Likelihood Of Accidents Research Articles

Risk analysis of gold processing in artisanal and small-scale gold mining in Bolaang Mongondow Regency, North Sulawesi, Indonesia

Gold processing at artisanal and small-scale gold mining (ASGM) in Indonesia is inherently risky due to the high severity and likelihood of accidents causing serious injury. The objectives of this study were to identify hazards, assess risks, and determine risk control measures in the ASGM location at Imandi Village, East Dumoga District, Bolaang Mongondow Regency, North Sulawesi Province. The method used was Hazard Identification Risk Assessment and Risk Control (HIRARC). The determination of work stages and identification of hazards was carried out through observation at 14 ASGM units and interviews with 14 informants consisting of 6 mining workers and 8 ASGM business owners. The risk assessment was carried out by observing and interviewing 8 experts as informants selected from health and environmental scientists, various offices of the Government Bolaang Mongondow Regency, and non-government institutions. The results showed that the stage of gold processing work in ASGM consists of 13 sources of hazards that can pose 16 risks. The obtained risk assessment results showed that 19% were low risk, 31% moderate risk, 25% high risk, and 25% very high risk caused by exposure to mercury through the gold ore burning process with a risk value of 25. The identified risk control measures were PPE (personal protective equipment) 43%, administrative controls 14%, engineering controls 14%, substitution 21%, and elimination 7%. Realistic risk controls that can be applied in ASGM are a combination of administrative controls and PPE.

A Comparative Analysis of Hazard Analysis Methods for Sustainable Energy Development

This paper discusses the potential risks and dangers associated with the oil and gas industry. This industry is essential for meeting energy needs and generating foreign exchange income, but it also poses significant risks, such as accidents, fires, explosions, and environmental contamination. Neglected work and safety procedures can result in catastrophic economic losses and have far-reaching effects on society and the environment. The study describes three significant accidents in the industry that were caused by internal and external factors. In order to comprehend the causes of these incidents, this study suggests three risk analysis techniques: Failure Mode and Effect Analysis, Fault Tree Analysis, and Hazard and Operability Study. The paper asserts that by employing these methods, incident data can be obtained to enhance security and reduce the likelihood of future accidents. Overall, this study emphasizes the significance of safety measures, environmental management, and total quality management in the oil and gas industry in order to avoid fatal outcomes and environmental impacts.

Experiment design for Stress data collection while driving in a simulator

The principal objective of this study is to investigate the impact of perceived stress on traffic and road safety. Therefore, we designed a study that allows the generation and collection of stress-relevant data. Drivers often experience stress due to their perception of lack of control during the driving process. This can lead to an increased likelihood of traffic accidents, driver errors, and traffic violations. To explore this phenomenon, we used the Stress Perceived Questionnaire (PSQ) to evaluate perceived stress levels during driving simulations and the EPQR questionnaire to determine the personality of the driver. With the presented study, participants can categorised based on their emotional stability and personality traits. Wearable devices were utilised to monitor each participant's instantaneous heart rate (HR) due to their non-intrusive and portable nature. The findings of this study deliver an overview of the link between stress and traffic and road safety. These findings can be utilised for future research and implementing strategies to reduce road accidents and promote traffic safety.

Analysis of influencing factors and anti-pinch measures for door pinch accidents in conventional public transportation

A safe and convenient bus service is important for improving the bus mode share. However, during the morning and evening peak travel periods, hurrying passengers may get caught in closing doors when they squeeze into a bus. We conducted a survey of bus door pinch accidents that occurred in Harbin, China for the past five years to investigate the factors contributing to such accidents. A total of 1465 samples were collected to explore the effects of passenger age, gender, and other factors on pinching accidents. The results of the logit regression analysis revealed that all six influencing factors significantly affect the occurrence of door pinch accidents. Juveniles, females, and slow-moving people are more susceptible to pinch accidents. Additionally, situations such as door congestion, rushing to get on or off the bus, and inappropriately located cameras increase the likelihood of such accidents. To further investigate the effects of variables on different scenarios, the accidents were classified into four categories based on their occurrence process and object and analyzed using multiple logistic regression. The results show that juveniles and females are more likely to be involved in accidents in which objects are pinched, slow-moving people are more prone to be pinched while boarding and rushing to get on or off the bus, and congestion at the doors increases the probability of all four types of pinch accidents. Therefore, we recommend modifying the door position, eliminating the front door seat, and adjusting the handrail distribution to alleviate door congestion. Moreover, the door-closing warning sound must be amplified to remind passengers that the door is about to close, potentially reducing the number of pinching accidents caused by rushing to get on or off the bus.

