Amir Mehdiabadi; Adel Azar; AbuTurab Alirezaee; Ghanbar Abbaspour Esfeden
Abstract
The Soft System Methodology (SSM), one of the OR techniques, is used tosolve complex real-world problems. Since to design of the after-sales servicemodels for the liquefied gas industry, various groups, such as refineries,mopeds, silencers, taps, standardized organizations, and the consumer rightsprotection ...
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The Soft System Methodology (SSM), one of the OR techniques, is used tosolve complex real-world problems. Since to design of the after-sales servicemodels for the liquefied gas industry, various groups, such as refineries,mopeds, silencers, taps, standardized organizations, and the consumer rightsprotection organization should be considered, so decision making in thissituations are very complicated issue. In this study, using the aboveapproach, the problem of non-structured model design at the world-classlevel is explained and then, by specifying its boundaries, the image of thevarious actors of the system and their benefits are depicted. In the third step,the CATWOE approach is used to explain the basic definition of the aftersales service model in this industry, and in the fourth stage, a conceptualmodel of activities is presented using the root definition. This paper usesintegration of ISM-Fuzzy Delphi in the process of problem solving. In thefifth step, the developed model is compared with the real world. In the sixthstage, desirable and feasible changes were identified and explained by theIPA method. Finally, using the results of the previous stages, andsuggestions for the development of the model to reach the world class levelare presented to the authorities and stakeholders.
Mohammad Reza Hassani; Javad Behnamian
Abstract
The employee scheduling seeks to find an optimal schedule for employees according to the amount of demand (workload), employee availability, labor law, employment contracts, etc. The importance of this problem in improving the quality of service, health and satisfaction of employees and reducing costs, ...
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The employee scheduling seeks to find an optimal schedule for employees according to the amount of demand (workload), employee availability, labor law, employment contracts, etc. The importance of this problem in improving the quality of service, health and satisfaction of employees and reducing costs, including in hospitals, military or service centers, has encouraged researchers to study. In this regard, nurse rostering problem is a scheduling that determines the number of nurses required with different skills and the time of their services on the planning horizon. In this research, by adding the nurses' shift preferences and number of consecutive working days constraints, an attempt has been made to make the problem more realistic. The objective function of the problem is to minimize the total cost of allocating work shifts to nurses, the cost of the number of nurses required to reserve, the cost of overtime from a particular shift, the cost of underemployment from a particular shift, the cost of overtime on the planning horizon, the cost of underemployment on the planning horizon and the cost of absence shift-working and non-working days preferred by nurses. To solve problem, after modeling the problem as a mixed-nteger program and due to the complexity of the problem, the differential evolutionary algorithm is used with innovation in its crossover operator. To validate the proposed algorithm, its output was compared with the genetic algorithm. The results show that the differential evolutionary algorithm has good performance in problem-solving.Keywords: Nurse Rostering Problem, Deferential Evolution Algorithm
Mohammad Ali Sangbor; Mohammad Reza Safi; Masood Rabieh
Abstract
Petrochemical industry is one of the leading industries in the field of oil and gas in the country, which has a significant role in completing the chains of value creation in this field. Today, given the fact that sustainable development and, consequently, sustainable adaptation in supply chain management ...
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Petrochemical industry is one of the leading industries in the field of oil and gas in the country, which has a significant role in completing the chains of value creation in this field. Today, given the fact that sustainable development and, consequently, sustainable adaptation in supply chain management have become a social demand, the development of the petrochemical industry in the country and the penetration of global markets require the adaptation of sustainable development approaches in this industry. The purpose of this study is to identify, assess and analyze enablers that facilitates the achievement of sustainable development goals in the petrochemical supply chain. In order to achieve the research objectives, first by using Meta-Synthesis Method, the previous studies in the field of sustainable supply chain management investigated and the main factors and components that enable sustainable supply chain management have identified. Then, according to the Graph Theory and Matrix Approach (GTMA), the Supply chain management enablers have been analyzed. Based on the research findings, sustainable supply chain management enablers in the petrochemical industry was divided into components related to corporate governance, supply chain management, continuity of supply chain, supply chain characteristics, partnership in supply chain, and employees. The components related to continuity of the supply chain were the first priorities of planning in the petrochemical industry.
supply chain management
Mehdi Seifbarghy; Nastaran Bakhshizadeh
Abstract
Closed loop supply chain network design is of great important due to the legal requirements and economic benefits. Raw material suppliers are of the most important players of this supply chain. Most of the previous researchers studied the design problem separated from the supplier assessment. Some other ...
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Closed loop supply chain network design is of great important due to the legal requirements and economic benefits. Raw material suppliers are of the most important players of this supply chain. Most of the previous researchers studied the design problem separated from the supplier assessment. Some other criteria except for price, like the production process, the features of parts and reliability of supply have long term effects on the performance of supply chains. In this research a general closed loop supply chain network including production centres, disassembly, refurbishing, and disposal sites is considered. An integrated two-phase model is given so that in the first phase, the proposed fuzzy-MOORA-reference point method is applied to suppliers’ assessment and the results from this phase is used in the second phase. In the second phase, a three-objective mixed integer linear programming model is proposed in order to determine the eligible suppliers, the locations of refurbishing sites and the material flows between the supply chain members. The objective functions are maximizing profit, suppliers’ evaluation and resiliency scores. Unsatisfied demand of customers is lost. The numerical results show the validity of the model and the role of stockout option in reaching better solutions based on the LP-Metric method.
