Research Article
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A new risk assessment method based on the probability of human error: SPC-HEART

Year 2022, Volume: 6 Issue: 2, 1390 - 1409, 31.12.2022

S. Cihan Köseoğlu , Elif Kılıç Delice

https://doi.org/10.56554/jtom.1205364
Cited By: 1

Abstract

It is crucial to minimize the probability of errors made by health professionals. The extent of this probability is considerably affected by task types, physical conditions of working environment, workload and working conditions. Moreover, it varies according to physical and mental characteristics of health staff. Thus, there are different risk levels for the tasks performed in the sector depending on the probability of human error. It is also possible to improve the quality of health services by appropriately matching health professionals with a specific task according to these risk levels and balancing workloads accordingly. This study proposes SPC-HEART method, which is a new type of HEART model based on SWARA and PCA methods, in order to explore probability of human errors made by health professions. The EPCs’ importance weights were calculated by employing SWARA method and the combined effect of physical and mental workload factors for each employee were determined by using PCA method. As a result, a proactive human error prevention approach has been developed in order to evaluate error making potentials of each employee separately. The effectiveness of the proposed approach has been proven by real practices with nurses.

Keywords

Human Error HEART SWARA PCA Risk evaluation

References

  • Akyuz, E., Celik, M. & Cebi, S. (2016). A phase of comprehensive research to determine marine-specific EPC values in human error assessment and reduction technique. Saf Sci, 87, pp.63–75. doi: https://doi.org/10.1016/j.ssci.2016.03.013
  • Aliabadi, M. M. (2021). Human error analysis in furnace start-up operation using HEART under intuitionistic fuzzy environment, Journal of Loss Prevention in the Process Industries, Vol. 69, 104372. doi: https://doi.org/10.1016/j.jlp.2020.104372.
  • Burton, A. (1935). Human calorimetry: II. the average temperature of the tissues of the body: three figures. J. Nutr., 9 (3), pp.261–280. doi: https://doi.org/10.1093/jn/9.3.261
  • Castiglia, F. & Giardina, M. (2013). Analysis of operator human errors in hydrogen refuelling stations: comparison between human rate assessment techniques. Int J Hydrogen Energy, 38 (2), pp.1166–1176. doi: https://doi.org/10.1016/j.ijhydene.2012.10.092
  • Dunteman G, H. (1989). Principal components analysis (quantitative applications in the social sciences), 1st ed.; SAGE Publications; California, USA, pp.7–55.
  • Fang, L., Xiao, B., Yu, H., You, Q. (2018). A stable systemic risk ranking in china’s banking sector: based on principal component analysis. Physica A: Statistical Mechanics and its Applications, 492, pp. 1998–2006. doi: https://doi.org/10.1016/j.physa.2017.11.115
  • Garvey, P. R. (2001). Track 2: Implementing a risk management process for a large scale information system upgrade- a case study. INCOSE, 4 (1), pp.14–18. doi: https://doi.org/10.1002/inst.20014115.
  • Guyton, A. C. & Hall, J. E. (2013). Tıbbi Fizyoloji. Çeviri Ed: Prof. Dr. Berrak ÇAĞLAYAN YEĞEN. Nobel Tıp Kitapevleri, 868-877, İstanbul.