Proposal for Modification of the Syllabus for Ultralight Aircraft Pilot's Training

This article proposes modifications of the basic training syllabus for ultralight aircraft pilots based on the statistical data and analysis of ultralight aircraft accidents in the Czechia and Slovakia between 2016 to 2021. The article gives an overview of the current state of ultralight aviation in both countries and its current regulations, focusing on the need for increased safety measures. The article analyses existing accident data and identifies the causes of accidents, including human factors, equipment failure and other environmental factors. Based on this analysis, training modifications are proposed to improve pilot knowledge and skills, strengthen safety procedures and protocols, and reduce the likelihood of accidents. The proposed changes include an increase in training hours and practical experience focused on emergency procedures, flight parameters, and weather conditions. The results of this study contribute to ongoing efforts to improve the safety of ultralight aviation and inform and support about policy decisions regarding training requirements and regulatory frameworks.

Оценка эффективности спиралевидной разметки на кольцевых пересечениях автомобильных дорог

The results of a number of foreign studies recommend the application of spiral markings to ensure a higher level of safety at roundabouts of medium and large diameter highways. In a number of cities of the Russian Federation, these recommendations were implemented with the introduction of new traffic management schemes using spiral marking of traffic lanes. However, there is no objective data confirming the effectiveness of these measures in Russia. The aim of the study was to evaluate the effectiveness of spiral markings according to two criteria – the number of road accidents and traffic violations at roundabouts before and after the reorganization of traffic. The information was obtained from the traffic police and from video surveillance of individual sections of roundabouts. As a result of the study: 1) the hypothesis of a decrease in the number of accidents and the assertion that new traffic management schemes (spiral markings) by themselves provide greater traffic safety at roundabouts are refuted; 2) it is revealed that drivers tend to violate the requirements of spiral markings, which increases the likelihood of accidents; 3) it is concluded that new traffic management schemes can have a positive impact on road safety only when engineering measures are implemented to physically separate traffic flows on the ring roadway and reduce the speed of vehicles at the entrances and exits of roundabouts. The results of the work revealed promising areas for further research: to study the relationship between the trajectory of vehicles, their location from the point of view of certain intersection sites, spiral markings, characteristics of traffic flow (speed, density, congestion, flow composition), as well as weather condi¬tions. The identification of such links will allow us to evaluate the effectiveness of spiral marking and draw conclusions about the expediency of its further use at roundabouts in the territory of the Russian Federation.

Utilizing Neutrosophic Logic in a Hybrid CNN-GRU Framework for Driver Drowsiness Level Detection with Dynamic Spatio-Temporal Analysis Based on Eye Aspect Ratio

Driver drowsiness has been identified as a major cause of roadway accidents globally. Efficiently determining the extent of drowsiness can greatly enhance preventive measures. This study proposes a novel approach, combining convolutional neural networks (CNN) and Gated Recurrent Units (GRU) to dynamically evaluate both the presence of drowsiness and its severity based on the Eye Aspect Ratio (EAR). By bridging spatial features extracted by CNNs with temporal sequences through GRU, our model offers a robust and real-time assessment of drowsiness levels, paving the way for enhanced safety measures in vehicular systems. Incorporating Neutrosophic Logic enables a more robust representation of uncertainty and ambiguity in the data and enhances the accuracy of driver drowsiness level detection within the Hybrid CNN-GRU framework. The model’s hybrid CNN-GRU structure combines CNN layers to extract spatial information from Human eye Images and GRU units to represent temporal correlations between frames. In-car cameras and sensors must be integrated to implement the suggested system in real-time and enable continuous driver behavior monitoring. The system alerts early warnings and takes action when drowsiness is detected, lowering the likelihood of accidents caused by weary drivers. The CNN-GRU hybrid architecture accurately detects fatigue during real-time driving. Performance metrics, including accuracy, recall, and F1-score, are provided for comparative research utilizing baseline models. Model behavior may be understood by visualizing tiredness detection and carefully examining false positives and negatives. The proposed CNN-GRU framework outperforms traditional methods such as SVM, KNN, and BPNN by achieving a significantly higher accuracy of 99.5%. It increases the recognition of driver tiredness by proposing a trustworthy and adaptable hybrid CNN-GRU deep learning system. This project is implemented in Python; it offers a practical and versatile solution for real-time driver drowsiness level detection. The proposed technology has the potential to dramatically increase traffic safety by sending out early warnings and taking steps to lessen the risks related to driver fatigue.