Alireza Moumivand; Adel Azar; Abbas Toloie Eshlaghy
Abstract
Soft OR from pluralist paradigm has effective approaches to structure and improve problem situations with different stakeholders’ worldviews and conflict of interests. The approaches, structure and improve messy situations. In this study, we used Soft System Methodology (SSM) as a popular soft ...
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Soft OR from pluralist paradigm has effective approaches to structure and improve problem situations with different stakeholders’ worldviews and conflict of interests. The approaches, structure and improve messy situations. In this study, we used Soft System Methodology (SSM) as a popular soft approach at two levels. First, we applied Soft System Methodology process (SSMp) to plan the systemic intervention process in the employee promotion System of an oil and gas company. Then, Soft System Methodology content (SSMc) was used to investigate the content of the company's employee promotion system that caused employees’ dissatisfaction. By considering managers’ and employees’ worldviews, three root definitions were made. At this phase, fair condition to present different points of view was applied. So, employees with different organizational power levels expressed their opinions openly. Finally, stakeholders’ participation through the discussion helped to build an agreed model and a root definition, and agreed actions for addressing defects of the employee promotion system were proposed.
Morteza Khorram; Mahmood Eghtesadifard; Sadegh Niroomand
Abstract
This paper focuses on a novel model of the U-shaped assembly line balancing problem, in which the objective functions include cost, capacity, and quality. It is assumed that each task requires a set of equipment. In addition, the quality of tasks performed by each worker varies. Hence, the purpose of ...
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This paper focuses on a novel model of the U-shaped assembly line balancing problem, in which the objective functions include cost, capacity, and quality. It is assumed that each task requires a set of equipment. In addition, the quality of tasks performed by each worker varies. Hence, the purpose of the model is that the total cost of the equipment is minimized and the quality of the work is maximized. Additionally, the number of workstations is minimized. At first, a multi-objective non-linear mixed-integer programming model is provided. Then, the model is linearized, and simulated annealing (SA) algorithm and two of its modified modes have been proposed to solve the problem. The proposed algorithm includes a new encoding/decoding scheme, as well as a local search for assigning the worker to each station. To determine the parameters in three algorithms, the experimental design has been used and various modes have been created by combining the parameters. Moreover, numerical examples were established based on the graphs found in the literature and the solution is compared with three algorithms, revealing the efficiency of each algorithm. Additionally, a case study on the nozzle assembly line in oil refineries was conducted to evaluate the efficiency of the proposed model and algorithm. Results from the case study show that the modified SA algorithms performed better.IntroductionNowadays, assembly lines play a crucial role in the production of standardized and high-volume products. If task allocation to workstations is done without considering the balance of the assembly line, it can lead to high levels of idle time in some workstations and decreased line efficiency. Therefore, assembly line balancing is an important stage in the production process to enhance production line productivity. This study focuses on the single-model U-shaped assembly line balancing problem. Assembly lines can be divided into four categories based on their layout, and in this research, the U-shaped assembly lines are specifically considered. The objectives of this problem include minimizing the number of workstations, minimizing equipment costs, and minimizing the level of work quality deviation at each workstation (equivalent to maximizing work quality). Additionally, constraints related to occurrence, precedence, and capacity, as well as limitations on tool and worker allocations, have been considered in the problem model. In terms of research gaps in this field, it should be noted that in previous studies on U-shaped assembly line balancing problems, objective functions combining cost, capacity, and quality have not been simultaneously addressed within a single problem. Furthermore, simultaneous allocation of workers (based on skill levels) and tools has not been studied in the context of U-shaped assembly line balancing problems.Materials and MethodsIn this study, a nonlinear mixed-integer multi-objective programming model is proposed for balancing a single-model U-shaped assembly line. The problem modeling assumes realistic conditions where each task requires a set of tools, and in this regard, the quality of task execution by workers is considered to be different. The modeling of quality in the assembly line balancing problem (as one of the objective functions) is approached differently compared to previous studies in this field, aiming to minimize the level of work quality deviation in all workstations. Additionally, for solving the problem, the allocation of workers and tools to the workstations is performed based on a neighborhood algorithm, which is a notable innovation in the research. In this study, a modified simulated annealing metaheuristic algorithm is developed with innovations in encoding and decoding procedures to solve the proposed model in three optimization scenarios. To compare the results of these algorithms, numerical examples based on graphs available in the research literature are solved using the three algorithms. Furthermore, a case study is conducted on the assembly line of component δ, which is used in oil refineries, to evaluate the efficiency of the proposed model and algorithm in real assembly lines.Discussion and ResultsIn this study, to validate the proposed algorithms, 10 numerical examples of different sizes (small, medium, and large) were designed based on valid graphs available in the research literature. Then, for various parameter values, each problem was solved 10 times using each algorithm, and the results of each algorithm were analyzed. In these examples, the costs of tools and the data related to task quality were randomly generated. Additionally, workers with different skills were defined to perform the tasks. Furthermore, the cycle time proportional to the activity durations was considered. It is observed that in all solved examples, the values of the third objective function (quality objective function) obtained from the third algorithm are better than the values obtained from the first and second algorithms. These results are not unexpected because in the third algorithm, due to the presence of an improvement loop for the third objective function, its value decreases compared to the other two algorithms, resulting in a reduction in the overall objective function and its improvement compared to the other two algorithms. For the cost minimization objective function (first objective function) and the number of workstations minimization objective function (second objective function), the values obtained from the three algorithms are approximately the same, and the difference in the obtained values for the overall objective function is primarily dependent on the value of the quality objective function (third objective function). Additionally, the results of solving the numerical examples show that the third algorithm achieves the best values for the overall objective function (compared to the other two algorithms) on examples with more than 25 activities, indicating that employing a local search for worker allocation in the modified simulated annealing algorithm makes the algorithm stronger and more efficient compared to its classical form.ConclusionIn this research, the modeling and problem-solving of the U-shaped assembly line balancing problem were investigated considering tool allocation constraints and quality conditions. To this end, a mixed integer nonlinear programming model was presented for the problem, where equipment and workers were simultaneously considered as two objectives in terms of minimizing equipment cost and the level of task quality. In addition to these two objectives, the number of workstations was also minimized. To solve the problem, a metaheuristic algorithm called simulated annealing was employed, as well as two improved versions of it (by introducing innovations in the random allocation of workers to workstations and applying a local search for improving worker allocation). The proposed model was solved using well-known graphs in the literature of assembly line balancing problems (as numerical examples) with the proposed algorithms, and the results obtained from the algorithms were compared and the performance of these algorithms was analyzed and examined.
