Value Of Error Probability Research Articles

Study on Selection Diversity for MIMO 3-User Interference Channel with Interference Alignment

This paper explores selection diversity in the context of MIMO 3-user interference channels with interference alignment (IA), focusing on enhancing reliability through diversity order (DO) analysis. While degrees of freedom (DoF) have traditionally been emphasized for throughput optimization in IA, limited research has addressed diversity order to improve error performance. In this work, we define a conditional DO and propose a beamforming vector selection method that achieves a conditional DO of M2/2, where M is the number of antennas per transceiver. The proposed scheme employs a two-stage decoding approach, combining zero-forcing for interference cancellation with maximum likelihood (ML) decoding for desired signal recovery, which is augmented by orthogonalization techniques. Simulations demonstrate the superiority of the proposed scheme in both error probability and conditional DO values compared to conventional IA methods, particularly in scenarios with higher antenna counts. These results provide insights into optimizing IA for enhanced reliability and form the foundation for future exploration of advanced decoding and beamforming strategies.

A Comparative Risk Assessment of Human Error in Firefighting Using SLIM and Fuzzy SLIM Method

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.

Dynamic modeling of human error in industrial maintenance through structural analysis and system dynamics.

Human error constitutes a significant cause of accidents across diverse industries, leading to adverse consequences and heightened disruptions in maintenance operations. Organizations can enhance their decision-making process by quantifying human errors and identifying the underlying influencing factors, thereby mitigating their repercussions. Consequently, it becomes crucial to examine the value of human error probability (HEP) during these activities. The objective of this paper is to determine and simulate HEP in maintenance tasks at a cement factory, utilizing performance shaping factors (PSFs). The research employs the cross-impact matrix multiplication applied to classification (MICMAC) analysis method to evaluate the dependencies, impacts, and relationships among the factors influencing human error. This approach classifies and assesses the dependencies and impacts of different factors on HEP, occupational accidents, and related costs. The study also underscores that PSFs can dynamically change under the influence of other variables, emphasizing the necessity to forecast the behavior of human error over time. Therefore, this paper utilizes the MICMAC method to analyze the interdependencies, relationships, and impact levels among different variables. These relationships are then utilized to optimize the implementation of the system dynamics (SD) method. An SD model is employed to forecast the system's behavior, and multiple scenarios are presented. By considering the HEP value, managers can adjust organizational conditions and personnel to ensure acceptability. The paper also presents various scenarios related to HEP to assist managers in making informed decisions.

ANALISIS HUMAN ERROR TERHADAP KESEHATAN DAN KESELAMATAN KERJA PEKERJA LOGAM DAN PERMESINAN PADA PROSES PRODUKSI MENGGUNAKAN PENDEKATAN HEART STUDI KASUS CV ANDHY KARYA

The production process of CV Andhy Karya goes through several production lines, starting from the printing process, casting process, machining and finishing process. The work accident report for 2023 shows that as many as 20% of 30 workers have serious work accidents in the casting and machining process. Occurs during the casting process where the worker's foot is exposed to a hot metal liquid during casting which results in the worker's leg suffering serious burns and being referred to the hospital. Based on the above events, to minimize the occurrence of work accidents and human error, the purpose of this study is to identify and measure human error probability then determine control efforts to minimize the occurrence of human error on occupational safety and health. . The results of this study show. The task with the highest human error probability value in the printing and casting process is task 2.2 to enter raw materials into the combustion furnace, HEP value of 0.283. In the machining process, the task with the highest HEP value is task 1.2, turning on and adjusting the lathe with a HEP value of 0.320. In the finishing process of the task, the highest HEP value, task 1.1, moves the product from the grinding place to the painting place with a HEP value of 0.150. Efforts for control can be done by using stairs with the correct procedures, providing handles on stairs, using anti-slip footwear and not carrying excessive loads. Use PPE (gloves), follow safety procedures recommended by the machine, and maintain concentration in work. Then workers can lift products with a weight that is not excessive and lift products with the help of other tools or not manually such as using a trolly.