  • Hall, J. C.: Rosbash, M.; Young, Michael. W. (2017). Discoveries of molecular mechanisms controlling the circadian rhythm. The University of Maine, pp. 1-7. https://www.nobelprize.org/uploads/2018/06/press39.pdf
  • Hart, S. G., & Staveland, L. E. (1988). Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research. Human Mental Workload, 139–183. doi: https://doi.org/10.1016/s0166- 4115(08)62386-9
  • Jollife, I. T. & Cadima, J. (2016). Principal Component analysis: a review and recent developments. Philosophical Transactions of the Royal Society A: Mathematical, Pzhouhysical and Engineering Sciences, 374[2065]. doi: https://doi.org/10.1098/rsta.2015.0202
  • Kandemir, C. & Celik, M. (2021). Determining the error producing conditions in marine engineering maintenance and operations through HFACS-MMO, Reliability Engineering & System Safety, Vol. 206, 107308. doi: https://doi.org/10.1016/j.ress.2020.107308.
  • Keršulienė, V., Zavadskas, E. K. & Turskis, Z. (2010). Selection Of rational dispute resolution method by applying new step-wise weight assessment ratio analysis (SWARA). J Bus Econ Manag, 11 (2), pp.243–258. doi: https://doi.org/10.3846/jbem.2010.12
  • Kirwan, B. (1988). A comparative evaluation of five human reliability assessment techniques. In Human Factors and Decision Making: Their Influence on Safety and Reliability, Elsevier; London, U.K., pp.87–109.
  • Kotek, L., Zuma, Z., Blecha, P. & Mukhametzianova, L. (2016). In Risk based workload and staffing level analysis. Risk, Reliability and Safety: Innovating Theory and Practice, Walls, L.; Revie, M.; Bedford, T. Eds.; CRC Press, London, pp. 87-90. doi: https://doi.org/10.1201/9781315374987
  • Kumar, A. M., Rajakarunakaran, S. & Arumuga Prabhu, V. (2017). Application of fuzzy HEART and expert elicitation for quantifying human error probabilities in LPG refuelling station, Journal of Loss Prevention in the Process Industries, Vol. 48, 186–198. doi: https://doi.org/10.1016/j.jlp.2017.04.021.
  • Kurata, Y. B., Acula, D. J. L., Galingan, R. L., Palines, A. M. J. & Viterbo, J. C. L. (2015). Human Error Reduction for Cost Efficiency Improvement in the Butchery Area of a Chicken Processing Company, Procedia Manufacturing,Vol. 3, 346–353. doi: https://doi.org/10.1016/j.promfg.2015.07.170.
  • Lucas-Estañ, M. C., Sepulcre, M., Raptis, T. P., Passarella, A., Conti, M. (2018). Emerging trends in hybrid wireless communication and data management for the Industry 4.0. Electronics, 7 (12), 400-405. doi: https://doi.org/10.3390/electronics7120400
  • Nunnally, J. C. & Bernstein, I. H. (1994). Psychometric theory 3rd edt., New York: McGraw-Hill, 232. ISBN: 007047849X,9780070478497
  • Oka, T. (2015). Psychogenic Fever: How psychological stress affects body temperature in the clinical population. Temperature, 2(3), pp.368–378. doi: https://doi.org/10.1080/23328940.2015.1056907
  • Rogers, A. E., Hwang, W. T., Scott, L. D., Aiken, L. H. & Dinges, D. F. (2004). The working hours of hospital staff nurses and patient safety. Health Aff. , 23 (4), pp.202–212. doi: https://doi.org/10.1377/hlthaff.23.4.202
  • Salthouse, T. A. (1991). Mediation of adult age differences in cognition by reductions in working memory and speed of processing. Psychol Sci, 2 (3), pp.179–183. doi: https://doi.org/10.1111/j.1467-9280.1991.tb00127.x
