Zeitschriftenartikel: „Human Error Probability“

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Taylor-Adams, Sally E. „CORE-DATA, A Human Error Probability Database“. Safety and Reliability 13, Nr. 4 (Dezember 1993): 6–16. http://dx.doi.org/10.1080/09617353.1993.11690625.

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Basra, Gurpreet, und Barry Kirwan. „Collection of offshore human error probability data“. Reliability Engineering & System Safety 61, Nr. 1-2 (Juli 1998): 77–93. http://dx.doi.org/10.1016/s0951-8320(97)00064-1.

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Liu, Zhao Xia, und Lian Jun Chen. „Post-Accident Human Reliability Analysis and Control of Mine Hoisting System“. Advanced Materials Research 616-618 (Dezember 2012): 461–64. http://dx.doi.org/10.4028/www.scientific.net/amr.616-618.461.

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Using the method of THERPand HCR this paper studies post- accident human error events of mine hoisting system which reflects accident consequence seriousness and accident treatment urgency. It ascertains cognitive failure probability P1, non-response probability P2 and the failure probability P3, and quantities and appraises degree of human reliability. Finally this paper analyzes causes of hoisting accident human errors ,by which probability human error can be reduced to the lowest limit.

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Xi, Yong Tao, und Chong Guo. „A Method for Marine Human Error Probability Estimate: APJE-SLIM“. Applied Mechanics and Materials 97-98 (September 2011): 825–30. http://dx.doi.org/10.4028/www.scientific.net/amm.97-98.825.

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Safety is the eternal theme in shipping industry. Research shows that human error is the main reason of maritime accidents. Therefore, it is very necessary to research marine human errors, to discuss the contexts which caused human errors and how the contexts effect human behavior. Based on the detailed investigation of human errors in collision avoidance behavior which is the most key mission in navigation and the Performance Shaping Factors (PSFs), human reliability of mariners in collision avoidance was analyzed by using the integration of APJE and SLIM. Result shows that this combined method is effective and can be used for the research of maritime human reliability.

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Yang, Wei Jun, und Peng Xiao Jiang. „The Probability Analysis of Human Error in Teaching“. Applied Mechanics and Materials 239-240 (Dezember 2012): 1611–14. http://dx.doi.org/10.4028/www.scientific.net/amm.239-240.1611.

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This paper thoroughly analyzed the human error in teaching work of colleges and universities, discussed its causes, mode and consequences, proposed the probability analysis methods. The analysis can be treated as a reference to prevent, control and management human error in teaching work for colleges and universities.

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Visser, M., und P. A. Wieringa. „PREHEP: human error probability based process unit selection“. IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews) 31, Nr. 1 (2001): 1–15. http://dx.doi.org/10.1109/5326.923264.

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Sun, Zhiqiang, Zhengyi Li, Erling Gong und Hongwei Xie. „Estimating Human Error Probability using a modified CREAM“. Reliability Engineering & System Safety 100 (April 2012): 28–32. http://dx.doi.org/10.1016/j.ress.2011.12.017.

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Di Pasquale, Valentina, Salvatore Miranda, Raffaele Iannone und Stefano Riemma. „A Simulator for Human Error Probability Analysis (SHERPA)“. Reliability Engineering & System Safety 139 (Juli 2015): 17–32. http://dx.doi.org/10.1016/j.ress.2015.02.003.

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De Felice, F., A. Petrillo und F. Zomparelli. „A Hybrid Model for Human Error Probability Analysis“. IFAC-PapersOnLine 49, Nr. 12 (2016): 1673–78. http://dx.doi.org/10.1016/j.ifacol.2016.07.821.

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Sun, Zhiqiang, Erling Gong, Zhengyi Li, Yingjie Jiang und Hongwei Xie. „Bayesian estimator of human error probability based on human performance data“. Journal of Systems Engineering and Electronics 24, Nr. 2 (April 2013): 242–49. http://dx.doi.org/10.1109/jsee.2013.00031.

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Guglielmi, Dina, Alessio Paolucci, Valerio Cozzani, Marco Giovanni Mariani, Luca Pietrantoni und Federico Fraboni. „Integrating Human Barriers in Human Reliability Analysis: A New Model for the Energy Sector“. International Journal of Environmental Research and Public Health 19, Nr. 5 (27.02.2022): 2797. http://dx.doi.org/10.3390/ijerph19052797.

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Human reliability analysis (HRA) is a major concern for organizations. While various tools, methods, and instruments have been developed by the scientific community to assess human error probability, few of them actually consider human factors impact in their analysis. The active role that workers have in shaping their own performance should be taken into account in order to understand the causal factors that may lead to errors while performing a task and identifying which human factors may prevent errors from occurring. In line with this purpose, the aim of this study is to present a new methodology for the assessment of human reliability. The proposed model relies on well-known HRA methodologies (such as SPAR-H and HEART) and integrates them in a unified framework in which human factors assume the role of safety barriers against human error. A test case of the new method was carried out in a logistics hub of an energy company. Our results indicate that human factors play a significant role in preventing workers from making errors while performing tasks by reducing human error probability. The limits and implications of the study are discussed.