supply chain management
Mina Kazemi Miyangaskari; Mohammad Reza Mehrregan; Hossein Safari; samira keivanpour; Mahmoud Dehghan Nayer
Abstract
In today's competitive business landscape, the efficient management of supply chains has become a cornerstone of success for economic enterprises. Supplier selection, as the initial link in the supply chain, holds significant sway over various critical factors, such as product quality, return rates, ...
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In today's competitive business landscape, the efficient management of supply chains has become a cornerstone of success for economic enterprises. Supplier selection, as the initial link in the supply chain, holds significant sway over various critical factors, such as product quality, return rates, and production costs. However, the real world is rife with uncertainties, making the application of a fuzzy approach highly advisable. This study's primary objective is to develop a model for supplier selection and order quantity determination for perishable protein products in a retail setting under uncertain conditions. Initially, a comprehensive fuzzy multi-objective model is designed for Kourosh Protein, a company in the closed-loop supply chain, aiming to minimize costs, waste, and maximize profit, customer satisfaction, quality, and profit margin in the face of uncertainty. Subsequently, this full-fledged fuzzy multi-objective model is transformed into a deterministic single-objective model using the Sharma and Agarwal method (2018), yielding optimal order quantities from each supplier. The model's practical implementation in an Iranian retail store for protein products, such as sausages, bologna, hamburgers, etc., demonstrates its potential to reduce costs and boost profits.IntroductionThe global population's rapid expansion and shifts in lifestyle have significantly elevated the food sector's importance in the global economy, specifically in Sustainable Food Supply Chain Management (SFSCM). SFSCM plays a pivotal role in balancing economic, social, and environmental criteria to optimize supply chain performance. Within the complex food supply chain, suppliers wield considerable influence due to their impact on product attributes, safety, quality, and perishability. Supplier selection, a critical facet of SFSCM, substantially affects a company's strategic and operational performance, product pricing, and quality. In this context, this research introduces a fully fuzzy multi-objective model (FFMOP) to enhance the sustainable supply chain performance of a retail company's protein products. Given the inherent uncertainties associated with supplier selection, the proposed model incorporates an extensive array of variables to simulate real-world scenarios. This innovative approach aims to address identified gaps in existing literature, providing a more robust and realistic tool for bolstering supply chain sustainability.Materials and MethodsThis study constructs a full fuzzy multi-objective model with the objective of determining optimal order quantities within the food supply chain while integrating sustainability criteria. The analyzed supply chain network encompasses multiple suppliers, a single retailer, and end consumers, characterized by multi-product and multi-level interactions. The model seeks to optimize profit, customer satisfaction, brand acceptance, quality, profit margin, and minimize waste production while determining the optimal order volume for each product from each supplier. Reviewing the existing literature reveals various approaches to tackle Full Fuzzy Multi-Objective Problems. This research employs the methodology proposed by Sharma & Aggarwal in 2018 to solve the FFMOP model. After defuzzification, the final model is solved using GAMS software to determine the optimal values of decision variables.ResultsThis research utilizes a case study of an Iranian retail company with eight main suppliers providing 15 protein food products. However, the focus is primarily on four key products: sausages, bologna, hamburgers, and pizza cheese, which are examined. Data for the study was collected from historical company records and interviews with experts from June 2021 to 2022. Model parameters are defined using trapezoidal fuzzy numbers. A comparison of optimal order quantities with the company's actual orders and sales reveals that the proposed model for order allocation leads to reduced ordering, maintenance, and procurement costs for the company. Additionally, the model mitigates waste resulting from unsold products.ConclusionSupplier selection stands as a pivotal process in an effective supply chain, exerting substantial influence on a company's strategic outcomes and performance metrics. This study employs a full fuzzy multi-objective model to identify the most suitable supplier and determine optimal orders within a sustainable food supply chain context. To better mimic real-world conditions, variables and parameters are treated as trapezoidal fuzzy numbers. A comparison of the model's outputs with actual sales data indicates that this methodology aligns more accurately with sales figures. Consequently, applying this model has the potential to reduce waste production and economic consequences. The study's achievement lies in selecting a supplier through a methodology that simultaneously considers sustainability criteria within a fully fuzzy environment while determining optimal order quantities from various suppliers. Moreover, the model's flexibility allows for its application across diverse industries, including dairy and dried fruit, for procuring and selling an array of products from potential suppliers.
supply chain management
Mehrdad kiani; davood andalib ardakani; Habib Zare Ahmadabadi; Seid Heydar Mirfakhraddini
Abstract
Circular economy and Industry 4.0 are concepts that have garnered significant attention from businesses and universities in recent years. They are currently being promoted by many governments worldwide. The synergy between these two concepts offers the potential to move towards a more sustainable society ...