  • Shlens, J. (2014). A tutorial on principal component analysis 2005. Educational International Journal of Remote Sensing, 51(2), pp.1–12. Google Scholar
  • Stampi, C. (1992). Why We Nap, Birkhåuser: Boston, pp.142–258. doi: https://www.gwern.net/docs/zeo/1992-stampi-whywenap.pdf
  • Tharwat, A. (2016). Principal component analysis- a tutorial. International Journal of Applied Pattern Recognition, 3 (3), pp.197–240. doi: https://doi.org/10.1504/IJAPR.2016.079733
  • Torres, Y., Nadeau, S. & Landau, K. (2021). Classification and quantification of human error in manufacturing: a case study in complex manual assembly, Appl. Sci., Vol. 11, No. 2, 749. doi: https://doi.org/10.3390/app11020749
  • Wang, W., Liu, X. & Qin, Y. (2018). A modified HEART method with FANP for human error assessment in high-speed railway dispatching tasks, International Journal of Industrial Ergonomics, Vol. 67, 242–258. doi: https://doi.org/10.1016/j.ergon.2018.06.002.
  • Warm, J. S. , Dember, W. N. & Hancock, P. A. (1996). Vigilance and workload in automated systems. In R. Parasuraman & M. Mouloua (Eds.), Automation and Human Performance: Theory and Applications. Mahwah, NJ: Lawrence Erlbaum, 183-200. Google Scholar ISBN: 9781315137957
  • Weaver, M. D., Sletten, T. L., Foster, R. G., Gozal, D., Klerman, E. B., Rajaratnam, S. M. W., Roenneberg, T., Takahashi, J. S., Turek, F. W., Vitiello, M. v., Young, M. W. & Czeisler, C. A. (2021). Adverse impact of polyphasic sleep patterns in humans: report of the national sleep foundation sleep timing and variability consensus panel. Sleep Health, 7 (3), pp.293–302. doi: https://doi.org/10.1016/j.sleh.2021.02.009
  • WHO. (2018). A global imperative for universal health coverage. Delivering Quality Health Services, World Health Organization, OECD, and International Bank for Reconstruction and Development/The World Bank; pp. 45-55. ISBN:9789241513906
  • Williams, J. C. (1988). Data-based method for assessing and reducing human error to improve operational performance. IEEE Fourth Conference on Human Factors and Power Plants, Monterey, USA, pp. 436-450. doi: https://doi.org/10.1109/HFPP.1988.27540
  • Wu, Y., Wang, J., Luo, C., Hu, S., Lin, X., Anderson, A. E., Bruera, E., Yang, X., Wei, S. & Qian, Y. A. (2020). Comparison of burnout frequency among oncology physicians and nurses working on the frontline and usual wards during the covıd-19 epidemic in Wuhan, China. J Pain Symptom Manage, 60 (1), pp.60–65. doi: https://doi.org/10.1016/j.jpainsymman.2020.04.008 .
  • Yılmaz Kaya, B. (2022). Minimizing OHS Risks with Spherical Fuzzy Sets as a Verdict to Inventory Management: A Case Regarding Energy Companies. Discrete Dynamics in Nature and Society, Article ID 9511339, 1-26. https://doi.org/10.1155/2022/9511339
  • Yılmaz Kaya, B. (2022). Contemplation and analysis of pandemic impacts on accommodation industry and a system reformulation proposal with Kano model: Turkey case. Current Issues in Tourism, 25(8), 1226- 1241. https://doi.org/10.1080/13683500.2021.2007860
  • Zhou, J. L., Lei, Y. & Chen, Y. (2019). A hybrid HEART method to estimate human error probabilities in locomotive driving process, Reliability Engineering and System Safety, 80–89. doi: https://doi.org/10.1016/j.ress.2019.03.001