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Facchini, Francesco, Salvatore Digiesi und Giovanni Mummolo. „Model of Human Error Probability based on dual-phase approach for learning process in cognitive-oriented tasks“. International Journal of Industrial Engineering and Management 11, Nr. 1 (01.03.2020): 31–39. http://dx.doi.org/10.24867/ijiem-2020-1-250.

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Poluyan, L. V., und M. G. Malukova. „Assessing functions of human risk, reliability and error probability“. IOP Conference Series: Materials Science and Engineering 962 (18.11.2020): 042055. http://dx.doi.org/10.1088/1757-899x/962/4/042055.

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Böllhoff, Jörg, Joachim Metternich, Nicholas Frick und Matthias Kruczek. „Evaluation of the Human Error Probability in Cellular Manufacturing“. Procedia CIRP 55 (2016): 218–23. http://dx.doi.org/10.1016/j.procir.2016.07.080.

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Ung, Shuen-Tai, und Wei-Min Shen. „A Novel Human Error Probability Assessment Using Fuzzy Modeling“. Risk Analysis 31, Nr. 5 (08.12.2010): 745–57. http://dx.doi.org/10.1111/j.1539-6924.2010.01536.x.

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Zimolong, Bernhard, und Barbara Stolte. „A Study of Expert Judgment on Human Error Probability“. Proceedings of the Human Factors Society Annual Meeting 32, Nr. 15 (Oktober 1988): 954–57. http://dx.doi.org/10.1518/107118188786761938.

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An experiment was conducted to derive empirically human error probabilities from a task performed under 12 different conditions. The task was to control a simulated flexible manufacturing scenario (FMS) under three Performance Shaping Factors (PSF): Incentive, workload and event frequency of breakdowns. Six experts with background in human factors assess the relative contribution of each PSF in affecting the likelihood of failure with the multi attribute decomposition technique. The conversion of the assessment values to probabilities was achieved by the use of an empirically derived calibration equation. Results indicate a poor match of empirical HEPs and their estimates and increase the doubts that subjective estimation is a solution to the missing data problem in reliability measurement.

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Liu, Shang Hai, Bao Fa Liu und Xian Tao Liu. „A Status Evaluation Model of Human Errors Probability in Petroleum Operations“. Applied Mechanics and Materials 416-417 (September 2013): 2078–82. http://dx.doi.org/10.4028/www.scientific.net/amm.416-417.2078.

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The accident happens sometimes in the oil industry and that the Human errors (HEs) are studied and used in the petroleum field is fewer. Then, the paper analyzes the early achievements and finds that most of the studies are aimed at the operation behavior but not the operator. So, using probability theory, the paper discusses the HE Causes and the relationship between human behavior and the accident, and it presents the error state evaluation model of organization and the evaluation model of the number of operators doing Error. According to the evaluation models, the management can get the risk status of accident of an organization.

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Buchatskyi, L. P. „DETERMINING PROBABILITY OF CANCER CELL TRANSFOMATION AT HUMAN PAPILLOMAVIRUS INFECTION“. Biotechnologia Acta 14, Nr. 5 (Oktober 2021): 74–83. http://dx.doi.org/10.15407/biotech14.05.074.

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Aim. The purpose of the work was to assess the probability of cancerous transformation of cells for viruses of high and low oncogenic risk. Aim. The purpose of the work was to assess the probability of cancerous transformation of cells for viruses of high and low oncogenic risk. Results. Using normalized squared error (NSE) for viruses of high (20 strains) and low (153 strains) oncogenic risk, rank statistic of 2-exponential type was build. For productive papillomavirus infection, NSE function was determined as the growing accurate 2-exponent of a cell layer basal to the epithelial surface. Logarithm of NSE numerical values is proportional to the cell entropy that is connected with the availability of virus DNA. To calculate entropy, generalized Hartley formula was used with the informational cell of dimension d: H = NdLOG(NSE), where N is the generalized cell coordinate. Conclusions. Using a statistical ensemble of E6 proteins separately for viruses of high and low oncogenic risk made it possible to assess the probability of cancerous transformation of cells, which was proportional to the ratio of the area of entropy of cancer transformation to the area of the productive entropy region papillomavirus infection.

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Janota, Aleš, Rastislav Pirník, Juraj Ždánsky und Peter Nagy. „Human Factor Analysis of the Railway Traffic Operators“. Machines 10, Nr. 9 (19.09.2022): 820. http://dx.doi.org/10.3390/machines10090820.

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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.

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Bakhtiar, Bakhtiar, Syukriah Syukriah und Muhammad Iqbal. „Measurement of Human Work Reliability Using Systematic Human Error Reduction and Prediction Approach and Human Error Assessment and Reduction Technique Method“. International Journal of Engineering, Science and Information Technology 2, Nr. 1 (05.01.2022): 158–66. http://dx.doi.org/10.52088/ijesty.v2i1.244.

