A new risk assessment method based on the probability of human error: SPC-HEART
Yıl 2022,
Cilt: 6 Sayı: 2, 1390 - 1409, 31.12.2022
S. Cihan Köseoğlu
,
Elif Kılıç Delice
Öz
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.
Kaynakça
- 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
Yıl 2022,
Cilt: 6 Sayı: 2, 1390 - 1409, 31.12.2022
S. Cihan Köseoğlu
,
Elif Kılıç Delice
Kaynakça
- 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
Yıl 2022,
Cilt: 6 Sayı: 2, 1390 - 1409, 31.12.2022
S. Cihan Köseoğlu
,
Elif Kılıç Delice
Kaynakça
- 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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İnsan hata yapma olasılığına dayanan yeni bir risk değerlendirme metodu: SPC-HEART
Yıl 2022,
Cilt: 6 Sayı: 2, 1390 - 1409, 31.12.2022
S. Cihan Köseoğlu
,
Elif Kılıç Delice
Öz
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.
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