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• A model was introduced using meta-synthesis and ISM to help analyze ICFs in industrial workers. • ISM is quite applicable to represent the cause and effect relationships between ICFs. • Lack of alertness due to mental overload and lack of person's resilience were the most influential ICFs. Most of the incidents including near misses are attributed to human unsafe acts. An available means for preventing incidents is to recognize "accident prone" workers in a system as the last layer of working system. This study was conducted to recognize individual cognitive factors affecting unsafe acts among Iranian industrial workers as well as finding hierarchical relationships among the factors. This study was mainly performed in two phases including a seven stage meta-synthesis as a basic qualitative approach to extract the effective factors on unsafe acts of workers in industries and Interpretive Structural Modeling (ISM) as an appropriate approach to modeling the factors hierarchically with a glance on their relationships. Twenty experts partook in this study from different universities and industrial companies in Iran to complete the matrices used in ISM model. Fifty-one papers were included out of which 10 dimensions were extracted as the main dimensions affecting unsafe acts individually. Kappa indicator was 0.69 indicating valid status of agreement for the extracted items. Lack of alertness due to mental overload and lack of individual's resilience were identified as the driving factors. The factor of difficulties in remembering work-related information had the characteristics of both independent and linkage clusters. The study provided a hierarchy of factors influencing unsafe acts; hence, the hierarchy could help all employers, industrial managers and even workers themselves to make a better decision when predicting workers' possible unsafe acts. [ABSTRACT FROM AUTHOR]

Performance assessment of Iranian petrochemical companies based on the H3SE performance excellence model is the purpose of this paper. Reaching this goal, different aspects of the sustainable excellence model and its indices have been introduced, and through Multiple Attribute Decision-Making (MADM) approaches, Iranian petrochemical companies were assessed and ranked. Since the results of MADM are not panacea for all decision making problems and the questionnaire self-assessment approach is not rigorous enough, different techniques have been involved for compensation. In the following, the convergence of MADM rankings has been compared. The findings signify that processes management, leadership, social environmental accountability and staff results are of relative importance in H3SE performance assessment. Moreover, Ethylene Gharb, Zagros, and Bandar Imam companies have the highest rankings. Finally, ranking sensitivity was analyzed. Since the data were collected through questionnaire self-assessment approach, the reliability of this assessment may be doubted. [ABSTRACT FROM AUTHOR]

Highlights: [•] The high rate of incidents in Iran’s quarries, is the necessity of safety risk assessment. [•] This paper develops a new approach of safety risk assessment and adjustment in quarries. [•] Traffic accidents, cutting wire rupture and rock fall were the three greatest risk resources. [•] Total amounts of risk was 31.8 and 11.7 before and after adjustment, respectively. [•] Total risk adjustment risk ratio of 63.3%, shows the importance of risk management. [ABSTRACT FROM AUTHOR]

Highlights: [•] This paper addresses a new clustering-classification method for classifying the severity of road accidents in Iran. [•] k-Means and some classification methods are used for running numerical experiments. [•] Some activation functions have been used for training the neural networks. The results of them are compared together. [•] Also, the accuracy of classification is compared by using different approaches in k-mean. [•] Silhouette technique was used to confirm the validity of the clusters. [Copyright &y& Elsevier]

Abstract: The conventional deterministic approach based (DAB) methods are simple and widely used to determine an adequate chain pillar size in coal mines where geological settings, coal characterizations and mining methods have been explored. It is evident that such deterministic methods have some intrinsic limitations in handling uncertainties in material properties, non-regular geometries and different mining operations. In the deterministic stability analysis of a chain pillar, the safety factors as well as all input parameters are deterministic. Although, these parameters generally exhibit uncertainty and should lead to a probabilistic expression for the safety factor. The probabilistic analysis provides a confidence interval to express the reliability of chain pillars stability. In this paper, safety factor is defined as a probabilistic function and the failure probability of designed chain pillar of Tabas coal mine is then evaluated using the First Order Second Moment (FOSM) and the Advanced Second Moment (ASM) methods. The results of the probabilistic stability analysis show that the confidence interval for designed pillars with both mentioned methods applied are similar and their values vary from 84% to 88%. The results of such analyses can be used as a basis for decision-making about the size of chain pillars and reduce the risk of pillars stability as well as the uncertainties. However, a trade-off between cost is essential for making the final decision. [Copyright &y& Elsevier]

Abstract: Flyrock is one of the most hazardous side effects of blasting operation in surface mining. This phenomenon can be considered as the main cause of casualties and damages. Inaccuracy of the available flyrock prediction empirical methods has caused utilizing of new methods such as fuzzy systems. In this paper a Mamdani fuzzy model was developed to predict flyrock in the Gol-E-Gohar iron mine of Iran. In this regard, a database including 490 datasets of the mine blasting operation was prepared from which about 20% was kept for testing the models. Performance of the fuzzy model was compared with that of the conventional statistical method. It was observed that efficiency of the developed fuzzy model is much better than the statistical model. Also, sensitivity analysis showed that powder factor and rock density are the most and least effective parameters on the flyrock, respectively. [Copyright &y& Elsevier]

• Understanding drivers' mental patterns is fundamental in recognizing the reasons for accidents. • The views of rural drivers' regarding safety and accidents were analyzed using Q-methodology. • The Q methodology is known as a link between qualitative and quantitative approaches. • Drivers' perceptions of the factors affecting accidents are not always the same as the results achieved by RSI. Recognizing the factors affecting road accidents, especially in developing countries, is an important step in increasing the level of road safety and decreasing losses. Studies on the factors affecting road accidents in Iran mostly concentrated on the views of road engineers and the police, while the views of drivers, one of the main users of roads, received less attention. Understanding drivers' mental patterns could be very effective in recognizing the reasons for accidents. In this paper, the Q factor analysis was used to determine drivers' mental patterns. Q methodology is a technique that enables the investigator to recognize and classify perceptions and beliefs as well as categorize groups of people on the basis of their perceptions. The main objective of this technique is to clarify different thought patterns, not to count the numbers of people with different thoughts. Samples of rural drivers were chosen as the target community, and based on the Q-method, their propositions were prioritized. Finally, on the basis of Q-factor analysis, the mental patterns of drivers related to the factors affecting accidents were determined, and useful information was acquired in this regard. Drivers' perceptions of the factors affecting accidents differ from the results gained on the basis of safety inspections. Recognizing these patterns helps to correct the ideas of engineers and can also be used to correct the incorrect mental patterns among drivers regarding the reasons for accidents through training. [ABSTRACT FROM AUTHOR]