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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%.

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Rammadaniya, Putri, und Nina Mahbubah. „Integration of the HEART and SHERPA Approach to Evaluating Human Errors in the Refinery Salt Production“. Jurnal Sistem Teknik Industri 24, Nr. 2 (29.07.2022): 177–93. http://dx.doi.org/10.32734/jsti.v24i2.7755.

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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.

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Islam, Rabiul, Faisal Khan, Rouzbeh Abbassi und Vikram Garaniya. „Human Error Probability Assessment During Maintenance Activities of Marine Systems“. Safety and Health at Work 9, Nr. 1 (März 2018): 42–52. http://dx.doi.org/10.1016/j.shaw.2017.06.008.

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Du, Yu, Michael Dorneich, Brian Steward und Cameron A. MacKenzie. „A Bayesian-Influence Model for Error Probability Analysis of Combine Operations in Harvesting“. Proceedings of the Human Factors and Ergonomics Society Annual Meeting 60, Nr. 1 (September 2016): 1414–18. http://dx.doi.org/10.1177/1541931213601325.

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Harvesting is one of the most important agricultural operations because it captures the value from the entire cropping season. In modern agriculture, grain harvesting has been mechanized through the combine harvester. A combine harvester enables highly productive crop harvesting. Combine harvesting performance depends on the highly variable skill of combine operators and associated operator error. An approach was developed to analyze the risk of the combine harvesting operation as it relates to operator error. Specifically, a risk analysis model was built based on a task analysis from operator interviews and estimates of the probability of operator error. This paper employs a Bayesian approach to assess risks in combine operation. This approach applies a Bayesian Belief Network to agriculture operations, which represents a new application for this risk analysis tool. Sensitivity analysis of different errors and operator skill levels was also performed. The preliminary results indicate that a reduction of human operator action errors can substantially improve the outcomes of the human-machine interaction.

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Pan, Xing, und Zekun Wu. „Performance shaping factors in the human error probability modification of human reliability analysis“. International Journal of Occupational Safety and Ergonomics 26, Nr. 3 (08.10.2018): 538–50. http://dx.doi.org/10.1080/10803548.2018.1498655.

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Borisov, V. E., V. V. Borsoeva, S. M. Stepanov und A. I. Stepnova. „THE PROBABILITY DETERMINATION OF ERROR-FREE AIR TRAFFIC CONTROLLER OPERATION“. Civil Aviation High TECHNOLOGIES 21, Nr. 3 (03.07.2018): 47–55. http://dx.doi.org/10.26467/2079-0619-2018-21-3-47-55.

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Human error is considered to be a cause or one of the main factors in most accidents. Errors are not a certain type of deviation in behaviour; they are a natural product of all human efforts. Errors must be accepted as a normal component of any system, in which humans and technology interact. In aviation for decades since 1960-ies the share of the human factor (HF) from the total number of aviation accident reasons is estimated by the constant growth from 40–50 to 80–90% [1]. This figure refers generally to the certified flight personnel of commercial aviation. Taking into account flights of General aviation (GA), maintenance, air traffic control, transport infrastructure, the overall share of the HF is over 90%. The subject content of HF focuses on the study of man in various conditions and relations to natural habitat and anthropogenic activities. The HF concept is aimed at finding the reasons for unsatisfactory activity and is understood as a field of methods development to optimize safety. In the understanding of human activities inaccuracy is the history of feelings and ideas about responsibility and free will. Erroneous human actions are the result of many simultaneous and asynchronous processes of air transport subjects and the social environment. The study of the nature of erroneous actions leads to conclusions about the deep origin in the human mentality structures of intentions, opinions and expression of the will. Consequence evaluation takes place during changing environment and individual consciousness. The results are often perceived as not corresponding to the original intentions. The human factor acquires special relevance at introduction of the navigation based on characteristics (PBN). Airline companies and services of Air Traffic Control (ATC) face serious problems while implementing the international standards on human factor.

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Wu, Yaju, Kaili Xu, Ruojun Wang und Xiaohu Xu. „Human reliability analysis of high-temperature molten metal operation based on fuzzy CREAM and Bayesian network“. PLOS ONE 16, Nr. 8 (02.08.2021): e0254861. http://dx.doi.org/10.1371/journal.pone.0254861.