Using e-scooters: An easy way to get home or a nightmare? An orthopedic perspective on e-scooter accidents.

The percentage of e-scooter use quickly escalated in our community due to its convenience, low cost, and eases of use. The number of accidents causing high-energy traumas has also increased. This study aims to describe the demographic char-acteristics and fracture patterns of patients admitted to the emergency department following an e-scooter accident and to identify common, correctable factors that increased the likelihood of accidents. Between January 2022 and August 2022, 43 patients (20 females and 23 males) who were admitted to the emergency department after an e-scooter accident and developed extremity fractures were included. The patients were divided into 2 groups those treated surgically and conservatively. Parameters such as the time of the accident, education level of the user, alcohol use, e-scooter malfunction, and compliance with traffic rules were evaluated. Accidents that led to treatment by surgery mostly occurred between 11 pm and 7 am. Surgically treated patients were mostly high school graduates. Alcohol use and recreational scooter use rates were statistically higher in the operated patients when compared to patients who were treated conservatively. The number of patients who reported a malfunction in the e-scooter was significantly lower in the operated group than in the conservative group. The rates of accidents due to non-compliance with traffic laws, driving at full speed of the e-scooter, use on the driveway, and presence of wet ground at the time of the accident were higher in the surgically treated patient group. Surgically treated patients also had a higher rate of being 1st time e-scooter users. Although governments have introduced many regulations regarding e-scooter use, the current situation seems insufficient in solving the problem. E-scooter users should be further educated about the associated risks. Authorities should tighten their supervision of scooter rental companies and drivers. Nighttime usage conditions should be reviewed, and the use of alcohol should be controlled. The use of helmets should be mandatory. If such regulations are tightened, accident rates can be reduced or high-energy impacts from existing accidents can be avoided. The results suggest that experienced, slow, non-alcoholic, and rule-abiding drivers require less operative treatment. This article will hopefully raise awareness and improve e-scooter regulations.

Improved management practice and process hazard analysis techniques for minimizing likelihood of process safety incidents in Taiwan

In Taiwan, process safety accidents often occur despite the prior implementation of process hazard analysis (PHA). One of the main reasons for this is the poor quality of the PHA process; with the main hazards not being properly identified, or properly controlled. Accordingly, based on the findings of 86 process safety management (PSM) audits, dozens of post-accident site resumption review meetings, and hundreds of PSM review sessions, this study examines the main deficiencies of management practice and PHA implementation in Taiwan, and presents several recommendations for improved PHA assessment techniques and procedures. The study additionally examines the feasibility for using PSM-related information, such as process safety information and process incident information, as a tool for further enhancing the PHA quality. Overall, the study suggests that, in addition to following the basic rules of PHA and requirements of OSHA (1992),management in Taiwan should also provide training in the enhanced assessment techniques proposed herein and take active steps to incorporate PSM information into the PHA framework in order to improve the general quality of PHA and reduce the likelihood of process safety accidents accordingly.

Improving the Safety of Operation of Overhead Cranes with Welded Modular Construction Based on the Analysis of Their Accidents

Introduction. The article presents an analysis of the destruction of welds that occurred during the operation of modular overhead cranes. Measures are proposed to prevent the occurrence of such defects in the future, reduce the likelihood of accidents and improve the safety of operation of overhead cranes with a welded modular construction. The relevance of the work is due to the fact that in the Russian Federation approximately 65% of the lifting cranes registered with Rostechnadzor have fulfilled the standard service life.The work objective is to improve the safety of operation of modular overhead cranes and the reliability of their welded metal structures. Achieving the objectives of the work, based on the analysis of the destruction of metal structures of overhead cranes, a diagnostic map of welded joints of metal structures of end beams with modules of travelling wheels of overhead cranes was compiled. The use of the proposed diagnostic card in a production environment will significantly improve the quality of diagnostics of welded joints.Materials and Methods. Investigations of accidents of load-bearing metal structures of cranes by methods of technical diagnostics of destruction of welds that occurred during the operation of overhead cranes of modular design have been carried out. This made it possible to develop a number of measures to prevent accidents of overhead cranes initiated by the destruction of their welded modular structures.Results. Based on the analysis of accidents, a diagnostic map of destructing welded joints of metal structures of end beams with modules of travelling wheels of an overhead crane has been compiled. The use of the proposed diagnostic card will increase the reliability of welded metal structures and improve the quality of diagnostics of welded joints in production conditions.Discussion and Conclusions. As a result of the analysis of structural failures of modular overhead cranes, a number of measures are proposed to prevent the formation of such defects, the occurrence of accidents due to them, and to improve the safety of operation of overhead cranes.