Adverse effects of receiver clock bias and drift on NavIC user position coordinates and their mitigation

We investigated the effects of receiver clock bias and drift on NavIC receiver position coordinates at a low latitude station and proposed a mitigation technique. For this, Five weeks data of Accord IRNSS-GPS-SPS (AIGS) receiver are considered. Error in each position coordinates (X, Y and Z) is estimated and observed that the maximum error occurred in user position Z-coordinate. CEP for 2D position is analyzed and observed that the Circular Error Probability (CEP) values are high in Z coordinate of YZ and ZX planes. Further, it is noticed that the timing of sudden enhancement of both clock bias and drift parameters coincides with the periodic anomaly of the X, Y and Z coordinates. The error in individual position coordinates is minimized by applying 6th order Butterworth low pass filter resulting in improved position accuracy. If such errors are not mitigated, the position estimation of the receiver becomes highly erroneous.

A framework to determine the holistic multiplier of performance shaping factors in human reliability analysis – An explanatory study

The safety of nuclear power plants is the uppermost goal to be emphasized for their sustainability. To this end, it is crucial to evaluate their anticipated risk by visualizing accident scenarios resulting in undesirable consequences. In quantifying the likelihood of an accident scenario occurrence, it is necessary to estimate values of human error probabilities with respect to the performance of safety-critical tasks following relevant human reliability analysis (HRA) methods. One of the technical issues pertaining to the quality of HRA results is to determine the multipliers of performance shaping factors (PSFs) that specify the contexts in which human operators have to accomplish the required safety-critical tasks. Unfortunately, since PSFs are entangled with complicated interrelations, it is hard to properly determine their multipliers. To address this problem, in this study, a framework that can quantify the holistic multiplier of a specific PSF is proposed that can encompass the effect of these complicated interrelations. In order to corroborate the applicability of the proposed framework, an explanatory case study is conducted by using data available from the literature. Based on the result of this case study, it is expected that the proposed framework would be effective for determining PSF multipliers.

Nurse-Task Matching Decision Support System Based on FSPC-HEART Method to Prevent Human Errors for Sustainable Healthcare

To increase the levels of sustainability of service quality as well as to ensure satisfaction and assurance of patients in the health sector, minimizing the probability of making mistakes nurses is of great importance. The extent of this probability is considerably affected by task types, physical conditions of the working environment, workload, and working conditions. Moreover, the physical and mental characteristics of nurses also have a colossal influence on this probability. It is also possible to increase the sustainability of health services by matching nurses appropriately to a specific task according to related risk levels, and by balancing their workload accordingly. This study proposes FSPC-HEART method in that purpose, as a new type of human error reduction and assessment technique (HEART) application based on fuzzy step-wise weight assessment ratio analysis and principal component analysis methods. Unlike the methods in the literature, this new method offers a person-specific proactive error prevention approach. With FSPC-HEART, the probability of each nurse to make a mistake, that is, the human error probability (HEP) values are calculated separately for each task. Also, the combined effect of physical and mental workload factors for each employee was taken into account. In the proposed method, the effect of the subjective judgments of the decision-makers on the objectively obtained HEP values was tried to be reduced. The developed nurse-task matching decision support system enables the FSPC-HEART method to be easily used by decision-makers, and to assign employees to tasks with low error probabilities.

Importance Sampling Over Monte Carlo Technique to Estimate Wireless Infrared On-Chip Communication

Optical code division multiple access (OCDMA) represents the development of optical communication. The advantages of OCDMA such as, asynchronous multiuser communication transmission, flexibility, ample bandwidth and scalability; have made this technique a better candidate to be proposed for next generation network on chip. In this paper, performance of on-chip OCDMA communication system is analyzed. Analytical techniques for estimating the performance of optical communication systems are difficult, complicated and no complete analytical treatment of the problem has been obtained before. Simulation techniques such as Monte Carlo (MC) are used to obtain reasonable estimates of these systems performance. For optical communications, Monte Carlo require excessively large sample sizes which makes it cumbersome in terms of physical resources, and are not practical for estimating very low values of error probabilities. Modified Monte-Carlo (Importance sampling/IS) method was used to reduce the number of simulation tests for estimating error probabilities for optical communications systems by modifying the probability density function of the on-chip noise process. Simulation results are presented and assessed in term of bit error rate (BER), showing the contribution of IS relatively to MC.