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Human errors are considered to be the main causation factors of high-temperature molten metal accidents in metallurgical enterprises. The complex working environment of high- temperature molten metal in metallurgical enterprises has an important influence on the reliability of human behavior. A review of current human reliability techniques confirms that there is a lack of quantitative analysis of human errors in high-temperature molten metal operating environments. In this paper, a model was proposed to support the human reliability analysis of high-temperature molten metal operation in the metallurgy industry based on cognitive reliability and error analysis method (CREAM), fuzzy logic theory, and Bayesian network (BN). The comprehensive rules of common performance conditions in conventional CREAM approach were provided to evaluate various conditions for high-temperature molten metal operation in the metallurgy industry. This study adopted fuzzy CREAM to consider the uncertainties and used the BN to determine the control mode and calculate human error probability (HEP). The HEP for workers involved in high-temperature melting in steelmaking production process was calculated in a case with 13 operators being engaged in different high-temperature molten metal operations. The human error probability of two operators with different control modes was compared with the calculation result of basic CREAM, and the result showed that the method proposed in this paper is validated. This paper quantified point values of human error probability in high-temperature molten metal operation for the first time, which can be used as input in the risk evaluation of metallurgical industry.

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Ngatilah, Yustina, Endang Pudji W, Rr Rochmoeljati und Tranggono Tranggono. „ANALISA HUMAN ERROR PADA KARYAWAN PRODUKSI BARECORE MENGGUNAKAN METODE HUMAN RELIABILITY ASSESSMENT (HRA)“. Tekmapro : Journal of Industrial Engineering and Management 14, Nr. 1 (10.07.2019): 7–16. http://dx.doi.org/10.33005/tekmapro.v14i1.24.

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Seluruh industri pasti memiliki keinginan untuk memiliki zero accident. Namun pada kenyataannya banyak perusahaan yang memiliki angka kecelakaan yang tinggi tiap tahunnya. Human Reliability Assessment merupakan salah satu metode untuk memberi usulan alternatif pengurangan terhadap kecelakaan kerja yang terjadi. Dimana langkah yang digunakan yakni mengumpulkan data kecelakaan kerja,data Task Analysis Sistem dan data identifikasi kegagalan. Pengolahan yang dilakukan yakni dengan penggambaran kecelakaan kerja menggunakan Fault Tree Analysis,kemudian kuantifikasi nilai Human Error Probability dengan metode Human Error And Reduction Technique dan pada akhirnya akan ditemukan usulan alternatif pengurangan kecelakaan kerja. Hasil dari penelitian ini adalah mengidentifikasi kesalahan manusia yang menimbulkan kecelakaan kerja. Kesalahan karyawan tersebut antara lain posisi pemotongan kurang benar dengan probabilitas tertinggi yaitu 0,728, untuk yang lain seperti gagal memposisikan saat pengambilan material, salah posisi dalam melakukan prosedur,tidak fokus dalam melakukan proses,tidak memperhatikan posisi kayu dan terburu-buru dalam melakukan prosedur probabilitasnya dibawah 0,728.

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Nam, Chang-Su, und Byung-Sik Lee. „Development of an Integrated Human Error Simulation Model in Nuclear Power Plant Decommissioning Activities“. Science and Technology of Nuclear Installations 2023 (12.01.2023): 1–13. http://dx.doi.org/10.1155/2023/8133223.

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In this study, an integrated human error simulation model in nuclear power plant (NPP) decommissioning activities (HEISM-DA) that can integrate and manage various factors affecting human errors is developed. In the HEISM-DA, an error probability input method suitable for the characteristics of each performance shaping factors (PSFs) was presented. Because each PSF has different importance on human error, the relative importance of decommissioning PSF Levels 1 and 2 and influential factors is considered. A multiplier was selected for each PSF and then used for human error evaluation. To calculate the human error probability (HEP) for the NPP decommissioning activity, the relationship between each PSF is identified and linked to develop a human error evaluation model. Using the HEISM-DA, HEP for reactor pressure vessel internal cutting work is evaluated based on the experience data. HEP is calculated to be approximately 1%. As a result of HEP calculation, it is found that the “operation” factor has a significant influence on the HEP of NPP decommissioning activities. Therefore, if the dismantling work is conducted by supervising the “operation” factors in a detailed and systematic approach, it is believed that the HEP will be reduced as other factors are also affected.

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Noventya Cahyani, Salma, M. Tutuk Safirin, Dwi Sukma Donoriyanto und Nur Rahmawati. „Human Error Analysis to Minimize Work Accidents Using the HEART and SHERPA Methods at PT. Wonojati Wijoyo“. PROZIMA (Productivity, Optimization and Manufacturing System Engineering) 6, Nr. 1 (22.06.2022): 48–59. http://dx.doi.org/10.21070/prozima.v6i1.1569.

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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).

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Prasad, Mahendra, und A. J. Gaikwad. „Human error probability estimation by coupling simulator data and deterministic analysis“. Progress in Nuclear Energy 81 (Mai 2015): 22–29. http://dx.doi.org/10.1016/j.pnucene.2015.01.008.

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Lee, Seung Jun, Jaewhan Kim und Wondea Jung. „Quantitative estimation of the human error probability during soft control operations“. Annals of Nuclear Energy 57 (Juli 2013): 318–26. http://dx.doi.org/10.1016/j.anucene.2013.02.018.

