HumHID is a hazard identification process that uses cognitive work analysis techniques and human factors/error taxonomy information to help identify human related hazards and the possible causes of them so designs can be modified to mitigate or tolerate such hazards. To facilitate the usability of HumHID, a software tool was constructed to guide users through the methodology and to automate otherwise tedious activities. An initial pilot study of the HumHID method and tool was conducted with industrial personnel on an industry case study to assess its usability and usefulness prior to conducting a full case study. The feasibility trial results showed that, with some further improvements, the method and software tool could help process organisations identify human factors issues.
Get full access to this article
View all access options for this article.
References
1.
BaybuttP. (2002). Layers of protection analysis for human factors (LOPA-HF). Process Safety Progress, 21(2), 119-129.
2.
BaybuttP. (2003). Layers of protection analysis for human factors (LOPA-HF): An improved method for addressing human failures in process hazard analysis. Symposium on Human Error in Occupational Safety (pp. 163-175). Altanta, Georgia: Americal Society of Safety Engineers.
3.
BellamyL. J.GeyerT. A.WilkinsonJ. (2008). Development of a functional model which integrates human factors, safety management systems and wider organisational issues. Safety science, 46, 461-492.
4.
BullemerP. T.NimmoI. (1994). Understanding and supporting abnormal situation management in industrial process control environments: a new approach to trainingIEEE International Conference on Systems, Man, and Cybernetics. Humans, Information and Technology. (Vol. 1, pp. 391-396).
5.
CacciabueP. C. (2000). Human factors impact on risk analysis of complex systems. Journal of Hazardous Materials, 71(1-3), 101.
6.
CCPS. (1994). Guidelines for preventing human error in process safety. New York: Center for Chemical Process Safety of the American Institute of Chemical Engineers.
7.
EmbreyD. (1986). SHERPA: A systematic human error reduction and prediction approach. Paper presented at the International Meeting on Advances in Nuclear Power Systems, Knoxville, TN.
8.
GordonR.FlinR.MearnsK. (2005). Designing and evaluating a human factors investigation tool (HFIT) for accident analysis. Safety Science, 43(3), 147.
9.
HassallM. E.SandersonP. M.CameronI. T. (2010). Using cognitive work analysis techniques to identify human factors hazardsProceedings of the 54th Annual Meeting of the HFES. San Franciso, CA.
10.
HollnagelE. (1998). Cognitive reliability and error analysis method. Oxford: Elsevier.
KimJ. W.JungW. (2003). A taxonomy of performance influencing factors for human reliability analysis of emergency tasks. Journal of Loss Prevention in the Process Industries, 16(6), 479-495.
13.
KletzT. A. (2009). What went wrong? Case histories of process plant disasters and how they could have been avoided. Burlington, MA: Gulf Professional Pub.
14.
NaikarN.MoylanA.PearceB. (2006). Analysing activity in complex systems with cognitive work analysis: concepts, guidelines and case study for control task analysis. Theoretical Issues in Ergonomics Science, 7(4), 371-394.
15.
PaletzS. B. F.BearmanC.OrasanuJ.HolbrookJ. (2009). Socializing the Human Factors Analysis and Classification System: Incorporating Social Psychological Phenomena Into a Human Factors Error Classification System. Human Factors., 51(4), 435.
16.
PocockS.WritghtP.HarrisonM. (1999). THEA – A technique for human error assessment early in design. Paper presented at the RTO HFM Workshop on the Human Factor in System Reliability – Is Human Performance Predictable?, Siena, Italy.
17.
RantanenE. M.PalmerB., O.WiegmennD., A.MusiorskiK. M. (2006). Five-dimensional taxonomy to relate human errors and technological interventions in a human factors literature database. JASIS57(9), 1221.
18.
SandersonP. M. (2003). Cognitive Work Analysis across the system life-cycle: Achievements, challenges, and prospects in aviation. In EdkinsG.PfisterP. (Eds.), Innovation and consolidation in aviation. (Vol. 3, pp. 73-85). Aldershot, UK: Ashgate.
19.
SeligmannB.NémethE.HockingsK.McDonaldI.LeeJ.CameronI. T. (2010). A structured, blended hazard identification framework for advanced process diagnosis. Proc. Int’l Symp. Loss Prevention and Safety Promotion in the Process Industries, 1, 193-200, Brugge, Belgium.
20.
SeligmannB.NémethE.HockingsK.O’BrienC.CameronI. T. (2009). A blended hazard identification approach to support intelligent diagnosis of process systems. Paper presented at CHEMECA, Perth, WA.
21.
ShappellS. A.WiegmannD. A. (2000). The human factors analysis and classification system - HFACS. (DOT/FAA/AM-00/7).
22.
ShorrockS. T. (2002). Error classification for safety management. Finding the right approach. Paper presented at the Workshop on the Investigation and Reporting of Incidents and Accidents, Senate Room, Univ Glasgow.
23.
ShorrockS. T.KirwanB. (2002). Development and application of a human error identification tool for air traffic control. Applied Ergonomics, 33(4), 319.
24.
StantonN. A.SalmonP. M.WalkerG. H.BaberC.JenkinsD. P. (2005). Human factors methods: A practical guide for engineering and design. Aldershot, UK: Ashgate.
25.
StringfellowM. V. (2010). Accident analysis and hazard analysis for human and organizational factors. Doctor of Philosophy, Massachusetts Institute of Technology, Massachusetts.
26.
Whalley-LloydS. (1998). Reducing the impact of human error. The Safety & Health Practitioner, 16(5), 20.
27.
WilliamsJ. (1986). HEART - A proposed method for assessing and reducing human error. Paper presented at the 9th Advances in Reliability Technology Symposium, University of Bradford.
