Laboratory Reliability Analysis Using the SPAR-H Approach: A Case Study on Soil Nitrogen Analysis

Yıl 2025, Cilt: 13 Sayı: 3, 1195 - 1207, 30.09.2025

Nurgül Zengin , Ertuğrul Ayyıldız

https://doi.org/10.29109/gujsc.1625155

Öz

This study examines the probability of human error in the soil nitrogen analysis process conducted in the Trabzon Forest Regional Directorate’s laboratory through the SPAR-H method. Applying the HRA approach to laboratory incidents highlights the significance of procedural guidelines, equipment, and factors such as personnel experience and training. In the analysis steps, all tasks were initially defined, followed by the determination of Performance Shaping Factor (PSF) levels. The findings reveal that the highest error probability was observed in the distillation unit (0.72), followed by the sieving stage (0.67). Working with hot samples and limited capacity in the distillation unit, as well as the heavy dust encountered during sieving, were identified as critical points in the process. In order to mitigate these risks, capacity enhancements, the use of protective equipment, and additional training programs were recommended. Moreover, the importance of considering mental fatigue during the analysis was emphasized. This study demonstrates the applicability of the SPAR-H method in laboratory settings and underlines its effectiveness beyond high-risk industries. The results provide valuable insights into occupational safety, efficiency, and laboratory accident prevention, offering a foundation for future research in similar domains.

Anahtar Kelimeler

SPAR-H , Human reliability analysis , Soil nitrogen analysis , Occupational health and safety

Proje Numarası

FYL-2024-15940

Laboratuvar Güvenilirlik Analizinde SPAR-H Yaklaşımı: Toprak Azot Analizi Örneği

Öz

Bu çalışma, Trabzon Orman Bölge Müdürlüğü laboratuvarında yürütülen toprak azot analizi sürecinde insan hata olasılıklarını SPAR-H yöntemiyle incelemektedir. HRA yaklaşımının laboratuvar kazalarına uygulanması, prosedürlerin ve ekipmanların yanı sıra personelin deneyim ve eğitim düzeyi gibi faktörlerin de önemini ortaya koymuştur. Analiz adımlarında öncelikle tüm görevler tanımlanmış, ardından Performansı Şekillendiren Faktörlerin (PŞF) seviyeleri belirlenmiştir. Elde edilen bulgular, en yüksek hata olasılığının distilasyon ünitesinde (0,72) gözlendiğini ve bunu eleme aşamasının (0,67) izlediğini göstermektedir. Destilasyon ünitesinde sıcak numuneyle çalışma ve kapasite eksikliği, eleme aşamasında ise yoğun tozun oluşturduğu sağlık riskleri sürecin kritik noktalarıdır. Bu riskleri azaltmak amacıyla kapasite artışı, koruyucu ekipman kullanımı ve ek eğitim programları önerilmiştir. Ayrıca analiz sırasında zihinsel yorgunluk gibi faktörlerin de göz önünde bulundurulması gerektiği vurgulanmıştır. Çalışma, SPAR-H yönteminin laboratuvar ortamlarında uygulanabilirliğini kanıtlamakta ve yüksek riskli endüstriler dışında da etkinliğinin altını çizmektedir. Elde edilen bulgular, iş güvenliği, verimlilik ve laboratuvar kazalarının önlenmesi konularında önemli veriler sunarak gelecekte yapılacak benzer araştırmalara yol göstermektedir.

Anahtar Kelimeler

SPAR-H , İnsan güvenilirlik analizi , Toprak azot analizi , İş sağlığı ve güvenliği

Destekleyen Kurum

Karadeniz Teknik Üniversitesi

Proje Numarası

FYL-2024-15940

Teşekkür

Bu çalışma Karadeniz Teknik Üniversitesi Bilimsel Araştırma Projeleri Birimi tarafından desteklenmiştir. Yazarlar Karadeniz Teknik Üniversitesi'ne teşekkür etmektedirler.