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Karthick, M., C. Senthil Kumar und T. Paul Robert. „BAYES-HEP: Bayesian belief networks for estimation of human error probability“. Life Cycle Reliability and Safety Engineering 6, Nr. 3 (September 2017): 187–97. http://dx.doi.org/10.1007/s41872-017-0026-4.

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Can, Gülin Feryal. „Implementation of Heart and Dematel Integration to Steam Boiler Working Process“. Ergonomics International Journal 5, Nr. 2 (2021): 1–17. http://dx.doi.org/10.23880/eoij-16000269.

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Human Error Assessment and Reduction Technique (HEART) is a practical and powerful approach to prioritize errors related to human actions, based on probabilities. HEART can determine error producing conditions (EPCs) which cause human errors for different processes including main duties (MDs) and sub-duties (SDs). HEART can be applied quickly for any process where human reliability is important. In this study, HEART and advanced version of Decision Making Trial and Evaluation Laboratory (AV-DEMATEL) integration proposed by Can and Delice in 2018 was performed for evaluating human related errors in steam boiler working process. In this way, the interactions between MDs, SDs and EPCs in a steam boiler working process were considered to compute process error probability (PEP). Additionally, the applicability of the proposed approach by Can and Delice (2018) was demonstrated again.

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Ratriwardhani, Ratna Ayu, und Friska Ayu. „PENILAIAN PROBABILITAS HUMAN ERROR DI INDUSTRI TAMBANG BATUBARA“. Medical Technology and Public Health Journal 5, Nr. 1 (08.04.2021): 66–74. http://dx.doi.org/10.33086/mtphj.v5i1.1825.

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Based on data from the Health and Safety Executive, it can be concluded that as many as 90% of accidents are caused by human error. Coal mining is an industry that has a high risk of work accidents. If the mining process is not following procedures, then lives will be at stake. Human error probability assessment needs to be done because most accidents that occur in coal mining are caused by human error. HRA (Human Reliability Analysis) is part of the risk assessment process which aims to calculate the HEP value. HRA has been used in many studies to assess the risks involved in large, complex, and dangerous systems. The Success Likelihood Index Method (SLIM) is a method of analysis for human reliability. Prevention and control of human error need to be done at every stage of work. SLIM can analyze HEP at each stage of the work. SLIM aims to obtain a HEP value. To get the HEP value, we must first find the SLI (Success Likelihood Index) value. Finding the SLI value comes from a weighting questionnaire and PSF (Performance Shaping Factor) assessment that has been filled in by an expert judgment. After the HEP value is obtained, it can be seen which jobs fall into the safe risk level and which the risk cannot be accepted. Furthermore, risk reduction is carried out by making a task analysis of jobs that have a high hazard risk. Based on the research results, it can be seen the factors that cause a human error, namely unsafe conditions, unsafe actions, personal factors, and job factors. While the task that has the highest HEP value is on task 4, which is equal to 0,006932. The task with the smallest HEP value is task 1, amounting to 0,006478.

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Nurdiawati, Annisya Arumy, Lukman Handoko, Am Maisarah Disrinama, Haidar Natsir Amrullah, Denny Dermawan, Muhammad Shah und Fais Hamzah. „Human error probability analysis of overhead crane operation in steel fabrication company using SLIM-DEMATEL-ANP method“. MATEC Web of Conferences 204 (2018): 05012. http://dx.doi.org/10.1051/matecconf/201820405012.

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The accident record from a steel fabrication company in 2014-2017 shows that the most frequent accidents take place in overhead crane operation with a percentage of 42%. The overhead crane operation has the greatest potential of accidents with human error as the main cause. The purpose of this study is to determine what factors affect the occurrence of errors, to know how much HEPs, and to determine recommendations. The method used in this research is Success Likelihood Index Method (SLIM) with qualitative development using Decision Making Trial and Evaluation Laboratory (DEMATEL) which aims to establish the relationship among PSFs to be an easily comprehensible structured model by considering expert judgements and to solve dependency in a set of criteria. Analytic Network Process (ANP) is used to overcome the inconsistency of expert judgements and difficulty in selection and weighting. The calculation and analysis reveal that the highest Human Error Probability (HEP) value is shown by the task to handling or lifting with the value 0.000485. Impact assessment using the HEP value to determine probability and consequence is performed by expert judgements. Improvement recommendations are prioritized for high rating error tasks using Error Reduction Analysis.

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Utama, As Shiddiq Putra, Willy Tambunan und Lina Dianati Fathimahhayati. „Analisis Human Error pada Proses Produksi Keramik dengan Menggunakan Metode HEART dan SHERPA“. Jurnal INTECH Teknik Industri Universitas Serang Raya 6, Nr. 1 (27.06.2020): 12–22. http://dx.doi.org/10.30656/intech.v6i1.2114.

