فصلنامه چشم انداز مدیریت صنعتی
سال سیزدهم شماره 2 (پیاپی 50، تابستان 1402)

In the city of Qom, there is no dual water supply network with a separate meter inside the citizens' homes. On the other hand, high quality water sources do not meet all the drinking and non-drinking needs of the consumption areas. Therefore, the water and sewage company should respond to the drinking and non-drinking needs of the citizens by optimally managing the distribution of various available water resources. In this paper, the problem has been investigated in the form of two optimization mathematical models.In the first model, the current water allocation to citizens has been modeled and optimally solved, in which water resources should be allocated to citizens at the lowest cost, provided that all the needs of citizens are covered. In the second model, it is suggested that by scheduling the allocation of water resources, citizens will have access to quality water for drinking at a certain pre-determined time, and other consumption needs of citizens will be met with low quality water during the rest hours of the day and night.In the proposed model, both the allocation of water resources for the drinking and non-drinking needs of the citizens under the condition of covering all the needs of the citizens and the allocation of water resources with the lowest cost for the needs of the citizens are included. Finally, the application of the proposed model is presented with numerical analysis.

The COVID-19 pandemic has posed a significant challenge to the COVID-19 vaccine supply chain that need to be resolved for a successful exit from the pandemic. It is essential to identify and evaluate the risks associated with the vaccine supply chain. We propose a new measure for quantifying the resilience of the vaccine supply chain in Iran. To evaluate the resilience of the vaccine supply chain, we use a Bayesian network to consider the vulnerability and recoverability indices as well as the associated disruption propagation. This approach enables managers to measure the resilience of the supply chain and identify the reasons for performance decline due to the ripple effect. Our results show that outbreak risks, lack of access to vaccine suppliers, low efficacy of the vaccine against new variants, inaccurate prediction of vaccine demand, and failure to choose the right suppliers are the risks likely to have a high impact on the disruption of the vaccine supply chain. Our approach provides a useful tool for evaluating the resilience of the vaccine supply chain and identifying the critical risks. It can be used by decision-makers to mitigate the impact of disruptions and improve overall resilience of the vaccine supply chain.

This paper aims to identify the optimal locations for new fire stations in Isfahan city using multiple criteria decision-making (MCDM) methods and geographic information system (GIS) data. AHP, fuzzy AHP, and TOPSIS methods are used to identify potential locations for new fire stations based on decision criteria such as population density, proximity to main roads, distance from existing fire stations, density of hazardous materials, radius of the fire brigade, traffic network, land use, age of buildings, and potential for danger. The candidate locations for new fire stations are ranked according to these criteria, and the results are validated by the Statistics and Strategic Planning Unit of the Isfahan Central Fire Department. The fuzzy AHP results indicate that districts 8, 9, and 4 have the highest priority for new fire stations, respectively. Sensitivity analysis of the criteria weights reveals that district 8 has the highest priority, while districts 12 and 15 have the lowest. This study also provides managerial insights, including the need to modify municipal building regulations and relocate dangerous sites to improve fire safety in Isfahan city. The proposed approach provides a useful tool for decision-makers to identify optimal locations for new fire stations and improve fire safety in urban areas.

As competition among marketing companies and retailers intensifies, segmenting customers and recommending suitable products has become a critical strategy for maintaining a competitive edge. With the rapid growth of online shopping, customers often make purchasing decisions based on their needs and desires. Salespeople play a crucial role in influencing customers, making a product recommendation system essential. Such a system has various applications and can also encourage customers to purchase additional products. In this study, we present a method for recommending products to customers that utilizes the K-means clustering algorithm and the RFM (Recency, Frequency, Monetary) model to segment customers and make personalized product recommendations. To evaluate the performance of the proposed system, we conducted experiments using data collected from Digikala, an online shopping company. The results show that clustering based on the RFM features has better results for cluster number zero, which represents loyal customers. Therefore, to encourage these customers to purchase higher-priced goods, companies can offer special discounts to cluster number zero. Our approach provides a customer-centric solution for increasing sales and customer satisfaction.

In this paper, we study a production system that is subject to network failures and produces perishable goods. We assume that the system has preventive and corrective maintenance activities and can return defective items for rework. Our objective is to find the optimal production rate that minimizes the total cost of production, inventory, spoilage, and maintenance over a long planning horizon. We consider the uncertainty of machine failures and use discrete event simulation and ARENA.14 software to estimate the performance measures of the system. We also use data envelopment analysis to evaluate the efficiency of the system and identify the best scenario. The results show the effectiveness of our proposed model.