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Circular economy and Industry 4.0 are concepts that have garnered significant attention from businesses and universities in recent years. They are currently being promoted by many governments worldwide. The synergy between these two concepts offers the potential to move towards a more sustainable society and address the environmental and economic challenges related to managing organizational operations. This research aims to analyze the factors enabling the implementation of circular economy and Industry 4.0 in the supply chain of Yazd glass factories. In the initial phase of the research, a review of various articles was conducted using the meta-synthesis method to identify and categorize relevant enablers. This process resulted in the identification of 15 enablers categorized into four dimensions: economic, human resources, organizational management, and infrastructure. In the subsequent step, the Fuzzy DEMATEL technique was employed to examine the cause-and-effect relationships. The findings indicate that, within the economic dimension, the most influential enablers are "budget allocation for the implementation of circular economy and Industry 4.0" and "stimulation of demand for circular products." In the human resources dimension, "training and development of employees" and "organizational culture" play crucial roles. In the organizational-management dimension, "support and commitment of senior management" and "cooperation and networking with supply chain partners (industrial coexistence)" are highly significant. Lastly, within the infrastructure dimension, "development of information technology standards and infrastructures" and "security and protection of intellectual property rights" are considered the most effective enablers for the implementation of circular economy and Industry 4.0 in the Yazd glass factories. The results indicate that the Ardakan glass factories of Yazd should prioritize attention to economic and infrastructural enablers when implementing circular economy and Industry 4.0.
Introduction
The concept of the circular economy can be regarded as a solution to reduce production costs within a sustainable supply chain. In this context, the integration of cyber-physical systems, big data, data mining, data analytics, the Internet of Things, and novel business models can offer significant opportunities for the creation of sustainable industrial value, value capture, and the promotion of the circular economy (Antikainen et al., 2018). Industry 4.0, often referred to as the future of supply chains, can have numerous implications for sustainability, including the optimal utilization of resources and technology (Quezada et al., 2017). Based on the sustainability axis, the concept of Industry 4.0 aids industrial managers in encompassing not only environmental protection and control initiatives but also aspects of process safety, such as resource efficiency, human resource and societal well-being, and the development of smarter and more flexible supply chain processes (Luthra & Mangla, 2018). Numerous studies have explored the factors that impact the implementation of circular economy and Industry 4.0, and these factors have been broadly classified into categories such as barriers, challenges, drivers, and enablers (Fedotkina et al., 2019). Identifying the enablers that are effective in implementation is a crucial step in enhancing the performance of a circular and intelligent supply chain. Until these enablers are identified, it is impossible to determine their relative importance. Following their identification, industry practitioners and policymakers can develop appropriate strategies for their implementation. As such, this current research aims to identify, categorize, and analyze the effective enablers for implementing circular economy and Industry 4.0 at the Ardakan Glass Factory in Yazd, which is the largest glass factory in West Asia. To achieve this, both a qualitative method for enabler identification and the technical Dimtel method using fuzzy logic for establishing cause-and-effect relationships between enablers are employed. What sets this research apart from others is its focus on identifying the combined enablers for implementing the circular economy and Industry 4.0 at the Ardakan Glass Factory Group of Yazd, as well as the network approach that examines the relationships and interactions between these enablers. Given these key elements, this research aims to address the following questions:
-What are the effective enablers for implementing the circular economy and Industry 4.0 at the Ardakan glass factories in Yazd?
-What is the effectiveness and influence, including cause-and-effect relationships, of these enablers?
Materials and Methods
This research is categorized as applied-developmental research in terms of its purpose and is classified as a field-library study in terms of its methodology. Its objective is to formulate a novel scientific model of enablers for implementing circular economy and Industry 4.0 within organizational supply chains. Given the significant number of qualitative articles that have explored the enablers of Industry 4.0 and the circular economy across various industries and the need to establish a shared understanding of these enablers, the first stage of this research involved identifying effective enablers using the meta-synthesis qualitative method. Their validity was assessed through content validity, which involved obtaining opinions from 15 organizational experts. In the second phase of the research, the researchers evaluated the effectiveness and impact of these enablers using the Fuzzy DEMATEL method. The statistical population for the first stage of the research comprised all studies published in the Scopus database, the largest text database, related to the enablers that influence the implementation of circular economy and Industry 4.0 within organizational supply chains up until the commencement of this research. In the second stage of the research, the statistical population included all professors and managers with expertise in sustainability, familiar with circular economy, and knowledgeable about Industry 4.0 technologies at Ardakan Glass Factories in Yazd. For this phase, a purposeful sampling method was used to select ten participants.
