Showing 8 results for Fuzzy Logic
, , ,
Volume 2, Issue 1 (5-2012)
Abstract
Introduction: In addition to direct and indirect costs of occupational accidents imposing on production companies, they impact the productivity of labor, too. However, gaining more profits and having less costs is always the main concern among industrial managers. Considering safety measures can be effective way to reduce occupational accidents and costs as well as negative impacts on production systems.
.
Material and Method: In this paper, a risk assessment method using fuzzy and MATLAB software is presented to determine the safety level of production environments. The main parameters of this model include three items: accident probability, accident severity and current safety level. For this purpose, the statistical data of accidents and their causes published by Social Insurance Organization have been used in this study. Furthermore, expert judgments of safety and health professional have been used to determine the severity of accidents. In the fuzzy method, the Mamdani deductive fuzzy model has been adapted due to its easy applicability. Application of the model has been shown using a practical instance.
.
Result: The defuzzified value for RL is found to be 3.48. Linguistic risk level expression is 100% substantial high risk that is full membership for fuzzy average set.
.
Conclusion: The application of the proposed method can reveal which safety items and factors are most important in improving workers safety, and therefore decide where to concentrate resources in order to improve the safety of the work environment.
Z. Qorbali, P. Nasiri, A. Baqaei, S. M. R. Mirilavasani,
Volume 3, Issue 3 (12-2013)
Abstract
Introduction: Due to the presence of extreme hazard sources and high intrinsic risk in refineries and process industry sectors, different layers of protection are being used to reduce the risk and avoid the hazardous events. Determining Safety Integrity Levels (SILs) in Safety Instrumented Systems (SISs) helps to ensure the safety of the whole process. Risk Graph is one of the most popular and cost effective techniques to do so. Despite Risk Graph simplicity it’s a qualitative method which is highly subjective and suffers from interpretation problems that can lead to inconsistent or conservative SILs.
.
Material and Method: In this paper, Improved Risk Graph (IRG) method was presented and evaluated, and using Fuzzy Logic a novel approach namely Fuzzy Improved Risk Graph (FIRG) was suggested. In the proposed method consequence levels which were defined as qualitative terms were transformed into quantitative intervals. Having those numerical values, risk graph table was converted to a quantitative one. Finally, applying the presented approach and using three experts’ opinions and attributing weight factors, an ultimate numeric value was produced.
.
Conclusion: as a result of establishing the presented method, identical levels in conventional risk graph table are replaced with different sublevels that not only increases the accuracy in determining the SIL, but also elucidates the effective factor in improving the safety level and consequently saves time and cost significantly. The proposed technique has been employed to develop the SIL of Tehran Refinery ISOMAX Center. IRG and FIRG results have been compared to clarify the efficacy and importance of the proposed method
F. Golbabaei, A. Azar, M. Ganji Kazemian,
Volume 4, Issue 2 (7-2014)
Abstract
Introduction: Air health is an important environmental issue which has been endangered in recent years due to application of advanced technologies used for improving the financial welfare and relative prosperity of humans. Making use of pollution control systems and refinement methods are some general ways to control environmental pollution. Since several different techniques of control, each with its advantages and disadvantages are employed in order to mitigate the spread of air pollution, the aim of current study was to design a fuzzy multi-attribute decision making model to select the most appropriate air pollution control equipment in Mashhad Shargh Cement Company.
.
Material and Method: After identifying the desired industry and also the production process, all factors affecting decision-making process including environmental factors, technical factors and economic factors were considered by utilizing Fuzzy Analytic Hierarchy Process method. Importance weight of these criteria was calculated and subsequently the priority of model choices were also determined using this approach.
.
Result: Among main criteria of the model, economic criteria was identified as the most important factor influencing the selection of the type of air pollution control equipment, with the wight of 0.555. Environmental and technical factors with weighting of 0,286 and 0,159 also gained the next priorities, respectively. Final weights of Electro filter, Baghouse and Hybrid filter technologies were calculated 0.256, 0.415 and 0.329 in cement mill unit and 0.291, 0.374 and 0.334 in material grinding and furnace unit, respectively.