Year 2022, Volume: 6 Issue: 2, 1390 - 1409, 31.12.2022

S. Cihan Köseoğlu , Elif Kılıç Delice

https://doi.org/10.56554/jtom.1205364
Cited By: 1

Abstract

Keywords

Human Error HEART SWARA PCA Risk evaluation İnsan Hatası HEART SWARA PCA Risk değerlendirme

References

  • Akyuz, E., Celik, M. & Cebi, S. (2016). A phase of comprehensive research to determine marine-specific EPC values in human error assessment and reduction technique. Saf Sci, 87, pp.63–75. doi: https://doi.org/10.1016/j.ssci.2016.03.013
  • Aliabadi, M. M. (2021). Human error analysis in furnace start-up operation using HEART under intuitionistic fuzzy environment, Journal of Loss Prevention in the Process Industries, Vol. 69, 104372. doi: https://doi.org/10.1016/j.jlp.2020.104372.
  • Burton, A. (1935). Human calorimetry: II. the average temperature of the tissues of the body: three figures. J. Nutr., 9 (3), pp.261–280. doi: https://doi.org/10.1093/jn/9.3.261
  • Castiglia, F. & Giardina, M. (2013). Analysis of operator human errors in hydrogen refuelling stations: comparison between human rate assessment techniques. Int J Hydrogen Energy, 38 (2), pp.1166–1176. doi: https://doi.org/10.1016/j.ijhydene.2012.10.092
  • Dunteman G, H. (1989). Principal components analysis (quantitative applications in the social sciences), 1st ed.; SAGE Publications; California, USA, pp.7–55.
  • Fang, L., Xiao, B., Yu, H., You, Q. (2018). A stable systemic risk ranking in china’s banking sector: based on principal component analysis. Physica A: Statistical Mechanics and its Applications, 492, pp. 1998–2006. doi: https://doi.org/10.1016/j.physa.2017.11.115
  • Garvey, P. R. (2001). Track 2: Implementing a risk management process for a large scale information system upgrade- a case study. INCOSE, 4 (1), pp.14–18. doi: https://doi.org/10.1002/inst.20014115.
  • Guyton, A. C. & Hall, J. E. (2013). Tıbbi Fizyoloji. Çeviri Ed: Prof. Dr. Berrak ÇAĞLAYAN YEĞEN. Nobel Tıp Kitapevleri, 868-877, İstanbul.
  • Hall, J. C.: Rosbash, M.; Young, Michael. W. (2017). Discoveries of molecular mechanisms controlling the circadian rhythm. The University of Maine, pp. 1-7. https://www.nobelprize.org/uploads/2018/06/press39.pdf
  • Hart, S. G., & Staveland, L. E. (1988). Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research. Human Mental Workload, 139–183. doi: https://doi.org/10.1016/s0166- 4115(08)62386-9
  • Jollife, I. T. & Cadima, J. (2016). Principal Component analysis: a review and recent developments. Philosophical Transactions of the Royal Society A: Mathematical, Pzhouhysical and Engineering Sciences, 374[2065]. doi: https://doi.org/10.1098/rsta.2015.0202
  • Kandemir, C. & Celik, M. (2021). Determining the error producing conditions in marine engineering maintenance and operations through HFACS-MMO, Reliability Engineering & System Safety, Vol. 206, 107308. doi: https://doi.org/10.1016/j.ress.2020.107308.
  • Keršulienė, V., Zavadskas, E. K. & Turskis, Z. (2010). Selection Of rational dispute resolution method by applying new step-wise weight assessment ratio analysis (SWARA). J Bus Econ Manag, 11 (2), pp.243–258. doi: https://doi.org/10.3846/jbem.2010.12
  • Kirwan, B. (1988). A comparative evaluation of five human reliability assessment techniques. In Human Factors and Decision Making: Their Influence on Safety and Reliability, Elsevier; London, U.K., pp.87–109.
  • Kotek, L., Zuma, Z., Blecha, P. & Mukhametzianova, L. (2016). In Risk based workload and staffing level analysis. Risk, Reliability and Safety: Innovating Theory and Practice, Walls, L.; Revie, M.; Bedford, T. Eds.; CRC Press, London, pp. 87-90. doi: https://doi.org/10.1201/9781315374987
  • Kumar, A. M., Rajakarunakaran, S. & Arumuga Prabhu, V. (2017). Application of fuzzy HEART and expert elicitation for quantifying human error probabilities in LPG refuelling station, Journal of Loss Prevention in the Process Industries, Vol. 48, 186–198. doi: https://doi.org/10.1016/j.jlp.2017.04.021.
  • Kurata, Y. B., Acula, D. J. L., Galingan, R. L., Palines, A. M. J. & Viterbo, J. C. L. (2015). Human Error Reduction for Cost Efficiency Improvement in the Butchery Area of a Chicken Processing Company, Procedia Manufacturing,Vol. 3, 346–353. doi: https://doi.org/10.1016/j.promfg.2015.07.170.