Discussion and Results
The purpose of the current research is to analyze the enablers that are effective in implementing the circular economy and Industry 4.0 within the supply chain of Ardakan Glass Factories in Yazd. In the first stage of the research, various articles were reviewed, and the meta-combination method was employed to identify and categorize relevant enablers. This process led to the identification of 15 enablers across four dimensions: economic, human resources, organizational management, and infrastructure. In the second stage, the Fuzzy DEMATEL technique was utilized to investigate the cause-and-effect relationships between these enablers. The research results revealed that the economic and infrastructural enablers are considered influential dimensions that affect human resources and organizational management dimensions. Within the economic dimension, "budget allocation for the implementation of the circular economy and Industry 4.0" and "stimulation of demand for circular products" emerged as the most effective enablers. Additionally, in the infrastructure dimension, "development of IT standards and infrastructure" was identified as the most influential enabler for the implementation of the circular economy and Industry 4.0 within the supply chain. In the organizational management dimension, "the support and commitment of senior management" was recognized as the most influential enabler.
Conclusion
While the enablers mentioned are considered among the most effective ones in implementing circular economy and Industry 4.0 in the Ardakan Glass Factories of Yazd, it's crucial for the glass industry to prioritize the most important enablers. It's essential to pay adequate attention to all identified enablers. Using specific guidelines and a checklist of effective enablers during decision-making can facilitate the decision-making process and enhance decision-making capabilities. Therefore, based on the identified enablers and their importance in this research, it's recommended to develop and provide guidelines and checklists for executive managers. Among the significant limitations of this research is the reliance on a single scientific database, Scopus, for sourcing research. It's advisable to supplement this by utilizing other databases such as Google Scholar and Web of Science. Additionally, the classification of enablers was conducted using a qualitative approach. Researchers are encouraged to name and categorize enablers using survey and quantitative methods, such as cluster analysis, to expand their research scope. Another limitation pertains to the research's statistical population, which was restricted to Ardakan Glass Factories in Yazd due to time and cost constraints. To generalize the research results, it's advisable to investigate the same research topic in other glass factories across the country. Future researchers could employ methods like fuzzy cognitive mapping and systems dynamics to examine relationships and interactions between enablers. Moreover, the enablers identified and analyzed in this research were primarily based on international studies. To adapt these enablers to the specific conditions of Iran's industries, it's suggested that in-depth interviews be conducted with industry owners. This way, certain enablers that may be unique to Iran's circumstances or require different interpretations can be revised.
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
seyyed heydar mirfakhradini; fatemeh azizi
Volume 13, Issue 36 , April 2015, , Pages 5-26
Abstract
Performance evaluation is a systematic review that helps organizations to achieve their goals. This study evaluates and ranks Yazd Science and Technology Park’s high-tech firms, using integration Data Envelopment Analysis into Six Sigma methodology. In this study a combination of both methods is ...
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Performance evaluation is a systematic review that helps organizations to achieve their goals. This study evaluates and ranks Yazd Science and Technology Park’s high-tech firms, using integration Data Envelopment Analysis into Six Sigma methodology. In this study a combination of both methods is used to propose more effective and efficient performance evaluation framework. By studying research literature in the field of Science and Technology Park’s firms’ performance evaluation and using Fuzzy Delphi, Effective criteria for measuring the performance of Yazd Science and Technology Park’s firms are identified, then by reviewing research literature and experts’ opinions, inputs and outputs of DEA model are identified. Then, by using combining DMAIC circle and DEA, an inclusive approach for In the analysis phase of Six Sigma evaluating performance is suggested. process ranking of firms is identified using DEA scores. This research helps firms’ managers to find the effective criteria on their performance and how they can improve these factors and control its impacts.
Masoud Rabbani,; Neda Manavizadeh; Amir Farshbaf-Geranmayeh
Volume 13, Issue 37 , July 2015, , Pages 5-35
Abstract
In this paper, supply chain network design problem is modeled as a fuzzy multi objective mixed integer programming which seeks to locate the plants, DCs, and warehouses by considering disruption, supply and demand risk. Maximizing net present value of supply chain cash flow, minimizing delivery tardiness ...
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In this paper, supply chain network design problem is modeled as a fuzzy multi objective mixed integer programming which seeks to locate the plants, DCs, and warehouses by considering disruption, supply and demand risk. Maximizing net present value of supply chain cash flow, minimizing delivery tardiness and maximizing reliability of suppliers are considered as objective functions in the proposed mathematic model. In order to have a more reliable model in case of disruption, the robustness measure is used in the model. Moreover, because of the lack of information, the economic factors such as tax rate, interest rate, and inflation are considered as uncertain factors in the model. An interactive possibilistic programming approach is applied for solving the multi-objective model. To solve larger size instances, genetic algorithm is proposed. Finally numerical examples are presented to show how the model works in practice
Adel Azar; Maryam Shariati rad
Volume 10, Issue 27 , January 2012, , Pages 6-21
Abstract
One of the trench that is used in quality desiccation is QualityFunction Deployment. One of the factors which has been used in thismethod is accomplishing the house of quality and as a result isdetermining the degree of importance of the customer's requirements.Kano model is a kind of two dimensional ...
