through distribution centers, delivering the final product to customers. On the other hand, it simultaneously collects recycled goods from customers and enters the cycle of safe reconstruction or destruction.The aim of this model is minimizing the costs of establishing facilities at potential points as well as the optimal flow of materials in the network layers. Since the problem is NP-hard, to solve it, the cloud theory based simulated annealing algorithm has been used. We also used the tree-covering method to show the answer, which uses fewer arrays than other methods in the literature. To analyze the accuracy and speed of the proposed algorithm, we compared its performance with the genetic and simulated annealing algorithm. The results show that the cost function in the cloud-based refrigeration simulation algorithm provides more accurate answers than both algorithms studied in the literature. The results show that the cost function in the cloud-based simulated annealing algorithm provides more accurate answers than both algorithms studied in the literature. Also, in terms of convergence rate criterion, the proposed method has better position than the genetic algorithm, but it is not significantly different from simulated annealing algorithm.
Akbar Rahimi; Abbas Raad; Akbar Alem Tabriz; Alireza Motameni
Abstract
The production of defense products is indispensable because of the role it plays in deterring and promoting the national security of the country, and, on the other hand, the economic conditions prevailing in the country have made production of defense products at the lowest cost an obligatory requirement. ...
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The production of defense products is indispensable because of the role it plays in deterring and promoting the national security of the country, and, on the other hand, the economic conditions prevailing in the country have made production of defense products at the lowest cost an obligatory requirement. The lean supply chain of defense industries by focusing on waste removal and reducing costs, is an answer for producing lower-cost defense products. The purpose of this research is to identify the most important practices of the defense industries lean supply chain, and then, using exploratory and confirmatory factor analysis, the categorization and verification of the practices based on Structural Equation Modeling (SEM), and then, using the Interpretive Structural Modeling (ISM) model, presents a model that shows the relationships between these practices. The power of driving and dependence of practices are also analyzed using the MICMAC technique. The results of the research show that out of a total of 84 practices introduced in the previous research for the lean supply chain, 94 practices are effective in the lean supply chain of defense industries. It consists of 8 categories and includes: Workshop level management, Quality management, just in time, Repairs and Maintenance management, Human resource management, Suppliers relationships, new products design and Customer relationship. Customer’s relationship as the most basic and most driving practice and supplier relationship is the most dependent practice of the defense industries lean supply chain.
Abdolreza Sedighpour; Mostafa Zandieh; Akbar Alem Tabriz; behroz dori
Abstract
Within two recent decades, the complexity of business environment, dynamics, uncertainty and higher environmental fluctuations, concepts such as globalization and increasing competition made many changes in the equations ruling on the industries supply chain. In such conditions, the businesses must make ...
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Within two recent decades, the complexity of business environment, dynamics, uncertainty and higher environmental fluctuations, concepts such as globalization and increasing competition made many changes in the equations ruling on the industries supply chain. In such conditions, the businesses must make themselves ready for encountering the continuous flow of challenges such as economic crises, sanctions, exchange rate and prices fluctuations, limitations of manufacturing system or natural disasters. “Resiliency” is one of strategies for dealing with such challenges. The present study aims to review the systematic studies based on the strategic position of pharmaceutical industry as a part of society’s health system and present here the resilient supply chain model. For this purpose, in addition to contemplating in the literature review, interview to the experts and using Delphi method, the resilient elements and indices of supply chain were identified and extracted, and a questionnaire was designed and provided to the population of pharmaceutical industry. The results were analyzed using structural Equations modeling technique and Lisrel software, and the proposed model of research was accepted upon explaining the associations between factors. This model studied the relationship between elements such as drivers, vulnerabilities, capabilities and empowerments of supply chain and their effect on each other. Summary of study indicates that the managers of pharmaceutical industries through making or using the capabilities and strengthening the empowerments can reduce the factors that make the companies susceptible for the disruption, and achieve the required resiliency to deal with them.
Seyed hadi Mirghaderi; Akbar Alam Tabriz; Hassan Farsigani,; Farhad Farzad
Volume 13, Issue 38 , October 2015, , Pages 1-25
Abstract
Industrial clusters are one of the new approaches in industrial development of developing countries which has recently attracted the attention of many researchers and policy makers.Clustering has positive economic effects on the region and also increase the competitiveness of the small and medium enterprises ...
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Industrial clusters are one of the new approaches in industrial development of developing countries which has recently attracted the attention of many researchers and policy makers.Clustering has positive economic effects on the region and also increase the competitiveness of the small and medium enterprises (SMEs).But success level of all clusters is not the same because their performances are different. The subject of clusters performance has various aspects and contains a wide range of result areas. This is due to cross-organizational nature and complexity of the internal functions and external effects of cluster as a comprehensive model of industrial cluster performance dimensions have not been presented so far.Precise definition of performance dimensions can reduce (part view) which is based on point of view to clusters and also study of cluster development proceedings with comprehensive approach can be applicable. This study aims to identify the performance dimensions of industrial clusters by classifying the performance measures of industrial clusters and present a model for comprehensive evaluation of industrial clusters performance. For data analysis the method used in this study is cluster analysis which integrated the Classifications of 31 experts used heuristic method and based on that, four performance dimensions of industrial clusters including financial, competitive, economic and environmental along with components and measures of each were extracted.
akdar alam tabriz; amirsalar mohammadi; mir saman pishvaee
Volume 11, Issue 28 , April 2013, , Pages 21-40
Abstract
Economic Development of countries caused damages in environment and society. This issue created three dimensional concept for development, based on economy, society and environment that named as a sustainable development. Mining industry is one of the industries that always faced with challenges of sustainable ...
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Economic Development of countries caused damages in environment and society. This issue created three dimensional concept for development, based on economy, society and environment that named as a sustainable development. Mining industry is one of the industries that always faced with challenges of sustainable development. Based on this issue and based on need for evaluation tools in sustainable development, this article is specified to recommending suitable tool for evaluating sustainability of development in mining industry. For this purpose after investigation of literature, balance scorecard recognized as a suitable tool, then international indicators are localized based on the expert opinion and Iran mining industry situation, and put in BSC aspects. Finally by using AHP method importance weight of BSC aspects and indicators calculated for recommending quantitative tool to mining industry organizations