.
Conclusion: Finally, the proposed model that is based on the Fuzzy Analytic Hierarchy Process indicates that the Baghouse Technique is the most appropriate technique for the purpose of dust filtration in major sources of air pollution spread in Shargh Cement Company.
Hedayat Noori, Morteza Cheraghi, Aliakbar Eslami Baladeh,
Volume 9, Issue 3 (9-2019)
Abstract
Introduction: Evaluating environmental risks in the oil and gas industry is essential to prevent irreparable damage to the environment. Using classical methods for prioritizing environmental risks does not achieve high-reliable results. Therefore, the aim of this study is to minimize the limitations of classical methods in a typical oil and gas production zone, by using fuzzy logic and Multi Attribute Decision Making (MADM) approach.
Material and Methods: After forming an identification and assessment team including experienced experts from different organizational units in a region of exploitation of oil and gas, values of each risk factor (likelihood of occurrence, severity and detectability) related to identified environmental risks are determined according to their qualitative opinions represented by linguistic variables. Relative weights of the risk factors are calculated by applying the group Analytic Hierarchy Process (AHP) in a fuzzy environment on expert opinions. Then, fuzzy aggregation in the linear form by considering the weight of the risk factors and a method that is developed based on the center of gravity are employed in evaluation and ranking of the risks.
Results: In this study, the severity factor has the most important contribution in risk assessment compared to the other risk factors, since it has the highest relative weight. Raw sewage aspect resulted from absence of appropriate treatment system has the highest priority and spilling over of acid that is caused by chiller cleaning stands at the second position in the identified environmental risks.
Conclusion: The results demonstrate that although the proposed methodology requires greater time than classical methods, it is able to determine the risk ranking more practically because of minimizing the limitations of classical methods: high sensitivity to judgmental errors, considering some risks in the same index group and ignoring uncertainty in experts’ opinions. Proposed method is a proper alternative for classical environmental risk assessment technique, and capable of prioritization and evaluation risks in terms of safety and health.
Mohsen Mahdinia, Mostafa Mirzaei Aliabadi, Ahmad Soltanzadeh, Ali Reza Soltanian, Iraj Mohammadfam,
Volume 11, Issue 2 (6-2021)
Abstract
Introduction: Safety situation awareness is an important element affecting operator's reliability and safety performance, which is influenced by various variables. Identification of these variables and their relationship will play a major role in optimizing control measures. The present study was conducted for this purpose.
Material and Methods: This study was based on the situation awareness, expert’s opinions and use of a Fuzzy multi-criteria decision-making method. Triangular fuzzy numbers was used to quantify the experts' judgments and to reduce the errors that result from theirs’ subjective evaluation on the relationships between the variables.
Results: The results showed that the studied organizational variables together with "safety/g knowledge" and "experience in job/specific task” are the most important predictive variables of situation awareness. Among the organizational variables, "Organizational Safety Attitudes", "Safe System Design" and "Education" are the most important determinants of safety situation awareness.
Conclusion: Fuzzy logic was used to aggregate expert opinions to determine the most important variables affecting situation awareness and their cause-effect relationships. Organizational variables are the main determinants of situation awareness. To improve situation awareness, the best results are obtained by modifying effective root variables, i.e., organizational variables and some individual variables.
Marzieh Abbasinia, Omid Kalatpour, Majid Motamedzade, Ali Reza Soltanian, Iraj Mohammadfam, Mohammad Ganjipour,
Volume 12, Issue 2 (6-2022)
Abstract
Introduction: Emergencies are unforeseen and unpredictable situations. In these situations, people’s performance is affected by various factors that cause stress. People’s performance in such situations can also affect human error probability. The purpose of this study was to evaluate human error in emergency situations based on the fuzzy CREAM and Fuzzy Analytical Hierarchy Process (FAHP).