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One of the trench that is used in quality desiccation is QualityFunction Deployment. One of the factors which has been used in thismethod is accomplishing the house of quality and as a result isdetermining the degree of importance of the customer's requirements.Kano model is a kind of two dimensional model which help theproducers to divide the consumer's requirements in to five categoriesincluding, basic, performance, attractive, indifferent quality andreverse quality. In the survey by identifying the customer'srequirements we determine kind of them and then according to theimprovement ratio and the degree of importance is assigned. Thedegrees of importance can be used for completing the house of qualitywhich is one of the useful tools in QFD. This research is publicalgorithms that it can use for every product. For example it has beenused in Cement Company of larestan, product II Portland cement
Laya Olfa; ahanyar BamdadSoofu; Maghsoud Amir; Mostafa Ebrahimpoor Azbari
Volume 10, Issue 26 , January 2012, , Pages 9-34
Abstract
For performance evaluation of supply chain, having a comprehensivemodel with reliable data is useful. This can help to improve the entirechain. In this paper a model is presented, according to the nature ofnetwork and multi-stage supply chain, that able to evaluate theperformance of the entire chain ...
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For performance evaluation of supply chain, having a comprehensivemodel with reliable data is useful. This can help to improve the entirechain. In this paper a model is presented, according to the nature ofnetwork and multi-stage supply chain, that able to evaluate theperformance of the entire chain in the form of a mathematical modeland using the financial, knowledge, participation and responsemeasures of the supply chain. In the first part, Indicator sat threelevels; strategic, process and operational, considered and survey themodel verification with Factor Analysis. In the second part, Networkdata envelopment analysis model is used. This paper is the result ofresearch related to supply chain of pharmaceutical companies inTehran Stock Exchange and 115 expert sand senior executive shavebeen questioned as sample. There search results show that strategiclevel with a weight of 0.98 is the most important performance leveland Process and operational levels are respectively 0.97 and 0.87weight. 4chainsof 28 chains studied, have a complete performance and0.43 is the lowest observed performance.
Mansureh Mohammadi; Mohammad Reza Gholamian
Abstract
This paper focuses on supply chain coordination under a revenue sharing contract. Demand plays a crucial role in modeling inventory systems, particularly in the retail industry where products need to be brought in and taken out of retail stores within specified timeframes. The question addressed is how ...
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This paper focuses on supply chain coordination under a revenue sharing contract. Demand plays a crucial role in modeling inventory systems, particularly in the retail industry where products need to be brought in and taken out of retail stores within specified timeframes. The question addressed is how to allocate shelf space effectively. Optimal shelf space allocation in retail significantly impacts product sales and profitability. The research demonstrates that by considering factors such as price, allocated shelf space, product brand image, and advertising, a new demand function can be developed. The study explores decentralized, centralized, and coordinated structures using a Stackelberg game model. The findings show that a revenue sharing contract leads to a win-win outcome in the supply chain. Additionally, a numerical example is provided to illustrate the model, and sensitivity analysis is performed on key parameters. The results highlight the significant impact of price elasticity on demand, emphasizing the need to pay close attention to this parameter in real-world applications.IntroductionCoordinating manufacturers and retailers has always been a challenge in decentralized supply chains, as each member seeks individual profit. One practical mechanism for coordination is the revenue-sharing contract, where manufacturers set the wholesale price and retailers pay it. Additionally, retailers share a portion of their profits with manufacturers to incentivize participation in coordinated structures. However, the percentage must be chosen carefully to maximize the profits of both chain members compared to a decentralized structure. In today's competitive world, securing shelf space and determining optimal pricing, particularly in chain stores, has become increasingly intense. Companies can increase their profits by considering various factors that influence customer behavior. This study investigates how manufacturers and retailers in a supply chain leverage advertising and brand image to drive demand while setting prices and allocating shelf space for their products. This new model effectively captures the concept of competition in the market. On the other hand, in today's highly competitive business world, the competition to secure shelf space and determine pricing in department stores has intensified. Pricing and shelf space decisions are influenced by the demand within the supply chain. By considering various factors that impact customer behavior and incorporating them into the model, even though it introduces complexity and challenges in solving the model, the results become more realistic and enhance the model's effectiveness. Customers place great importance on accessing products at the right time and place, making optimal allocation of shelf space in stores and effective shelf space planning crucial steps towards improving and increasing sales in retail stores.Materials and MethodsA two-echelon supply chain, comprising a manufacturer as the leader and a retailer as the follower, is the focus of this study, and Stackelberg game theory is applied to model and analyze this system. The investigated model considers decentralized, centralized, and coordinated structures. Through this research, various factors such as price, allocated shelf space, and the impact of product brand image and advertising are taken into account, leading to the development of a new demand function. The application of the Stackelberg game in the developed model demonstrates how a revenue sharing contract can result in a win-win outcome within the supply chain. Real-world performance analysis of the proposed models is conducted using a dataset from Golrang Holding Supply Chain Network and Ofogh Kourosh Chain Stores Company in Iran.Discussion and ResultsThe proposed problem is modeled under three structures: (1) a decentralized structure where each member of the supply chain (SC) makes independent decisions to optimize its own profit, (2) a centralized structure where a central administrator maximizes the overall SC profit, and (3) a coordinated structure achieved through the design of a revenue-sharing contract. The revenue-sharing contract encourages SC members to transition from the decentralized structure to the centralized one. The results demonstrate that the use of the revenue-sharing contract leads to the sum of retailer and manufacturer profits being equal to the total profit in the centralized structure, with each member achieving higher profit compared to the decentralized structure. Consequently, the revenue-sharing contract facilitates the coordination of the desired supply chain.ConclusionsThis research is based on a real-life case study in the retail industry. The findings of this study are applicable to various retail sectors, including dairy, protein, grocery, cosmetics, fresh fruits, vegetables, and more. Traditionally, price has been viewed as a revenue generation tool. However, it is now recognized that price plays a crucial role not only in generating revenue but also in ensuring customer satisfaction. Therefore, it is important to coordinate and align pricing decisions with factors related to customer management, such as brand image and advertising. The main objective of this research is to design a new model with a multiplicative demand function that considers factors such as price, shelf space, brand image, and advertising. Additionally, the implementation of a revenue-sharing contract has improved system performance. The developed models were solved using Mathematica software, and numerical examples were provided to demonstrate their real-world application and the solution method. The numerical examples revealed that the centralized and coordinated structures experienced price declines compared to the decentralized model, leading to increased profitability in these structures. Furthermore, sensitivity analysis was conducted on key model parameters, highlighting the significance of the price elasticity parameter on demand. This parameter should be given greater consideration in real-world applications. While the study focused on a supply chain structure involving one manufacturer and one retailer, future research can explore supply chains with multiple retailers. It is also possible to combine various supply chain coordination contracts or compare different coordination contracts with each other.