A methodical approach for knowledge-based fire and explosion accident likelihood analysis

An accident database is an excellent data source if appropriately leveraged along with domain expertise. However, a proper framework and tools are required to extract data from a database. The current work aims to develop such a framework by systematically introducing a unique approach to integrate three techniques. First, Natural Language Processing (NLP) is used to extract causal and contributing factors from an accident database. Second, an Interpretive Structural Model (ISM) establishes the interrelationship and hierarchy of the extracted factors. Third, a probabilistic method for quantitative reasoning and accident analysis is employed. This integrated approach is applied to the US Chemical Safety and Hazard Investigation Board (CSB) oil and refining (downstream) incident database to develop a generalized accident causation model. The model provides insight into the factors responsible for accidents (i.e., commonalities among casualties), interactions, and accident pathways. It can also be used to develop strategies for preventing accidents. The model is tested on ten scenarios from the CSB and verified on six incidents from the IChemE database. The results are promising in establishing the model's efficacy in predicting adverse events. Sensitivity analysis shows that management of change and lack of procedure and training have the highest sensitivity towards fire and explosion, and therefore need proper attention. This approach will be an essential tool for Safety 4.0, enabling process safety in the digitalization process.

Lane clearance approach for emergency vehicles in highways network.

The steady rise in the number of vehicles in modern urban areas and poor conformance to traffic laws (or rules) lead to avoidable commute delays and traffic jams. Also, there is an increased likelihood of road accidents requiring immediate medical attention. Emergency vehicle (EV) service is adversely affected due to the unavailability of the clear lane that supports EVs to get to their endpoint without being delayed along the national highways. Moreover, the EV's sirens have a limited range, which may fail to reach and notify other vehicular traffic about its mobility promptly. In addition to this range constraint, EVs in motion often lose their communication links while moving from network to network. This paper delineates an approach using the next generation mobile internet protocol, for automated pathway clearance, for EVs. The prototype model of the proposed approach was experimentally designed and implemented. The proposed design concept is validated by performance characterization via numerical analysis.

The Importance of Workplace- Occupational Safety in the Perspective of Enterprise Sustainable Development and Performance

Workplace- Occupational health and safety has grown more vital in order to safeguard the sustainability of firms' manufacturing operations in order to adapt to competitive pressures circumstances and quick consumption. Recognizing the destruction of productivity and image, as well as the money and spiritual expenses due to workplace fatalities and occupational diseases, implementing measures and improving workplace health and protection would bring major benefits to individuals, businesses, and the country 's business. Unsafe conditions, depending to studies, may be influenced through variables such as physical and technological environmental circumstances, as well as personnel characteristics. Conditions including the framework of the technology and manufacturing industry, the specifics of mining, development, and transportation lines of enterprise, ignorant and underqualified manufacturing workers, incapacity to adjust to technological advancements, environmental degradation, production organization layout, and the failure to use individual protective equipment and equipment guardians could all lead to occupational fatalities, particularly in underdeveloped and emerging nations.. These circumstances are significant in the likelihood of workplace accidents. Throughout the scope of this research, investigation is performed on the workspace functioning system, ergonomically design, and occupational physiological variables, which are considered the drivers of occupational disasters in generally. A continuous improvement, Total Abilities and Accomplishment (5S and Total Productive Maintenance) Implementation is provided to enhance occupational security and functional productivity in a business that manufactures white appliances. As a consequence of the specific application, an assessment was carried out in the perspective of worker productivity and commercial performance of the operations.