  • Lucas-Estañ, M. C., Sepulcre, M., Raptis, T. P., Passarella, A., Conti, M. (2018). Emerging trends in hybrid wireless communication and data management for the Industry 4.0. Electronics, 7 (12), 400-405. doi: https://doi.org/10.3390/electronics7120400
  • Nunnally, J. C. & Bernstein, I. H. (1994). Psychometric theory 3rd edt., New York: McGraw-Hill, 232. ISBN: 007047849X,9780070478497
  • Oka, T. (2015). Psychogenic Fever: How psychological stress affects body temperature in the clinical population. Temperature, 2(3), pp.368–378. doi: https://doi.org/10.1080/23328940.2015.1056907
  • Rogers, A. E., Hwang, W. T., Scott, L. D., Aiken, L. H. & Dinges, D. F. (2004). The working hours of hospital staff nurses and patient safety. Health Aff. , 23 (4), pp.202–212. doi: https://doi.org/10.1377/hlthaff.23.4.202
  • Salthouse, T. A. (1991). Mediation of adult age differences in cognition by reductions in working memory and speed of processing. Psychol Sci, 2 (3), pp.179–183. doi: https://doi.org/10.1111/j.1467-9280.1991.tb00127.x
  • Shlens, J. (2014). A tutorial on principal component analysis 2005. Educational International Journal of Remote Sensing, 51(2), pp.1–12. Google Scholar
  • Stampi, C. (1992). Why We Nap, Birkhåuser: Boston, pp.142–258. doi: https://www.gwern.net/docs/zeo/1992-stampi-whywenap.pdf
  • Tharwat, A. (2016). Principal component analysis- a tutorial. International Journal of Applied Pattern Recognition, 3 (3), pp.197–240. doi: https://doi.org/10.1504/IJAPR.2016.079733
  • Torres, Y., Nadeau, S. & Landau, K. (2021). Classification and quantification of human error in manufacturing: a case study in complex manual assembly, Appl. Sci., Vol. 11, No. 2, 749. doi: https://doi.org/10.3390/app11020749
  • Wang, W., Liu, X. & Qin, Y. (2018). A modified HEART method with FANP for human error assessment in high-speed railway dispatching tasks, International Journal of Industrial Ergonomics, Vol. 67, 242–258. doi: https://doi.org/10.1016/j.ergon.2018.06.002.
  • Warm, J. S. , Dember, W. N. & Hancock, P. A. (1996). Vigilance and workload in automated systems. In R. Parasuraman & M. Mouloua (Eds.), Automation and Human Performance: Theory and Applications. Mahwah, NJ: Lawrence Erlbaum, 183-200. Google Scholar ISBN: 9781315137957
  • Weaver, M. D., Sletten, T. L., Foster, R. G., Gozal, D., Klerman, E. B., Rajaratnam, S. M. W., Roenneberg, T., Takahashi, J. S., Turek, F. W., Vitiello, M. v., Young, M. W. & Czeisler, C. A. (2021). Adverse impact of polyphasic sleep patterns in humans: report of the national sleep foundation sleep timing and variability consensus panel. Sleep Health, 7 (3), pp.293–302. doi: https://doi.org/10.1016/j.sleh.2021.02.009
  • WHO. (2018). A global imperative for universal health coverage. Delivering Quality Health Services, World Health Organization, OECD, and International Bank for Reconstruction and Development/The World Bank; pp. 45-55. ISBN:9789241513906
  • Williams, J. C. (1988). Data-based method for assessing and reducing human error to improve operational performance. IEEE Fourth Conference on Human Factors and Power Plants, Monterey, USA, pp. 436-450. doi: https://doi.org/10.1109/HFPP.1988.27540
  • Wu, Y., Wang, J., Luo, C., Hu, S., Lin, X., Anderson, A. E., Bruera, E., Yang, X., Wei, S. & Qian, Y. A. (2020). Comparison of burnout frequency among oncology physicians and nurses working on the frontline and usual wards during the covıd-19 epidemic in Wuhan, China. J Pain Symptom Manage, 60 (1), pp.60–65. doi: https://doi.org/10.1016/j.jpainsymman.2020.04.008 .
  • Yılmaz Kaya, B. (2022). Minimizing OHS Risks with Spherical Fuzzy Sets as a Verdict to Inventory Management: A Case Regarding Energy Companies. Discrete Dynamics in Nature and Society, Article ID 9511339, 1-26. https://doi.org/10.1155/2022/9511339
  • Yılmaz Kaya, B. (2022). Contemplation and analysis of pandemic impacts on accommodation industry and a system reformulation proposal with Kano model: Turkey case. Current Issues in Tourism, 25(8), 1226- 1241. https://doi.org/10.1080/13683500.2021.2007860
  • Zhou, J. L., Lei, Y. & Chen, Y. (2019). A hybrid HEART method to estimate human error probabilities in locomotive driving process, Reliability Engineering and System Safety, 80–89. doi: https://doi.org/10.1016/j.ress.2019.03.001