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Unit Pelaksana Teknis Dinas Pusat Pengembangan Koperasi dan Usaha Kecil Menengah Kota Samarinda melakukan proses produksi untuk membantu masyarakat memenuhi kebutuhan produk tanpa harus memesan keluar pulau. UPTD P2KUKM mempunyai empat workshop, salah satunya workshop keramik, Workshop keramik memproduksi dua jenis yaitu earthenware dan stoneware. Proses produksi keramik dilakukan dengan mengandalkan tenaga manusia. Penelitian ini bertujuan mengidentifikasi human error yang terjadi pada proses produksi dan memberikan rekomendasi perbaikan untuk meminimalkan human error yang terjadi. Penelitian ini menggunakan metode SHERPA dan HEART dalam menganalisis human error yang terjadi. Metode kualitatif menggunakan SHERPA untuk mengidentifikasi human error. Metode kuantitatif dengan metode HEART untuk mengetahui nilai probabilitas terjadinya human error. Berdasarkan data yang diperoleh dengan menggunakan HTA, pada proses produksi keramik mempunyai 6 tahapan yang terbagi dalam 18 sub-pekerjaan. Analisis secara kualitatif menggunakan metode SHERPA memperoleh 18 kemungkinan error yang dapat dilakukan oleh pekerja. Berdasarkan analisis secara kuantitatif didapatkan nilai Human Error Probability (HEP) tertinggi yaitu pada sub-pekerjaan membersihkan tanah dari kotoran dengan nilai HEP sebesar 0.99. Rekomendasi perbaikan untuk mengurangi terjadinya kesalahan manusia (human error) yaitu briefing sebelum melakukan pekerjaan, membuat display, membuat form checklist, melakukan pengawasan dan training. Meminimalkan human error pada suatu proses produksi secara tidak langsung mampu meningkatkan tingkat produktivitas pekerja.

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Hartomo, Hartomo, und Asih Setyorini. „ANALISIS HUMAN REABILITY DAN PERBAIKAN PROSES PENGOLAHAN GULA RAFINASI“. Journal of Industrial Engineering Management 4, Nr. 2 (28.10.2019): 1–10. http://dx.doi.org/10.33536/jiem.v4i2.446.

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In Indonesia sugar needs is very significant along with the population, food and beverage industries, so the sugar industry is required to provide quality products. Determination of standardization of sugar quality in processing is influecend by machine conditions and human reability. This studyaims to analyze human error inrefiend sugar processing and determine recommedations for improvements neede to improve human reability in refined sugar processing. The methodused in this study is the Human Error Assesment and Reduction Techiue (HEART) and Human Error Reduction and Prediction Approach (SHERPA)which can calculate and provide solutions to the probability of the occurrence of errors. The results of this study indicate that the total human reability value of refined sugar processing is 5,34891 and there are 4 improvenebt strategies, such as undertake briefing, make records by making checklist form and making display poster about cleanliness

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Song, Shiji, Yanshang Gong, Yuli Zhang, Gao Huang und Guang-Bin Huang. „Dimension Reduction by Minimum Error Minimax Probability Machine“. IEEE Transactions on Systems, Man, and Cybernetics: Systems 47, Nr. 1 (Januar 2017): 58–69. http://dx.doi.org/10.1109/tsmc.2016.2563395.

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Susilo, Mitasya. „HUMAN ERROR IDENTIFICATION IN BUS DRIVER WORK USING SHERPA AND HEART“. Journal of Industrial Engineering Management 5, Nr. 2 (22.11.2020): 62–69. http://dx.doi.org/10.33536/jiem.v5i2.730.

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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

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Catelani, Marcantonio, Lorenzo Ciani, Giulia Guidi und Gabriele Patrizi. „Human error probability estimation for safety and diagnostic systems in railway engineering“. Measurement: Sensors 18 (Dezember 2021): 100105. http://dx.doi.org/10.1016/j.measen.2021.100105.

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Khan, Faisal I., Paul R. Amyotte und Dean G. DiMattia. „HEPI: A new tool for human error probability calculation for offshore operation“. Safety Science 44, Nr. 4 (April 2006): 313–34. http://dx.doi.org/10.1016/j.ssci.2005.10.008.

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Cho, Jaehyun, Yochan Kim, Jaewhan Kim, Jinkyun Park und Dong-San Kim. „Realistic estimation of human error probability through Monte Carlo thermal-hydraulic simulation“. Reliability Engineering & System Safety 193 (Januar 2020): 106673. http://dx.doi.org/10.1016/j.ress.2019.106673.

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Sun, Yanhao, Qi Zhang, Zhiming Yuan, Ying Gao und Shuxin Ding. „Quantitative Analysis of Human Error Probability in High-Speed Railway Dispatching Tasks“. IEEE Access 8 (2020): 56253–66. http://dx.doi.org/10.1109/access.2020.2981763.