Kaynakça

• [1] C. D. Griffith and S. Mahadevan, “Inclusion of fatigue effects in human reliability analysis,” Reliab. Eng. Syst. Saf., vol. 96, no. 11, 2011, doi: 10.1016/j.ress.2011.06.005.
• [2] E. Uflaz, S. I. Sezer, E. Akyuz, O. Arslan, and R. E. Kurt, “A human reliability analysis for ship to ship LNG bunkering process under D-S evidence fusion HEART approach,” J. Loss Prev. Process Ind., vol. 80, 2022, doi: 10.1016/j.jlp.2022.104887.
• [3] S. A. Yıldızel and Y. Arslan, “Risk Factors Identification and Estimation for Glass Fiber Reinforced Concrete Production Sector TT - Cam Elyaf Takviyeli Beton Üretim Sektöründe Risk Faktörlerinin Belirlenmesi ve Tahmini,” Gazi Üniversitesi Fen Bilim. Derg. Part C Tasarım ve Teknol., vol. 5, no. 4, pp. 215–221, 2017, doi: 10.29109/http-gujsc-gazi-edu-tr.345755.
• [4] E. Yalçin, G. A. Çiftçioğlu, and B. Güzel, “Human reliability analysis methods,” Pamukkale Üniversitesi Mühendislik Bilim. Derg., vol. 30, no. 2, pp. 282–292, 2024.
• [5] P. H. Raabe, “Constant failure rate of redundant repairable hardware,” J. Eng. Gas Turbines Power, vol. 96, no. 3, 1974, doi: 10.1115/1.3445789.
• [6] E. N. Corlett, “Handbook of human reliability analysis with emphasis on nuclear power plant applications,” Appl. Ergon., vol. 12, no. 1, p. 36, 1981, doi: 10.1016/0003-6870(81)90094-6.
• [7] D. E. Embrey, P. Humphreys, E. A. Rosa, B. Kirwan, and K. Rea, “SLIM-MAUD: an approach to assessing human error probabilities using structured expert judgment Volume II Detailed analysis of the technical issues,” 1984. [Online]. Available: http://inis.iaea.org/search/search.aspx?orig_q=RN:16061396
• [8] J. C. Williams, “HEART - A PROPOSED METHOD FOR ACHIEVING HIGH RELIABILITY IN PROCESS OPERATION BY MEANS OF HUMAN FACTORS ENGINEERING TECHNOLOGY.,” 1985. doi: 10.1080/09617353.2015.11691046.
• [9] D. E. Embrey, “SHERPA: A systematic human error reduction and prediction approach,” in Proceedings of the international topical meeting on advances in human factors in nuclear power systems, 1986.
• [10] E. Hollnagel, Cognitive Reliability and Error Analysis Method (CREAM). 1998. doi: 10.1016/b978-0-08-042848-2.x5000-3.
• [11] S. E. Cooper, J. Wreathall, C. Thompson, M. Drouin, and D. Bley, “Knowledge-base for the new human reliability analysis method ‘A Technique for Human Error Analysis (ATHEANA),’” Int. Top. Meet. probabilistic Saf. assessmentmoving Towar. risk based Regul. Park City, UT, 1996.
• [12] D. I. Gertman, H. S. Blackman, J. L. Marble, C. Smith, R. L. Boring, and P. O’Reilly, “The SPAR H human reliability analysis method,” in American Nuclear Society 4th International Topical Meeting on Nuclear Plant Instrumentation, Control and Human Machine Interface Technology, 2004.
• [13] C. Niza, S. Silva, and M. L. Lima, “Occupational accident experience: Association with workers’ accident explanation and definition,” Saf. Sci., vol. 46, no. 6, 2008, doi: 10.1016/j.ssci.2007.11.015.
• [14] L. J. Bellamy, D. Lisbona, M. Johnson, E. Kooi, and H. J. Manuel, “The major accident failure rates Project: Concept phase,” HSE Research Report RR915, Health and Safety Executive, Bootle, UK, 2012.
• [15] V. Şölen, “Laboratuvar kazaları ve ilk yardım,” J. Fac. For. Istanbul Univ., vol. 32, no. 1, pp. 132–165, 2014, doi: 10.17099/jffiu.21947.
• [16] M. Omidvari, N. Mansouri, and J. Nouri, “A pattern of fire risk assessment and emergency management in educational center laboratories,” Saf. Sci., vol. 73, 2015, doi: 10.1016/j.ssci.2014.11.003.