Year 2022, Volume: 6 Issue: 2, 1390 - 1409, 31.12.2022

S. Cihan Köseoğlu , Elif Kılıç Delice

https://doi.org/10.56554/jtom.1205364
Cited By: 1

Abstract

Keywords

Human Error HEART SWARA PCA Risk evaluation İnsan Hatası HEART SWARA PCA Risk değerlendirme

References

  • Akyuz, E., Celik, M. & Cebi, S. (2016). A phase of comprehensive research to determine marine-specific EPC values in human error assessment and reduction technique. Saf Sci, 87, pp.63–75. doi: https://doi.org/10.1016/j.ssci.2016.03.013
  • Aliabadi, M. M. (2021). Human error analysis in furnace start-up operation using HEART under intuitionistic fuzzy environment, Journal of Loss Prevention in the Process Industries, Vol. 69, 104372. doi: https://doi.org/10.1016/j.jlp.2020.104372.
  • Burton, A. (1935). Human calorimetry: II. the average temperature of the tissues of the body: three figures. J. Nutr., 9 (3), pp.261–280. doi: https://doi.org/10.1093/jn/9.3.261
  • Castiglia, F. & Giardina, M. (2013). Analysis of operator human errors in hydrogen refuelling stations: comparison between human rate assessment techniques. Int J Hydrogen Energy, 38 (2), pp.1166–1176. doi: https://doi.org/10.1016/j.ijhydene.2012.10.092
  • Dunteman G, H. (1989). Principal components analysis (quantitative applications in the social sciences), 1st ed.; SAGE Publications; California, USA, pp.7–55.
  • Fang, L., Xiao, B., Yu, H., You, Q. (2018). A stable systemic risk ranking in china’s banking sector: based on principal component analysis. Physica A: Statistical Mechanics and its Applications, 492, pp. 1998–2006. doi: https://doi.org/10.1016/j.physa.2017.11.115
  • Garvey, P. R. (2001). Track 2: Implementing a risk management process for a large scale information system upgrade- a case study. INCOSE, 4 (1), pp.14–18. doi: https://doi.org/10.1002/inst.20014115.
  • Guyton, A. C. & Hall, J. E. (2013). Tıbbi Fizyoloji. Çeviri Ed: Prof. Dr. Berrak ÇAĞLAYAN YEĞEN. Nobel Tıp Kitapevleri, 868-877, İstanbul.
  • Hall, J. C.: Rosbash, M.; Young, Michael. W. (2017). Discoveries of molecular mechanisms controlling the circadian rhythm. The University of Maine, pp. 1-7. https://www.nobelprize.org/uploads/2018/06/press39.pdf
  • Hart, S. G., & Staveland, L. E. (1988). Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research. Human Mental Workload, 139–183. doi: https://doi.org/10.1016/s0166- 4115(08)62386-9
  • Jollife, I. T. & Cadima, J. (2016). Principal Component analysis: a review and recent developments. Philosophical Transactions of the Royal Society A: Mathematical, Pzhouhysical and Engineering Sciences, 374[2065]. doi: https://doi.org/10.1098/rsta.2015.0202
  • Kandemir, C. & Celik, M. (2021). Determining the error producing conditions in marine engineering maintenance and operations through HFACS-MMO, Reliability Engineering & System Safety, Vol. 206, 107308. doi: https://doi.org/10.1016/j.ress.2020.107308.
  • Keršulienė, V., Zavadskas, E. K. & Turskis, Z. (2010). Selection Of rational dispute resolution method by applying new step-wise weight assessment ratio analysis (SWARA). J Bus Econ Manag, 11 (2), pp.243–258. doi: https://doi.org/10.3846/jbem.2010.12
  • Kirwan, B. (1988). A comparative evaluation of five human reliability assessment techniques. In Human Factors and Decision Making: Their Influence on Safety and Reliability, Elsevier; London, U.K., pp.87–109.
  • Kotek, L., Zuma, Z., Blecha, P. & Mukhametzianova, L. (2016). In Risk based workload and staffing level analysis. Risk, Reliability and Safety: Innovating Theory and Practice, Walls, L.; Revie, M.; Bedford, T. Eds.; CRC Press, London, pp. 87-90. doi: https://doi.org/10.1201/9781315374987