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Di Bona, Gianpaolo, Domenico Falcone, Antonio Forcina, Filippo De Carlo und Luca Silvestri. „Quality Checks Logit Human Reliability (LHR): A New Model to Evaluate Human Error Probability (HEP)“. Mathematical Problems in Engineering 2021 (09.04.2021): 1–12. http://dx.doi.org/10.1155/2021/6653811.

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In the years, several approaches for human reliability analysis (HRA) have been developed. The aim of the present research is to propose a hybrid model to evaluate Human Error Probability (HEP). The new approach is based on logit-normal distribution, Nuclear Action Reliability Assessment (NARA), and Performance Shaping Factors (PSFs) relationship. In the research, shortcomings related to literature approaches are analyzed, especially the limitations of the working time. For this reason, PSFs after 8 hours (work standard) during emergency conditions were estimated. Therefore, the correlation between the advantages of these three methodologies allows proposing a HEP analysis during accident scenarios and emergencies; a fundamental issue to ensure the safety and reliability in industrial plants is emergency Mmnagement (EM). Applying EM methodology, two main aspects are analyzed: system reliability and human reliability. System reliability is strongly related to the reliability of its weakest component. During incidental situations, the weakest parts of the whole system are workers (human reliability) and accidental scenarios influence the operator’s ability to make decisions. This article proposes a new approach called Logit Human Reliability (LHR) that considers internal and external factors to estimate human reliability during emergencies. LHR has been applied in a pharmaceutical accident scenario, considering 24 hours of working time (more than 8 working hours). The results highlighted that the LHR method gives output data more in conformity with data banks than the conventional methods during the stress phase in an accident scenario.

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Richards, Brandon D. „Error Probabilities and Relationships in Assembly and Maintenance of Aircraft Engines“. Proceedings of the Human Factors and Ergonomics Society Annual Meeting 62, Nr. 1 (September 2018): 1599–603. http://dx.doi.org/10.1177/1541931218621361.

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Aircraft engine maintenance errors recorded during commercial revenue operation (field operation) share common causes and outcomes as those documented in original equipment manufacturer (OEM) and maintenance repair and overhaul (MRO) facilities. Utilizing data from one or more one of these sources can increase the understanding of skill-based, decision and perceptual errors occurring during assembly, operation and maintenance. The null hypothesis in this descriptive, explanatory research is: the nominal human error probability of removing and replacing a specified line replaceable unit (LRU)/component in field operations and OEM/MRO is the same. Quantitative analysis will include probabilities of human error for specific processes in both field operations and MRO/OEM environments determined by the Human Error Assessment and Reduction Technique (HEART). Qualitative analysis will include the classification of past errors utilizing the Human Factors Classification and Analysis System (HFACS). Accounting for all available types of data enables more precise and appropriate corrective actions.

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Ghasemi, Fakhradin, Mohammad Babamiri und Zahra Pashootan. „A comprehensive method for the quantification of medication error probability based on fuzzy SLIM“. PLOS ONE 17, Nr. 2 (25.02.2022): e0264303. http://dx.doi.org/10.1371/journal.pone.0264303.

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Medication errors can endanger the health and safety of patients and need to be managed appropriately. This study aimed at developing a new and comprehensive method for estimating the probability of medication errors in hospitals. An extensive literature review was conducted to identify factors affecting medication errors. Success Likelihood Index Methodology was employed for calculating the probability of medication errors. For weighting and rating of factors, the Fuzzy multiple attributive group decision making methodology and Fuzzy analytical hierarchical process were used, respectively. A case study in an emergency department was conducted using the framework. A total number of 17 factors affecting medication error were identified. Workload, patient safety climate, and fatigue were the most important ones. The case study showed that subtasks requiring nurses to read the handwritten of other nurses and physicians are more prone to human error. As there is no specific method for assessing the risk of medication errors, the framework developed in this study can be very useful in this regard. The developed technique was very easy to administer.

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Russo, Andrea, Lea Vojković, Filip Bojic und Rosanda Mulić. „The Conditional Probability for Human Error Caused by Fatigue, Stress and Anxiety in Seafaring“. Journal of Marine Science and Engineering 10, Nr. 11 (25.10.2022): 1576. http://dx.doi.org/10.3390/jmse10111576.

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Human error caused by the interaction and effect of fatigue, stress and anxiety in seafarers is the subject of this research. The human element is a major part of the maritime system. We used Bayesian networks to predict human error in maritime affairs by analysing interactions between people, technology, organisational and environmental factors which make up the specificity of the maritime system. Bayesian networks are graphical structures developed to represent the conditional dependencies among a number of variables and to make conditional conclusions related to the selected variables. Through the analysis of psychic causes such as stress, fatigue, anxiety and so on, the model can produce graphic diagrams indicating which rank on which type of vessel at which seafarers age contributes to an increase in conditional probability of human error. The contribution of the paper is to find the worst combinations of influencing variables that can lead to an increase in the risk of human error. The results show a significant level of fatigue and stress in all officers (engine and nautical), regardless of the type of vessel they serve. A strong presence of anxiety is also reported in all surveyed officers, with a higher degree between engine officers.