Material and Methods: This descriptive-analytical study was performed in a petrochemical industry in Markazi province in 2019. The FAHP was used to prioritize emergency situations. To evaluate human error in these conditions, the weights of Common Performance Conditions (CPC) was determined using Analytical Hierarchy Process (AHP) method. Human error probability was calculated using a fuzzy CREAM method in the most important emergency situations.
Results: The results of the FAHP showed that “Hydrogen leak from the cylinder joints in the olefin unit” was the most important emergency. The highest relative weight was related to crew collaboration quality (0.06) in the emergency situation.
Conclusion: This method can also be used to identify the important factors in human error occurrence and high weighted CPCs and plan to control them.
Mehri Mangeli Kamsefidi, Alireza Shahraki, Faranak Hosseinzadeh Saljooghi,
Volume 12, Issue 4 (12-2022)
Abstract
Introduction: Failure Mode and Effects Analysis (FMEA) is a structured way to find and understand the states of a system’s failure and to calculate the resulting effects. In this method, which has been criticized by many researchers, the risk priority number is obtained for each failure mode based on the multiplication of the three parameters of occurrence (O), severity (S) and detection (D). In order to overcome the disadvantages of the traditional method of FMEA, such as ranking the failure and weighting the parameters, this research proposes a model in the fuzzy set.
Material and Methods: The model proposed in this paper is a nonlinear model for weighting the parameters of the FMEA and the revised TOPSIS method for ranking the failures, which is used for the first time to improve the FMEA method.
Results: The proposed model was presented in the Copper Complex of Shahr-e-Babak to assess safety risks. Based on the results of the study, it was found that in this proposed model, the weights of severity and detection were 0.479 and 0.186, respectively, and the results of the ranking showed that the risks of falling from height and getting stuck between objects had the highest and lowest priorities, respectively.
Conclusion: In the proposed model, based on Logarithmic Fuzzy Preference Programming and the revised TOPSIS method, the definite weights of the parameters were presented without any fuzzy number ranking and risk ranking with more criteria, respectively. Therefore, the proposed model has a higher ability compared to the traditional FMEA, and its application can be recommended to determine the ranking of risks.
Raheleh Pourhosein, Saeed Musavi, Yahya Rasoulzadeh,
Volume 14, Issue 1 (3-2024)
Abstract
Introduction: The accurate evaluation of error probability and risk is important. Accordingly, this Comparative study was conducted to evaluate the risk of human error in emergency situations using SLIM and Fuzzy SLIM techniques in fierfighting tasks.
Material and Methods: This cross-sectional and descriptive-analytical study was conducted among 12, using Fuzzy SLIM and SLIM techniques. 39 sub-tasks were studied in 4 phases (Awareness, Evaluation, Egress and Recovery). Considering the advantages of the Fuzzy SLIM method, fuzzy logic was used in weighting of performance shaping factors (PSF). Excel software was used to calculate the probability of error. Also, correlation and kappa statistical tests were used for data analysis in SPSS software.
Results: The mean and standard deviation of human error probability in different sub-tasks of firefighting in SLIM and Fuzzy SLIM methods were 0.095357 ± 0.026193 and 0.06490 ± 0.051748, respectivly. In 48.7 percent of the sub-tasks, the probability category of human error and the assessed risk were the same; however, in 89.7 percent of the sub-tasks, the estimated level of risk was the same in both methods. Correlation test showed that the correlation coefficient of error probability values between the two methods was 0.32, which indicated a moderate correlation in this regard. Additionally, the results of kappa statistical test for the estimated level of risk showed that there is a high agreement between Fuzzy SLIM and SLIM (P value <0.05).
Conclusion: The results of the study indicated meaningful agreement and a moderate correlation between Fuzzy SLIM and SLIM. Therefore, due to the relatively high accuracy of Fuzzy logic methods, and also the long steps of implementing the SLIM method, the Fuzzy SLIM method can be a good alternative to this method.