  • Kumar, A. M., Rajakarunakaran, S. & Arumuga Prabhu, V. (2017). Application of fuzzy HEART and expert elicitation for quantifying human error probabilities in LPG refuelling station, Journal of Loss Prevention in the Process Industries, Vol. 48, 186–198. doi: https://doi.org/10.1016/j.jlp.2017.04.021.
  • Kurata, Y. B., Acula, D. J. L., Galingan, R. L., Palines, A. M. J. & Viterbo, J. C. L. (2015). Human Error Reduction for Cost Efficiency Improvement in the Butchery Area of a Chicken Processing Company, Procedia Manufacturing,Vol. 3, 346–353. doi: https://doi.org/10.1016/j.promfg.2015.07.170.
  • Lucas-Estañ, M. C., Sepulcre, M., Raptis, T. P., Passarella, A., Conti, M. (2018). Emerging trends in hybrid wireless communication and data management for the Industry 4.0. Electronics, 7 (12), 400-405. doi: https://doi.org/10.3390/electronics7120400
  • Nunnally, J. C. & Bernstein, I. H. (1994). Psychometric theory 3rd edt., New York: McGraw-Hill, 232. ISBN: 007047849X,9780070478497
  • Oka, T. (2015). Psychogenic Fever: How psychological stress affects body temperature in the clinical population. Temperature, 2(3), pp.368–378. doi: https://doi.org/10.1080/23328940.2015.1056907
  • Rogers, A. E., Hwang, W. T., Scott, L. D., Aiken, L. H. & Dinges, D. F. (2004). The working hours of hospital staff nurses and patient safety. Health Aff. , 23 (4), pp.202–212. doi: https://doi.org/10.1377/hlthaff.23.4.202
  • Salthouse, T. A. (1991). Mediation of adult age differences in cognition by reductions in working memory and speed of processing. Psychol Sci, 2 (3), pp.179–183. doi: https://doi.org/10.1111/j.1467-9280.1991.tb00127.x
  • Shlens, J. (2014). A tutorial on principal component analysis 2005. Educational International Journal of Remote Sensing, 51(2), pp.1–12. Google Scholar
  • Stampi, C. (1992). Why We Nap, Birkhåuser: Boston, pp.142–258. doi: https://www.gwern.net/docs/zeo/1992-stampi-whywenap.pdf
  • Tharwat, A. (2016). Principal component analysis- a tutorial. International Journal of Applied Pattern Recognition, 3 (3), pp.197–240. doi: https://doi.org/10.1504/IJAPR.2016.079733
  • Torres, Y., Nadeau, S. & Landau, K. (2021). Classification and quantification of human error in manufacturing: a case study in complex manual assembly, Appl. Sci., Vol. 11, No. 2, 749. doi: https://doi.org/10.3390/app11020749
  • Wang, W., Liu, X. & Qin, Y. (2018). A modified HEART method with FANP for human error assessment in high-speed railway dispatching tasks, International Journal of Industrial Ergonomics, Vol. 67, 242–258. doi: https://doi.org/10.1016/j.ergon.2018.06.002.
  • Warm, J. S. , Dember, W. N. & Hancock, P. A. (1996). Vigilance and workload in automated systems. In R. Parasuraman & M. Mouloua (Eds.), Automation and Human Performance: Theory and Applications. Mahwah, NJ: Lawrence Erlbaum, 183-200. Google Scholar ISBN: 9781315137957
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  • Yılmaz Kaya, B. (2022). Minimizing OHS Risks with Spherical Fuzzy Sets as a Verdict to Inventory Management: A Case Regarding Energy Companies. Discrete Dynamics in Nature and Society, Article ID 9511339, 1-26. https://doi.org/10.1155/2022/9511339
  • Yılmaz Kaya, B. (2022). Contemplation and analysis of pandemic impacts on accommodation industry and a system reformulation proposal with Kano model: Turkey case. Current Issues in Tourism, 25(8), 1226- 1241. https://doi.org/10.1080/13683500.2021.2007860
  • Zhou, J. L., Lei, Y. & Chen, Y. (2019). A hybrid HEART method to estimate human error probabilities in locomotive driving process, Reliability Engineering and System Safety, 80–89. doi: https://doi.org/10.1016/j.ress.2019.03.001