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Caputo, Antonio Casimiro, Pacifico Marcello Pelagagge und Paolo Salini. „Modeling errors in parts supply processes for assembly lines feeding“. Industrial Management & Data Systems 117, Nr. 6 (10.07.2017): 1263–94. http://dx.doi.org/10.1108/imds-08-2016-0333.

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Purpose The purpose of this paper is to develop a quantitative model to assess probability of errors and errors correction costs in parts feeding systems for assembly lines. Design/methodology/approach Event trees are adopted to model errors in the picking-handling-delivery-utilization of materials containers from the warehouse to assembly stations. Error probabilities and quality costs functions are developed to compare alternative feeding policies including kitting, line stocking and just-in-time delivery. A numerical case study is included. Findings This paper confirms with quantitative evidence the economic relevance of logistic errors (LEs) in parts feeding processes, a problem neglected in the existing literature. It also points out the most frequent or relevant error types and identifies specific corrective measures. Research limitations/implications While the model is general purpose, conclusions are specific to each applicative case and are not generalizable, and some modifications may be required to adapt it to specific industrial cases. When no experimental data are available, human error analysis should be used to estimate event probabilities based on underlying modes and causes of human error. Practical implications Production managers are given a quantitative decision tool to assess errors probability and errors correction costs in assembly lines parts feeding systems. This allows better comparing of alternative parts feeding policies and identifying corrective measures. Originality/value This is the first paper to develop quantitative models for estimating LEs and related quality cost, allowing a comparison between alternative parts feeding policies.

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Zetli, Sri. „Analisis Human Error dengan Pendekatan Metode SHERPA dan HEART pada Produksi Batu Bata UKM Yasin“. Jurnal INTECH Teknik Industri Universitas Serang Raya 7, Nr. 2 (31.12.2021): 147–56. http://dx.doi.org/10.30656/intech.v7i2.3934.

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Kesalahan kerja yang terjadi banyak diakibatkan oleh manusia itu sendiri yang disebut dengan human error. Human error yang sering terjadi dalam kegiatan produksi bisa merugikan perusahaan dalam mewujudkan efektivitas dan efisiensi produksi. Oleh karena itu maka perlu dilakukan perbaikan performansi pekerja untuk mengurangi seringnya terjadi kesalahan kerja. Beberapa metode dalam mengidentifikasi human error diantaranya metode SHERPA dan HEART. SHERPA suatu metode kualitatif dalam menganalisis human error yang menjadikan task level sebagai dasar inputnya. Sedangkan HEART adalah metode dalam menentukan resiko human error yang cepat, sederhana dan gampang dimengerti oleh para engineers dan juga human factors specialists. UKM Yasin merupakan salah satu UKM yang bergerak dalam produksi batu bata di Kota Batam. Proses pembuatan batu bata melalui beberapa tahapan yaitu proses pencetakan, proses pengeringan dan proses pembakaran. Permasalahan yang masih sering terjadi yaitu kesalahan saat melakukan pekerjaan yang berakibat terhadap kecelakaan kerja dan juga berpengaruh terhadap output produksi batu bata, hal ini disebabkan oleh human error. Hasil penelitian untuk rekomendasi yang akan diperlukan untuk mereduksi error pada proses produksi batu bata dengan metode SHERPA yaitu melakukan pemeriksaan secara teliti dan rutin terhadap masing-masing proses dan memberikan pelatihan secara berkala terhadap pekerja. Peluang terjadinya error dalam setiap aktivitas pekerjaan pada produksi batu bata dengan menggunakan metode HEART dimana nilai human error probability yang paling besar yaitu 0.16. Proses yang mungkin terjadinya human error dalam tahapan proses produksi batu bata di UKM Yasin melalui nilai Human Error Probability (HEP) tertinggi yaitu 0.544 yang terdapat pada proses pembakaran batu bata.

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Safitri, Dian Mardi, Ayu Rachma Astriaty und Nataya C. Rizani. „Human Reliability Assessment dengan Metode Human Error Assessment and Reduction Technique pada Operator Stasiun Shroud PT. X“. Jurnal Rekayasa Sistem Industri 4, Nr. 1 (09.10.2017): 1. http://dx.doi.org/10.26593/jrsi.v4i1.1388.1-7.

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Human realibility is a big tricky problem. Human failure rates depend on three main factors, namely intrinsic, work environment, and stress. PT. X is a supplier for PT. LG Indonesia manufacturing products made from plastics. Human Realibility Assesment is conducted using HEART methods (Human Error Assessment and Reduction Technique). In the first phase, task analysis on operators’ activities is done using Hierarchical Task Analysis (HTA). The largest Human Error Probability was found when Operator No. 1 did not insert the flash side carefully. The value of this probability is 0.53424. This factor is concluded as the main cause to shroud defectives, which results in customer penalyzing the company.

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