Sha-aban Ali Hoseinpour
Abstract
In order to be competitive, it is an obligation for companies and service centers to identify, evaluate and control risk and environmental aspects of their activities. Due to technical and financial constraints, it is required to prioritize the risks and control measures with greater accuracy. In the ...
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In order to be competitive, it is an obligation for companies and service centers to identify, evaluate and control risk and environmental aspects of their activities. Due to technical and financial constraints, it is required to prioritize the risks and control measures with greater accuracy. In the framework of the HSE-MS system, for the first time, risk evaluation of industrial activities and services, has been implemented using fuzzy Quality Function Deployment. In this approach, characteristics such as mutual effects of different risks and environmental aspects of industrial activities, risk estimation, and positive and negative aspects of activities have been considered in RPN computation. The application of fuzzy logic reduces the ambiguity of the linguistic parameters. In the case study of the Iran barrit falat it appears, that operation and impact of risk assessment methods and environmental aspects of activities, evaluation criteria and the priority actions has been performed more precisely in comparison with traditional methods of risk assessment.
Taha-Hossein Hejazi; Shahin Behboodi; Fatemeh Abbaszadeh
Abstract
Generally, the safety management system (SMS) introduced in 1980 focuses on reducing the risk of potential injuries and fatalities in the construction industry. The key to considering the challenges of project safety management and risk assessment in the construction industry as a hazardous industry ...
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Generally, the safety management system (SMS) introduced in 1980 focuses on reducing the risk of potential injuries and fatalities in the construction industry. The key to considering the challenges of project safety management and risk assessment in the construction industry as a hazardous industry because of its peculiar nature is important. In line with this, this article aims at employing decision-making techniques to ensure the safety requirements of construction projects. Additionally, a questionnaire under fuzzy environments for identifying the candidate locations and strategies associated with each specific location was conducted. Also, the Empirical Bayesian (EB) approach has been considered to estimate the expected frequency of accidents. The objective of the novel proposed approach is to find the optimal safety project selection with respect to the economic indicators and time value of money under uncertain circumstances. For this purpose, a mathematical optimization model is proposed, and its efficiency is demonstrated by a numerical case study. The results of optimizing the mathematical model indicate that by modifying two factors, namely the safety level and uncertainty coefficient, several scenarios can be explored for cost reduction and a decrease in the number of construction projects. By maintaining a constant safety level of 1.37 (as determined by industry experts) and increasing the uncertainty coefficient from 0 to 0.2, costs decrease by a factor of 1.7, accompanied by a decrease in the number of construction projects by one unit. Furthermore, when the uncertainty coefficient is held constant at 0.2, costs can be reduced up to four times by reducing the safety level from 1.37 to 1. This decision-making framework can significantly contribute to minimizing building accidents and enhancing safety in construction projects.
Sajed Rastbin; Mehrdad Gholami Shahbandi; Pouya Soudmand
Abstract
Fast growth of motorized transportation infrastructures in the cities is a consequence of the urbanization process. Despite the undeniable benefits of the developments, some unwelcome social-environmental damages have been occurred. On top of the list, the movements of the pedestrians and their participation ...
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Fast growth of motorized transportation infrastructures in the cities is a consequence of the urbanization process. Despite the undeniable benefits of the developments, some unwelcome social-environmental damages have been occurred. On top of the list, the movements of the pedestrians and their participation in social activities have dramatically reduced as a result of the vehicles dominancy. Pedestrianization and walking-friendly schemes are the key answer to preserve the valuable element of the urban lifestyle. This need motivated the researchers to study and propose mathematical methods to model the dynamics and behavior of the pedestrians in response to their surroundings. However, most of the models in the literature are suitable for limited small-size area and cannot be applied for a large scale urban zone. In this paper, a fuzzy macroscopic pedestrian assignment model is proposed which is applicable for a large scale network and useful for urban master plans as a decision making framework. In addition, a bi-level mixed integer programming model is presented to optimize the pedestrian walking network via selecting some projects on the network, considering the behavior of the pedestrians. Finally, the problem is solved for a large scale pedestrian network in the city of Tehran. The results show the efficiency of the algorithm where spending half of the maximum possible cost has led to a welfare gain of 82.6 percent. The problem was efficiently solved within 12.5 days which is fairly acceptable for the strategic planning of such a large scale network. The numerical results verify the necessity of the model for urban master plan horizon.