İnsan hata yapma olasılığına dayanan yeni bir risk değerlendirme metodu: SPC-HEART

Year 2022, Volume: 6 Issue: 2, 1390 - 1409, 31.12.2022

S. Cihan Köseoğlu , Elif Kılıç Delice

https://doi.org/10.56554/jtom.1205364
Cited By: 1

Abstract

Çalışanların hata yapma potansiyellerinin azaltılması iş sağlığı ve güvenliğinin artırılması ve dolayısıyla iş veriminin ve kalitesinin artırılması için son derece önemlidir. Hata yapma potansiyeli, çalışanların yerine getirdikleri görevlere, çalışma ortamına, iş yüklerine ve iş koşullarına bağlıdır. Ayrıca her çalışanın görev bazında hata yapma olasılığı kişinin fiziksel ve zihinsel özellikleri bakımından farklılık göstermektedir. Hata yapma olasılıklarına bağlı olarak görevlerin farklı risk düzeyleri mevcuttur. Bu risk düzeylerine göre çalışanlara görev atanması ve iş yüklerinin dengelenmesi iş kazalarını azaltacak ve verimliliğin artmasına neden olacaktır. Bu çalışmada, görev bazında hata yapma olasılıklarına bağlı olarak risk değerlendirilmesi için SWARA ve PCA tabanlı yeni bir HEART yöntemi olan SPC-HEART yöntemi önerilmiştir. Karar vericilerin görüşleri dikkate alınarak hata üreten koşulların önem ağırlıkları SWARA yöntemi ile belirlenirken; her bir çalışan için fiziksel ve zihinsel iş yükü faktörlerinin bileşke etkisi PCA yöntemi ile ortaya çıkarılmıştır. Her bir çalışan için görev bazında hata potansiyellerini hesaplayan proaktif bir risk önleme yaklaşımı elde önerilmiştir. Önerilen yaklaşımın etkinliği hemşireler üzerinde yapılan bir gerçek hayat uygulaması ile gösterilmiştir.

Keywords

İnsan Hatası HEART SWARA PCA Risk Değerlendirme

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There are 35 citations in total.

Details

Primary Language Turkish
Subjects Industrial Engineering
Journal Section Research Article
Authors

S. Cihan Köseoğlu 0000-0001-5982-4168

Elif Kılıç Delice 0000-0002-3051-0496

Publication Date December 31, 2022
Submission Date November 15, 2022
Acceptance Date December 6, 2022
Published in Issue Year 2022 Volume: 6 Issue: 2

Cite

APA Köseoğlu, S. C., & Kılıç Delice, E. (2022). İnsan hata yapma olasılığına dayanan yeni bir risk değerlendirme metodu: SPC-HEART. Journal of Turkish Operations Management, 6(2), 1390-1409. https://doi.org/10.56554/jtom.1205364
AMA Köseoğlu SC, Kılıç Delice E. İnsan hata yapma olasılığına dayanan yeni bir risk değerlendirme metodu: SPC-HEART. JTOM. December 2022;6(2):1390-1409. doi:10.56554/jtom.1205364
Chicago Köseoğlu, S. Cihan, and Elif Kılıç Delice. “İnsan Hata Yapma olasılığına Dayanan Yeni Bir Risk değerlendirme Metodu: SPC-HEART”. Journal of Turkish Operations Management 6, no. 2 (December 2022): 1390-1409. https://doi.org/10.56554/jtom.1205364.
EndNote Köseoğlu SC, Kılıç Delice E (December 1, 2022) İnsan hata yapma olasılığına dayanan yeni bir risk değerlendirme metodu: SPC-HEART. Journal of Turkish Operations Management 6 2 1390–1409.
IEEE S. C. Köseoğlu and E. Kılıç Delice, “İnsan hata yapma olasılığına dayanan yeni bir risk değerlendirme metodu: SPC-HEART”, JTOM, vol. 6, no. 2, pp. 1390–1409, 2022, doi: 10.56554/jtom.1205364.
ISNAD Köseoğlu, S. Cihan - Kılıç Delice, Elif. “İnsan Hata Yapma olasılığına Dayanan Yeni Bir Risk değerlendirme Metodu: SPC-HEART”. Journal of Turkish Operations Management 6/2 (December 2022), 1390-1409. https://doi.org/10.56554/jtom.1205364.
JAMA Köseoğlu SC, Kılıç Delice E. İnsan hata yapma olasılığına dayanan yeni bir risk değerlendirme metodu: SPC-HEART. JTOM. 2022;6:1390–1409.
MLA Köseoğlu, S. Cihan and Elif Kılıç Delice. “İnsan Hata Yapma olasılığına Dayanan Yeni Bir Risk değerlendirme Metodu: SPC-HEART”. Journal of Turkish Operations Management, vol. 6, no. 2, 2022, pp. 1390-09, doi:10.56554/jtom.1205364.
Vancouver Köseoğlu SC, Kılıç Delice E. İnsan hata yapma olasılığına dayanan yeni bir risk değerlendirme metodu: SPC-HEART. JTOM. 2022;6(2):1390-409.

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