USE OF VIRTUAL AND AUGMENTED REALITY TECHNOLOGIES TO ENSURE LABOR SAFETY

Recently, new learning technologies with elements of virtual and augmented reality have been created to eliminate the discrepancy between the necessary and existing competencies of employees. They can be used in the field of occupational safety or training young professionals in safe work practices. VR/AR technologies should be aimed at improving safety at work through the introduction of digital instructions and training in virtual reality, simulating both regular and extreme situations. VR/AR technologies help to reduce time costs and possible errors, increase productivity and efficiency, and also reduce the risk of industrial injuries. The importance and prospects of modern AR/VR technologies for ensuring labor safety are shown. The analysis of modern foreign and domestic research and development of the VR/AR interface in the field of building a labor protection management system has been carried out. Emphasis is placed on the formalization of the concept of using AR tools to ensure production safety. A SWOT analysis was carried out to assess the main problems and risks of introducing VR / AR technologies to ensure labor safety. During the analysis of technology application cases, data was obtained that allowed to identify the weak and strong sides of the technologies, the possibilities of their application and the threats faced by the companies. To systematize information from sources, a SWOT matrix was constructed. We will present a SWOT analysis of AR/VR technologies to ensure labor safety. One of the strengths can be considered "a variety of applications", which confirms the promise of using AR / VR tools. With proper use of the potential of technology, companies will be able to achieve the desired benefits by increasing employee productivity, improving work processes, effectively building a labor management system, deepening the professional competencies of their employees, and reducing the likelihood of accidents or accidents at the enterprise. Keywords: VR/AR technologies, industrial safety, labor protection.

Redox Testing and Control for Corrosion Control in Molten Flinak

Fluoride Cooled High-Temperature Reactors (FHRs) are Generation IV Nuclear Reactor designs which will use molten fluoride salts as coolants. FHRs operate at a much higher temperature than the water-cooled reactors and have lower operating pressure. This greatly improves their thermal efficiency and decreases the likelihood of severe accidents. Fluoride salts such as FLiNaK (46.5-11.5-42 mol% LiF-NaF-KF) are considered for use as coolants in FHRs.One of the major concerns for FHR designs is the significant corrosion of structural alloys in the FLiNaK. The corrosion in the form of selective dissolution of active alloying elements in these molten salts depends on the redox potential of the salt. This redox potential can be controlled by various chemical and electrochemical techniques and thereby corrosion of structural alloys in the salt can be controlled. However, the lack of reliable and reproducible reference electrodes for application in molten fluoride salts limits the ability to study redox control in these salts. Most tested reference electrodes in molten FLiNaK salt do not give stable potential due to a combination of the high electronegativity of fluorine and the high temperature of the medium. As such, the development of a reliable and stable reference electrode for these salts is paramount.In this study, various kinds of reference electrodes that could be used for molten FLiNaK salt such as Dynamic Reference Electrodes (DRE), Quasi Reference Electrodes (QRE) etc. have been studied. In addition, in this study, corrosion behaviour of selected Ni and Fe based alloys were studied in molten FLiNaK at 700 oC. The effect of various chemical and electrochemical redox control techniques such as addition of reducing agents to the salt, purification of the salt, and the use of applied potential against a QRE were studied to understand their ability to mitigate corrosion of selected alloys in FLiNaK. This presentation will discuss our results on different reference electrode designs as well as the efficacy of each tested redox control method in controlling the corrosion of candidate alloys in molten FLiNaK.

Discovering associated factors behind road accidents using association rule mining: A case study from Gujarat, Pakistan

Traffic and road safety is an international issue that is among the major concerns of the respective governing bodies around the world. Regulations and restrictions surrounding this issue can be legislated and applied only after identifying and understanding the numerous factors and conditions that increase the likelihood of traffic accidents. In this research work, we study and analyze the road accidents data and figure out the major factors that contribute to these incidents. The data was collected from Gujrat rescue office and outstanding results are achieved by applying association rules mining using Apriori algorithm. Our research and analysis found that some factors are greater contributors than others and need careful enforced legislation. Other researchers have also used the Apriori algorithm to analyze traffic accidents data from their regions and like our experience this algorithm has produced accurate and effective results. We also try to provide additional insights through visualization that may serve as guidelines to regulate better traffic control systems

NotiBike: Assessing Target Selection Techniques for Cyclist Notifications in Augmented Reality