Mental wellbeing; Human reliability assessment of seafarers during the COVID-19 era

ABSTRACT The COVID-19 pandemic took the world by storm and disrupted global trade and maritime activities. Seafarers suffered immensely as most of their activities were affected due to the lockdown and travel restrictions placed by most governments to protect their borders. This had an impact on mostly their mental health as most of their routine became disrupted, travel plans were cancelled, and some fear of losing their jobs due to uncertainty. This research focuses on the impact the lockdown had on the mental health of seafarers and how it affects their human error probability value during COVID-19 by utilizing the HEART methodology. The conventional HEART technique is not precisely developed to be applied in the marine and offshore sector, so it was imperative to modify it to capture the key factors this research would be measuring which include fatigue, poor communication, depression, sleep deprivation, and how they influence the Human Error Probability (HEP) value of seafarers. To properly factor in these influencing factors, a questionnaire was developed and distributed to expert seafarers to weigh each factor in other to develop the Error Influencing Factor (EIF) table to further boost the accuracy of this research. For this research, the scenario used is a pre-mooring task carried out by seafarers. The result shows that the HEP value changes by over 55% from 6.1676E–2 before covid-19, to 6.1960E–1 during covid-19. Event Tree analysis was also carried out using the individual HEP values to calculate the probability of failure of the mooring ropes. The result shows that the probability of failure during COVID-19 is higher when compared. The application of this modified HEART technique confirms that COVID-19 lockdown had a negative impact on these factors that influence the mental well-being of seafarers.

Human Factor Analysis of the Railway Traffic Operators

The human factor is an essential aspect of the operability and safety of many technical systems. This paper focuses on the analysis of human errors in the railway domain. The subject of human reliability analysis is the behavior of operators of station-signaling systems responsible for rail traffic management. We use a technique for human-error rate prediction as the 1st generation human reliability analysis to deal with task analyses, error identification and representation, and the quantification of human error probabilities. The paper contributes to the comparison of three technologically different railway traffic control systems, having different degrees of automation—from the manually operated (electro-mechanical), through semi-automated (relay-based) to almost fully automated (computer-based) station-signaling systems. We observe the frequency of individual operations performed in time intervals and calculate human error probability and human success probability values for each operation. Thus, we can analyze human reliability and compare the workload of operators working with control systems of different degrees of automation.

Integration of the HEART and SHERPA Approach to Evaluating Human Errors in the Refinery Salt Production

Human error can be prevented by measuring human reliability through the Human Reliability Assessment approach. PT A is a national scale salt producer that produces salt. The quality division identifies human error problems made by operators in the salt refining process. This study aims to identify, calculate probability values, and provide recommendations for improvement to reduce human error in salt refining production operators. HEART and SHERPA are research approaches used because they are considered the most suitable for this study. The results showed that the most visible human error for the error mode category was C2, incomplete checking, and 42 error modes because the operator infrequently did a complete check. The process with the highest Human Error Probability value is the drying process 1, with a value of 7.49. In contrast, the process with the most minor Human Error Probability value score of 0.085 is the bagging process 2. Human error prevention efforts are carried out for each process based on the highest score on the Human Error Probability Index, including Personal Protective Equipment, Standard Operating Procedures, and training to improve operator skills.

Application of the HEART method to enhance patient safety in the intensive care unit.

The intensive care unit (ICU) is a complex, dynamic, high stress and time-sensitive place. While a variety of rules and regulations provided to reduce medication errors in recent years, many studies have emphasized that medication errors still happen. The purpose of this investigation is to predict, reveal and assess medication errors among surgical intensive care unit (SICU) nurses. This study was performed in one of the public hospitals in Shiraz, namely Shahid Faghihi hospital. The human error assessment and reduction technique (HEART) method was adopted to measure and assess medication errors in the ICU. Findings indicate that ICU nurses perform 27 main tasks and 125 sub-tasks. The results also showed that setting and using DC shock task has the highest human error probability value, and assessment of patients by a nutritionist has the lowest human error probability value. Medical errors are key challenges in the ICU. Therefore, alternative solutions to mitigate medication errors and enhance patient safety in the ICU are necessary. Although the technique can be used in healthcare; there is a need to localize the coefficients and definitions to achieve more accurate results and take appropriate controls. Employing experienced people and providing conditions that reduce the possibility of errors in nurses, increasing the number of staff, and developing specialized and simulated training were identified as the most important control strategies to reduce errors in nurses.