The increase in pollution and environmental issues, consequently raising concerns for organizations and society, has given rise to the new concept of "Green Innovation". Green Innovation is a subset of innovation that enhances environmental quality and optimizes resource utilization. The aim of the present research is to examine the relationship between Green Innovation Strategy and Green Innovation, with the mediating factors of Organizational Environmental Legitimacy and Green Organizational Identity. The current study is of a survey and correlational nature. The statistical population of the research includes 14 companies that produce hospital waste management devices. An equal number of 10 questionnaires were distributed to senior managers and production managers within these companies. Ultimately, 126 questionnaires were gathered, and hypothesis testing was conducted using the smart.pls software. The results revealed that green organizational identity and organizational environmental legitimacy mediate the relationship between green innovation strategy and green innovation. Managers must endorse the role of green organizational identity and organizational environmental legitimacy within their companies and initiate the development of a green innovation strategy. Managers need to understand that having a strategy is not sufficient, and they should directly enhance the performance of green innovation. They should pursue robust approaches to fostering green organizational identity and, using it, seek to acquire organizational environmental legitimacy.

In the era of globalized markets, international standards play a crucial role in the development of business processes and ensuring adherence to export and import regulations, efficiency, and safety measures. Actively engaging in the formulation of international standards and harmonizing assessment methodologies can lead to enhanced product competitiveness, cost reduction, and the infusion of cutting-edge global knowledge and technology into a country. The objective of this research is to identify strategies in various domains of the standardization and quality management system, aiming to achieve the vision of "Development, Progress, and Social Welfare through Standards" in Iran. The research employs a qualitative approach and utilizes the research synthesis method. The research population encompasses all higher-level laws and documents of the Islamic Republic of Iran, international documents, and strategic documents from other countries pertaining to standards and quality. A systematic selection process led to the identification of 16 documents based on predefined criteria, saturating the data collection. Thematic analysis, facilitated by "Max Quda" software version 17, extracted 18 strategies across three primary categories and 57 actionable policy directives within the framework of the "National Standards Organization of Iran." The outcomes of this study hold direct utility for senior managers within the Standard Organization, members of the Supreme Policy Council, and regulatory and inspection entities.

Roadside units are crucial elements of intelligent transportation systems that provide vehicle–vehicle and vehicle–equipment information communication. Due to the high cost of installation, the deployment of roadside units is the most critical. Aim of this study is developing a model to optimize of roadside units placement to achieve maximum coverage. A multi–objective mathematical model presented, based on the three main parameters. These parameters are traffic volume, incident rate and adjacency to important centers, which determine for alternative points. The maximum coverage problem is NP–hard. Consequently, conventional mathematical methods are not accurate for large scale problem. A meta–heuristic method based on the greedy algorithm was developed which conciders marking points as definitive–select or non–selectable. Result of the model were evaluated through testing of three scenarios, 200, 500 and 1000 meters coverage in District 5 of Tehran by using MATLAB and the best one, 1000 meters was chosen with 71% coverage. Observations showed the effect of various parameters such as equipment coverage radius, number of equipment and budget on the results of distribution. This algorithm makes it possible to solve the problem on a large scale by using the geolocation of the candidate points.

The redundancy allocation problem is to find an optimal allocation of redundant components by considering a set of different constraints. Solving these problems is of great interest to various researchers due to its high mathematical complexity. In this research, the satellite attitude determination and control system are studied, and its components are introduced. Then, the reliability and cost of this system are modeled and optimized using a mathematical approach based on redundancy allocation. The model studied in this research pertains to the configuration of a series-parallel system operating within the precise context of a satellite attitude determination and control system. This paper introduces a novel approach to modeling a bi-objective problem and optimizing it using an exact solution method. The mathematical model presented in this paper is a mixed integer non-linear programming (MINLP). In this research, an heuristic method executed in 7 steps has been employed to achieve an exact solution to the problem. Based on this approach, the optimal values for system reliability and cost are determined under various objective weighting schemes.

Fourth industrial revolution is rapidly changing technology, industry and patterns through increased communications and intelligent automation in the current century. It is crucial to conduct thorough research to determine the importance of dimensions and indicators in assessing the preparedness of Iran's industries for sustainability in Industry 4.0. The goal of this paper is to identify and determine the importance of the influential components on the organization's readiness to move towards the fourth-generation industry. This model should help the organizations and industries understand their industry 4.0 readiness status. In qualitative part of the study, we categorized the data to produce the initial codes, themes and axial codes by examining the theoretical foundations and receiving experts' comments. The result was extracting 60 initial codes and 6 themes. We then used the fuzzy Delphi method on the result of the poll. Experts unanimously voted in favor of 17 sub-criteria. Finally, we used fuzzy DEMATEL method to study the relationships between criteria and sub-criteria. According to this study, ‘functional readiness’ was the most effectible and ‘information technology readiness’ was the most affecting criteria. Among sub-criteria, ‘governmental and institutional laws’ and ‘workplace dynamics’ were identified as the most effectible cause and most affecting effect respectively.