Cyclists' attention is often compromised when interacting with notifications in traffic, hence increasing the likelihood of road accidents. To address this issue, we evaluate three notification interaction modalities and investigate their impact on the interaction performance while cycling: gaze-based Dwell Time, Gestures, and Manual And Gaze Input Cascaded (MAGIC) Pointing. In a user study (N=18), participants confirmed notifications in Augmented Reality (AR) using the three interaction modalities in a simulated biking scenario. We assessed the efficiency regarding reaction times, error rates, and perceived task load. Our results show significantly faster response times for MAGIC Pointing compared to Dwell Time and Gestures, while Dwell Time led to a significantly lower error rate compared to Gestures. Participants favored the MAGIC Pointing approach, supporting cyclists in AR selection tasks. Our research sets the boundaries for more comfortable and easier interaction with notifications and discusses implications for target selections in AR while cycling.

Use of fuzzy fault tree analysis and Bayesian network for occurrence likelihood estimation of navigational accidents in the Qinzhou Port

This paper utilizes a fuzzy fault tree analysis and Noisy-OR gate Bayesian network to estimate the occurrence likelihood of navigational accidents. The kernel of this proposed method is first to construct the fault tree from investigation reports of navigational accidents, to calculate the occurrence probability of basic events using fuzzy set, to transform the fault tree to Bayesian network using the Noisy-OR gate. The merit of the developed model can overcome the problem of absolute description of the relationships between basic events and intermediate events. Finally, the model is applied to Qinzhou Port, the results are reasonable by comparing the results in other waterways. Moreover, the key influencing factors are identified from minimum cut set analysis and sensitive influencing factors are quantified sensitivity analysis. Consequently, the findings are beneficial for the maritime authorities to take countermeasures for navigational accidents prevention.

Anomaly Detection in Traffic Surveillance Videos Using Deep Learning.

In the recent past, a huge number of cameras have been placed in a variety of public and private areas for the purposes of surveillance, the monitoring of abnormal human actions, and traffic surveillance. The detection and recognition of abnormal activity in a real-world environment is a big challenge, as there can be many types of alarming and abnormal activities, such as theft, violence, and accidents. This research deals with accidents in traffic videos. In the modern world, video traffic surveillance cameras (VTSS) are used for traffic surveillance and monitoring. As the population is increasing drastically, the likelihood of accidents is also increasing. The VTSS is used to detect abnormal events or incidents regarding traffic on different roads and highways, such as traffic jams, traffic congestion, and vehicle accidents. Mostly in accidents, people are helpless and some die due to the unavailability of emergency treatment on long highways and those places that are far from cities. This research proposes a methodology for detecting accidents automatically through surveillance videos. A review of the literature suggests that convolutional neural networks (CNNs), which are a specialized deep learning approach pioneered to work with grid-like data, are effective in image and video analysis. This research uses CNNs to find anomalies (accidents) from videos captured by the VTSS and implement a rolling prediction algorithm to achieve high accuracy. In the training of the CNN model, a vehicle accident image dataset (VAID), composed of images with anomalies, was constructed and used. For testing the proposed methodology, the trained CNN model was checked on multiple videos, and the results were collected and analyzed. The results of this research show the successful detection of traffic accident events with an accuracy of 82% in the traffic surveillance system videos.

Power Plant Construction Projects Risk Assessment: A Proposed Method for Temporary Systems of Commissioning

The identification of hazards and risk assessment are key factors in the safety of the industries, including power plants. This paper contains an original risk analysis method that increases the level of safety in commissioning and start-up operations. With the proposed method, which has been tested in real industrial facilities, it has been possible to increase the safety of the system and reduce the likelihood of incidents and accidents in one of the most dangerous stages of project construction activities. This paper also gives an overview of the processes and procedures used in the construction of power plants compared to other industry sectors, proposing some areas for potential improvement. It has been verified that temporary systems used during commissioning apply risk evaluation techniques that do not consider some aspects related to process hazards, something that can be important for the prevention of accidents that historically happen at this stage. Analysis of the data has determined that, in these stages, there have been incidents and accidents, some of them severe. Thus, in this paper, a methodology is proposed. The method allows addressing the particularities of the execution of temporary systems in a safe way by putting into practice an agile and flexible method that can be applied to these particular systems, so that the risk levels can be reduced. The method was applied to one real application representative of this kind of system and yielded excellent results. The proposed methodology is highly recommended as an improvement for the power industry.