Human Error Analysis to Minimize Work Accidents Using the HEART and SHERPA Methods at PT. Wonojati Wijoyo

PT Wonojati Wijoyo is a company that produces furniture for export. In carrying out the production process, work accidents often occur. One of the causes is the factor of human negligence. Work accidents that have occurred include torn wounds due to being hit by a machine, legs hit by wood to make them swollen, fingers hit by machines to open wounds, fingers caught in blocks to open wounds. This study aims to determine the value of Human Error Probability (HEP) and recommend improvement strategies for activities that have the potential to cause human errors to minimize work accidents. The method used in the analysis of human error is the HEART method and the SHERPA method. The results showed that there are critical activities that have the potential for human error to occur, namely in 14 subtasks of 9 processes. The highest probability of human error is in the subtask of cutting wood plates using a circle machine with a HEP value of 0.88827 including the high category. While the lowest probability of human error is in the subtask of setting a copy machine with reference wood with a HEP value of 0.00372 including the medium category. One of the recommendations for improvement strategies to minimize work accidents is that the company needs to conduct training on K3 on a scheduled basis with an explanation of the risks that occur if you do not use Personal Protective Equipment (PPE).

Measurement of Human Work Reliability Using Systematic Human Error Reduction and Prediction Approach and Human Error Assessment and Reduction Technique Method

CV. Raja Hati is a company that is engaged in the process of refinishing tires that have been bald into new ones. The tire retreading process has a relatively high percentage of defects, such as 14.8% Printing Process, 12.3% Surface Leveling, 8.6% Tire Curing, and so on. The problems in this study are the factors that cause defects in terms of human aspects, the types of errors that most often occur in the production process, and the value of human error probability (HEP) in the production process at CV. Raja Hati. This study aims to determine the factors that cause defects in terms of human aspects, the types of errors that most often occur in the production process and the value of human error probability (HEP) in the production process. The research was conducted using the SHERPA and HEART methods. The SHERPA method’s study results show that the types of errors that often occur in the tire retreading process are many wrong operator actions. Still, on the proper object (A7), the operator is wrong in dividing the time in doing work (A2), and the operator is not suitable for doing his job (A5). This study concludes that the factors that cause product defects in the tire retreading process are the absence of a procedure for correcting errors by 21.63%, the need for different techniques in doing work to facilitate operators by 27.04%, inexperienced operators by 12.36%, and inexperience and independent inspection has a percentage of 12.36%. The results of the calculation of the HEP value show that the average HEP value in the tire retreading process is 0.8552 or 85.52%, while the operator reliability value is 14.48%.

Effect of Error Probability, Data Rates, Output Power and Noise Floor on Link Quality of WSN Channels

In this work, it is proposed that the use of statistical percentage of errors correlated to the Received Signal Strength (RSS) and to both the output power and noise bandwidth, together with the data rate ratio, can give a clear indication of the communication channel quality in the presence of a noise floor. Simulation of a WSN network with variable Data Rate to Noise Band Width ratio (R), different output power (Ptran), and variable Noise Floor Power (Pnoise), showed that each one of these parameters affects error probability distribution and values, which in turn affect channel utilization. The work also proved that these are critical parameters that, if correlated and optimized, can achieve a high utilization of WSN channels. The largest effect realized is related to Pnoise and interference, which, if present at high values, would reduce the probability of exchanging data by 25%. The work also showed that as the ratio R increases, the probability and magnitude of errors increases, which in turn contributes to lower utilization, as depicted in the tables and plots. The 10-nodes WSN is simulated in a uniform topology setting.

CMS-BN: A cognitive modeling and simulation environment for human performance assessment, part 2 — Application

Human operators play a critical role in the operation of complex engineered systems, in particular under abnormal conditions. It is important to assess human performance under conditions of interest and to improve upon the performance by taking effective measures. In this paper we present the application of a previously developed cognitive modeling and simulation environment to address these two problems. The developed environment simulates how a human operator dynamically interacts with the external system, with focus on the operator’s cognitive activities. Based on the Three Mile Island accident, specifically the stuck-open failure of the pilot operated relief valve, we demonstrate how the developed environment can be used for human reliability analysis and human performance improvement. For human reliability analysis, besides providing a single human error probability value the proposed environment allows us to examine in detail how an operator reached a decision or missed an action. For human performance improvement, the proposed environment provides an easy approach for investigating the effects of changes, for example, in operator training and system design, on human performance and therefore identifying the most effective changes to improve human performance.