• [17] M. Eyvazlou, A. Dadashpour Ahangar, A. Rahimi, M. R. Davarpanah, S. S. Sayyahi, and M. Mohebali, “Human reliability assessment in a 99Mo/99mTc generator production facility using the standardized plant analysis risk-human (SPAR-H) technique,” Int. J. Occup. Saf. Ergon., vol. 25, no. 2, pp. 321–330, Apr. 2019, doi: 10.1080/10803548.2017.1415832.
• [18] Y. Zhan et al., “Human reliability study on the door operation from the view of Deep Machine Learning,” Futur. Gener. Comput. Syst., vol. 99, 2019, doi: 10.1016/j.future.2018.11.055.
• [19] C. Taylor, S. Øie, and K. Gould, “Lessons learned from applying a new HRA method for the petroleum industry,” Reliab. Eng. Syst. Saf., vol. 194, 2020, doi: 10.1016/j.ress.2018.10.001.
• [20] J. Liu et al., “A study on assigning performance shaping factors of the SPAR-H method for adequacy human reliability analysis of nuclear power plants,” Int. J. Ind. Ergon., vol. 81, p. 103051, Jan. 2021, doi: 10.1016/J.ERGON.2020.103051.
• [21] W. Zhang, X. Meng, X. Yang, H. Lyu, X. Y. Zhou, and Q. Wang, “A Practical Risk-Based Model for Early Warning of Seafarer Errors Using Integrated Bayesian Network and SPAR-H,” Int. J. Environ. Res. Public Health, vol. 19, no. 16, 2022, doi: 10.3390/ijerph191610271.
• [22] S. Il Ahn, R. E. Kurt, and E. Akyuz, “Application of a SPAR-H based framework to assess human reliability during emergency response drill for man overboard on ships,” Ocean Eng., vol. 251, p. 111089, May 2022, doi: 10.1016/J.OCEANENG.2022.111089.
• [23] L. Ma, X. Ma, P. Xing, and F. Yu, “A hybrid approach based on the HFACS-FBN for identifying and analysing human factors for fire and explosion accidents in the laboratory,” J. Loss Prev. Process Ind., vol. 75, 2022, doi: 10.1016/j.jlp.2021.104675.
• [24] Z. Lu, “Analysis of China students’ laboratory accidents in the past 39 years and the laboratory management reform in the future,” Educ. Chem. Eng., vol. 42, 2023, doi: 10.1016/j.ece.2022.12.001.
• [25] G. Elidolu, S. Il Ahn, S. Ilke Sezer, R. Emek Kurt, E. Akyuz, and P. Gardoni, “Applying evidential reasoning extended SPAR-H modelling to analyse human reliability on crude oil tanker cargo operation,” Saf. Sci., vol. 164, 2023, doi: 10.1016/j.ssci.2023.106169.
• [26] Y. He, N. S. Kuai, L. M. Deng, Z. L. Wang, and M. J. Peng, “An investigation into accidents in laboratories in universities in China caused by human error: A study based on improved CREAM and SPAR-H,” Heliyon, vol. 10, no. 7, Apr. 2024, doi: 10.1016/j.heliyon.2024.e28897.
• [27] W. Si and L. Niu, “Enhancing Human Reliability Prediction in Smart Tower Crane Interfaces: A Refined Approach Using Simplified Plant Analysis Risk–Human Reliability Assessment and the Decision Making Trial and Evaluation Laboratory–Analytic Network Process,” Build. 2024, Vol. 14, Page 1083, vol. 14, no. 4, p. 1083, Apr. 2024, doi: 10.3390/BUILDINGS14041083.
• [28] X. Liu, S. Yan, X. Zhang, and W. Ahmed, “Dynamic human reliability analysis method for nuclear power plant main control room based on SPAR-H and SD,” Nucl. Eng. Technol., vol. 57, no. 3, p. 103253, Mar. 2025, doi: 10.1016/J.NET.2024.10.015.
• [29] Z. Mosavianasl, A. Babaeipouya, and R. Borun, “Evaluation of human reliability in steel industry using SPAR-H and CREAM techniques,” Pakistan J. Med. Heal. Sci., vol. 12, no. 2, 2018.
• [30] L. X. Hou, R. Liu, H. C. Liu, and S. Jiang, “Two decades on human reliability analysis: A bibliometric analysis and literature review,” 2021. doi: 10.1016/j.anucene.2020.107969.