Zohreh Zahedian, Mohammad Mahdi Nasiri,
Volume 25, Issue 3 (7-2014)
Abstract
In this paper, we develop a freight transportation model for railway network considering hazmat transportation issue. In the transportation system considered, different customers can request for carrying hazmat and non- hazmat boxes. It is assumed that the sequence of the trains in the network is known. The objective is assigning the non-hazmat boxes and hazmat boxes to wagons of the trains so that the transportation becomes safer. A zero-one integer programming model is presented that minimizes the cost of safe transportation. The model is solved using a new fuzzy approach.
Naghmeh Khosrowabadi, Rouzbeh Ghousi, Ahmad Makui,
Volume 30, Issue 2 (6-2019)
Abstract
With regard to the industry's development, occupational safety is a key factor in protecting the worker's health, achieving organizational goals and increasing productivity. Therefore, research is needed to investigate the factors affecting occupational safety. This research, based on the information gathered from the paint halts of one of the industrial units of Tehran, uses data mining technique to identify the important factors.Initially with Literature review to 2018, an insight into existing approaches and new ideas earned. Then, with a significant 5600 units of data, the results of the charts, association rules and K-means algorithm were used to extract the latent knowledge with the least error without human intervention from the six-step methodology of Crisp for data mining.The results of charts, association rules, and K-means algorithm for clustering are in a line and have been successful in determining effective factors such as important age groups and education, identifying important events, identifying the halls and finally, the root causes of major events that were the research questions.The results reveal the importance of very young and young age with often diploma education and low experience, in major accidents involving bruising, injury, and torsion, often due to self-unsafe act and unsafe conditions as slipping or collision with things. In addition, the important body members, hands and feet in the color retouching and surface color cabins are more at risk. These results help improve safety strategies. Finally, suggestions for future research were presented.
Olasunkanmi Akinyemi, Kazeen Adebiyi,
Volume 30, Issue 4 (12-2019)
Abstract
Safety has been established to maintaining and improving the productivity level of aviation industry with derivable benefits in terms of wealth and reputation. Despite, the investment in aviation; safety is generally recognized as an incurred cost, leading to compliance approach. This may be due to dearth of literature on generally agreed proactive safety performance indicator to justify the huge investment. This study therefore developed predictive models that evaluate runway safety investment strategies and predict the overall performance of the aviation system using System Dynamics stock and flow diagram. An interactive computer programme of the models was written using Java programming language. The set of dynamic equations for predicting number of runway accidents, preventions, monetary savings/losses and safety programme breakeven period were the safety performance measures. Runway safety intervention effectiveness factor and level of budget implementation were system policy parameters used to control the mechanism of the runway safety system. Relevant data were obtained from Federal Aviation Authority, Nigeria to validate the models. Twenty-nine runway safety quantities were identified. The dynamic equations for number of runway accident preventions and monetary savings/losses exhibited exponential growth while number of runway accidents, exhibit exponential decay. The results of the simulation runs showed no significant difference with real life situations; thus the models can serve as useful tools to effectively and efficiently manage the behaviour and performance of runway safety programme.
Mahdi Rahimdel Meybodi,
Volume 32, Issue 3 (9-2021)
Abstract
Today, one of the most important concerns of production units is the evaluation, analysis and risk management in the production process. In this research, based on the fuzzy control approach, a scientific and logical method for evaluating, analyzing and managing risk in the production process is presented. Based on the proposed method of this research, after identifying the risks in the production process of products, according to the three criteria of failure severity, probability of failure and detectability, as well as using the best - worst method, evaluation and determining the importance of these risks, is done. Then, with the fuzzy rules, fuzzy inference system is designed. The final result is the classification and prioritization of identified risks. Finally, the proposed research model for an applied sample is used and its final results are analyzed.
Sara Motevali Haghighi, Sima Motevali Haghighi,
Volume 33, Issue 2 (6-2022)
Abstract
In today's world, COVID-19 pandemic has affected many organizations. Pandemic issues have created financial and social problems for businesses. Crisis and risk management have a significant impact on reducing consequences of pandemics. Rapid response to risk enhances the performance of organizations in times of crisis. Therefore, a framework to provide risk treatment in a pandemic crisis seems essential. To do this, this paper presents a framework to identify risk factors posed by pandemics. In this regard comprehensive risk factors by considering sustainability concept are illustrated for university. Then, identified risk factors are evaluated by best–worst methodology (BWM) and then the important risks are recognized. Using the importance of risk and the strengths and weaknesses of the business, solutions to reduce the impact of risk are suggested to managers. The results of this paper can be used in order to enhance resiliency of the organization in front of the pandemics from social and financial viewpoints.
Pardis Roozkhosh, Amir Mohammad Fakoor Saghih,
Volume 35, Issue 3 (9-2024)
Abstract
The reliability of each component in a system plays a crucial role, as any malfunction can significantly reduce the system's overall lifespan. Optimizing the arrangement and sequence of heterogeneous components with varying lifespans is essential for enhancing system stability. This paper addresses the redundancy allocation problem (RAP) by determining the optimal number of components in each subsystem, considering their sequence, and optimizing multiple criteria such as reliability, cost uncertainty, and weight. A novel approach is introduced, incorporating a switching mechanism that accommodates both correct and defective switches. To assess reliability benefits, Markov chains are employed, while cost uncertainty is evaluated using the Monte-Carlo method with risk criteria such as percentile and mean-variance. The problem is solved using a modified genetic algorithm, and the proposed method is benchmarked against alternative approaches in similar scenarios. The results demonstrate a significant improvement in the Model Performance Index (MPI), with the best RAPMC solution under a mixed strategy achieving an MPI of 0.98625, indicating superior model efficiency compared to previous studies. Sensitivity analysis reveals that lower percentiles in the cost evaluations correlate with reduced objective function values and mean-variance, confirming the model's robustness in managing redundancy allocation to optimize reliability and control cost uncertainties effectively.