Human error probability analysis using Success Likelihood Index Method (SLIM) approach in grinding activities

Grinding activities produced 31% accident cases that occurred repeatedly and had the same cause. Most of them were investigated and were proved to be caused by human error. The study aims to obtain the value of Human Error Probability (HEP), thus, it could be employed as prevention and controlling consideration. HEP value was obtained by finding the value of. Success Likelihood Index (SLI). SLI value could be obtained using questionnaires and Performance Shaping Factor (PSF) assessment which had been filled by expert judgment. The scenarios were developed to predict and reduce the occurrence of human error as applied to Success Likelihood Index Method (SLIM). This research illustrated the factors that affected errors in the grinding process were procedure, fatigue, complexity, training, and experience. The task that contained the highest error value was in the first task (use PPE following predetermined). While the task which included the lowest HEP was task 2 (prepare documents according to pre-defined). As part of efforts to reduce the error probability values grinding process, it recommended reducing the probability of error by increasing the value of PSF, ranging from improved procedures, reduction of fatigue of the workers, the reduction of the complexity of the job, increased training for workers, and increased workers’ qualification through work experience history.

Analysis of Human Error Risk with Human Reliability Methods in Construction Projects

Work injury rates in Indonesia are relatively high, resulting in an urgency to maintain the safety of workers whose numbers are increasing. The biggest sector contributing to work accidents in Indonesia is the construction area, including building construction and causing large physical and financial losses. Workplace accidents are usually caused by human error and are strongly related to human reliability. The use of Fuzzy Cognitive Reliability and Error Analysis Method (Fuzzy CREAM) method is aimed at research to analyze patterns of worker behavior that affect the risk of workplace accidents combined with Bayesian Network simulation. 176 construction workers in the Jakarta and surrounding areas became the object of research. The value of Human Error Probability (HEP) was successfully obtained and the solution was given based on the characteristics of workers in the Control Mode category.

HUMAN ERROR IDENTIFICATION IN BUS DRIVER WORK USING SHERPA AND HEART

Traffic accidents, especially with a large capacity such as bus, can be caused by several factors. According to the Indonesian Directorate General of Land Transportation of the Ministry of Transportation in 2012, the factors causing traffic accidents in Indonesia are a human factor of 93.52%, vehicle factor by 2.76%, road factor 3.23%, and environmental factor by 0.49%. Therefore, research is needed to identify which human error has the greatest probability of accident cause using Systematic Human Error Reduction and Prediction Approach (SHERPA) method to identify job desk using Hierarchical Task Analysis (HTA) and Human Error Assessment Reduction Technique (HEART) method to calculate Human Error Probability (HEP). Based on the calculation of Human Error Probability value known the highest HEP value is not running the vehicle in accordance with the provisions of the speed that has been set with 0.375. Next is not to record or forget to record the damage that occurred during the trip with a value of 0.21. It did not check Bus equipment with a HEP value of 0.19, did not report when there was a problem on the street with a HEP value of 0.18 and did not break for the next preparation for departure with a HEP value of 0.15

A Human Reliability Analysis to Crankshaft Overhauling in Dry-Docking of a General Cargo Ship

This study conducts a practical application of shipboard operation human reliability analysis (SOHRA) to a crankshaft overhauling operation of a general cargo ship at dry-docking period. The SOHRA approach includes error producing condition (EPC) and general task type (GTT) parameters to consistently calculate the human error probability (HEP) values of operation steps. In this case, a comprehensive overhauling of main engine was planned at shipyard since the ship has experienced a catastrophic failure. An onboard survey to ship engine room is conducted to monitor the operational conditions. The targeted operation, involves disassembly, maintenance, and reassembly stages, is monitored based on 39 sub-tasks. According to the initial findings, immediate recovery actions are suggested to eliminate critical safety issues in a timely manner. Moreover, an extended discussion through long-term safety recommendations are also provided. The results revealed from case study illustrates that HEP values in maintenance operations are sensitive to ship operating conditions. The proposed approach is found very useful by company executives to support ship technical superintendents in critical operation monitoring. The further study is considered to develop mobile application of SOHRA specific to maintenance operations onboard ships.