laya olfat
Tayebeh Abbasnejad; Reza Shafizadeh; Mohammad Ghafournia
Abstract
The companies for their growth and survival in competitive domains must develop new products; however, innovation required for this process is a risky and costly enterprise. Most of the scholars have considered the factors leading to success as static and they have not taken into account their dynamic ...
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The companies for their growth and survival in competitive domains must develop new products; however, innovation required for this process is a risky and costly enterprise. Most of the scholars have considered the factors leading to success as static and they have not taken into account their dynamic nature. Since the relationships among the influential factors which can lead to the success of developing new products have various dynamics and feedbacks, tools for the identification of dynamics in such systems are among the most useful tools which can be used for investigative purposes in this domain. In the present study, which aimed at identifying and analyzing the dynamics of factors affecting the success of new product development, the key variables for the development of new products were identified based on the theoretical backgrounds and the ideas of experts in the industry and then the causal relationships among them were drawn. Subsequently, the mathematical relationships among these variables were determined based on the existing relationships among them in the literature and as a practical step the intended system was simulated in Nooshin Azar Food Company in the time span of 1384 to 1404. For improving the performance of the companies, policies like increased management support, more investment in research and development and improvement of product development planning were suggested and the results which can be derived by applying these scenarios were simulated as well.
Aref Tayyeba; Mohammad Ali Shafia
Volume 2, Issue 7 , December 2004, , Pages 15-35
Abstract
In this article it has been tries to represent the strategy of development paraffin industry in Iran by USING SWOT model.
Different Production Technologies have been acquainted in expansionist vision and production possibility has been noticed. Suitable technology has been chosen with ...
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In this article it has been tries to represent the strategy of development paraffin industry in Iran by USING SWOT model.
Different Production Technologies have been acquainted in expansionist vision and production possibility has been noticed. Suitable technology has been chosen with the use of Multiple Attribute Decision Making and TOPSIS Decision making model. ELECTRE Decision Making Model has been used of evaluate & confirm the accuracy of its results.
Maghsoud Amiri
Volume 8, Issue 18 , September 2010, , Pages 15-39
Abstract
Some problems of real world, must be determine and analyze input variable's effect on response variable. One of the applicable techniques which are used for modeling and solving such problems is response surface methodology (RSM). In this paper the effect of five controllable input factors: raw materials, ...
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Some problems of real world, must be determine and analyze input variable's effect on response variable. One of the applicable techniques which are used for modeling and solving such problems is response surface methodology (RSM). In this paper the effect of five controllable input factors: raw materials, electromotor speed, stove temperature, furnace temperature and air pressure on the determined response surface level i.e. the resistance of glass bottle is checked by design of experiment (DOE). After the execution of experiments and the recognition of effective factors, according to the application of RSM, the relationship between variables of effective input factors and the response surface variable is determined by nonlinear regression model. Then, the optimal value of each variable in nonlinear model is obtained by goal programming method.
Fatemeh salati; Ahmadi makoui
Volume 11, Issue 31 , January 2014, , Pages 19-33
Abstract
Subjectto prioritizeresearch projectsdue toresource constraints, the most important financial resources,manpower andequipmentis essential. To this purpose,the Officeof Education, Research and Technologyof Water ResourcesWith theimplementationof thisresearch is asignificant stepin coordinatingresearch ...
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Subjectto prioritizeresearch projectsdue toresource constraints, the most important financial resources,manpower andequipmentis essential. To this purpose,the Officeof Education, Research and Technologyof Water ResourcesWith theimplementationof thisresearch is asignificant stepin coordinatingresearch projectsinthe organizationhas taken.Thispaperissuitable forthe evaluationofresearch projects, the company is identifiedInthisreview of10researchprojects inthewater supplycompanyforconfidentiality andnon-licensed companyhasrefrainedfrom expressingresearchtopicsselectedbyAfter specifyingthe desiredcriteriadecision makingmethodAHPgroupprojectsarerankedTheratingdecisionisareferenceto estimate theutility functionand obtainthereferenceset ofdecisionsis no longer possiblewith anymethod,Themethodforthe estimation ofthe value functionisUTASTAR. The ultimate goalof thisarticle isprovidedsubjecttotheprioritization ofresearch projectsinthe company.With the use of this value subject to the office of education, research and technology resources company research projects can water the water resources of the other company or project that company in the future with them will assess and ranking.Undoubtedly this attitude and in the framework of the general value subject to the opportunity for Investment Promotion policy in the field of credits for priority research project .
Fattah Mikaeelei; Hossein Sedaghati
Volume 4, Issue 13 , June 2006, , Pages 19-40
Abstract
This research is done in order to evaluate and manage IT/IS outsourcing risks. Awareness about outsourcing, as a supportive source of organization strategies, is increasing and it is not only seen as a factor to reduce organization costs anymore. For this reason, organizations inclination to use IT Outsourcing, ...
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This research is done in order to evaluate and manage IT/IS outsourcing risks. Awareness about outsourcing, as a supportive source of organization strategies, is increasing and it is not only seen as a factor to reduce organization costs anymore. For this reason, organizations inclination to use IT Outsourcing, in order to pass useful feedback to the environment, is tremendously increasing. In this research we used expected loss perspective for evaluating risks of IT activities in Ab-Niru Company.
Research's results determined that some systems, which are closed to the core competency activities in the company, have highest amount of outsourcing risk and some systems which are not so close to the core competency activities in the company, have lowest amount of outsourcing risk.
seyed hossein razavi hajiagha; hannan amoozad mahdiraji; hadi akrami; shide sadat hashemi
Volume 11, Issue 29 , July 2013, , Pages 21-39
Abstract
The development of Multiple Criteria Decision Making Techniques is to provide the possibility of using multiple criteria in decision making problems. Multi-criteria decision making problems primarily relate to choosing the best option among several available options and according to some indicators. ...
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The development of Multiple Criteria Decision Making Techniques is to provide the possibility of using multiple criteria in decision making problems. Multi-criteria decision making problems primarily relate to choosing the best option among several available options and according to some indicators. One of the major issues in this regard is to determine the importance weights of decision criteria. Various methods such as Entropy, LINMAP and Saaty’s method have been presented for determining the weights of the indicators. In this paper, a non-linear model based on the logic of TOPSIS method is proposed to estimate the ideal weights. Simplicity, Reduction of received data from the decision makers in the evaluation process, and the possibility of considering his comments about the preference of indicators to each other can be cited as the advantages of this method
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
Mohammad Reza Taghva; Amir Reza Ayatollahi
Volume 1, Issue 2 , October 2003, , Pages 21-54
Abstract
In this research, after a brief introduction, different information systems, classification of various methodologies, Object –Oriented view and methodology will be discussed in detail. Then we will design a mechanized information system for purchase activities (including domestic and international ...
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In this research, after a brief introduction, different information systems, classification of various methodologies, Object –Oriented view and methodology will be discussed in detail. Then we will design a mechanized information system for purchase activities (including domestic and international purchase). The purchase division of one of the leading automakers (Sazeh Ghostar Saipa Company) was selected for the case study. The division is a good example of a purchase system because of the nature of its activity which is engineering design as well as provision of the parts.
At end of this article, using a questionnaire, Object-Oriented Methodology will be compared to Structured Methodology (SSADM) from technical, usage, and management points of view and then the results will be analyzed.
S. M. A'arabi; M. Rashid - Kaboli
Volume 2, Issue 4 , March 2004, , Pages 21-39
Abstract
Organizational structure has always been one of the most critical dilemma in the theory of organization. There has been tremendous research findings in this field. Structure-contingency models ...
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Organizational structure has always been one of the most critical dilemma in the theory of organization. There has been tremendous research findings in this field. Structure-contingency models occupy a central position in the study of organization and as guides for organization design. These models hold that the structure of an organization is dependent on its context. Research has shown that variation in organization structure can be explained by variations in such nontextual factors as technology ( Woodward, 1959 ), environment ( Lawrence & Lorsch , 1967) , size ( pugh etal, 1969).
In this study literature pertaining to the structural influence of technology, size, environment and the decision-maker choice is reviewed. It has been shown that the structure - contingency models has neglected the decision-maker choice. We propose that an organization's structure is the result of an interaction of the decision maker's cognitive and motivational orientations, and the organization's context, such as technology, size and environment. Our research finding has supported the previous research findings.
Mohamad Hosein Tahari Mehrjardi; Dariush Farid; Hamid Babaei Meybodi
Volume 8, Issue 21 , June 2011, , Pages 21-37
Abstract
Data Envelopment Analysis (DEA) has been a very popular method for measuring and benchmarking relative efficiency of peer Decision Making Units (DMUs) with multiple input and outputs. However, some problems have also appeared as the applications of DEA advance. One of inter-related problems that has ...
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Data Envelopment Analysis (DEA) has been a very popular method for measuring and benchmarking relative efficiency of peer Decision Making Units (DMUs) with multiple input and outputs. However, some problems have also appeared as the applications of DEA advance. One of inter-related problems that has long been known is the lack of discrimination power. The lack of discriminating power problem occurs when the number of DMUs under evaluation is not large enough compared to the total number of inputs-outputs. In this situation, classical DEA models often yield solutions that identify too many DMUs as efficient. In this study the base of the modeling is technique Data Envelopment Analysis But in order to increase accuracy in assessing banks performance and identify the inefficiency and efficiency units, designing a model that combines data envelopment analysis and Goal Programming and also performance of the banks are measured in this perspective. The results of this study showed the higher ability of the presented model toward the basic models to separate the banking units.
