DOI: 10.5937/jaes14-9842
This is an open access article distributed under the CC BY-NC-ND 4.0 terms and conditions.
![Creative Commons License](https://licensebuttons.net/l/by-nc-nd/3.0/88x31.png)
Volume 14 article 353 pages: 54-60
Common practises for Quantitative Risk Assessment (QRA) include the estimation of frequencies of releases and related initial causes; these are a function of several parameters such as components failure rates, probabilities of human error, equipment damage and managerial factors. The availability of general values for such parameters from the literature simplifies the work of the risk analyst, but standardised results are provided, which unfortunately do not permit taking into consideration the plants specificity. The specificity of the establishment is defined through its management system, thus if managerial and organisational factors are neglected or not proper assessed, risk analysis for two identical establishments, characterised by totally different management systems, gives the same results and this appears absolutely unacceptable especially when risk analysis is used for risk-based decisions. This paper aims quantifying the effects of managerial and organisational variables on the frequency of losses of containment of pipeworks, by using a simple and flexible method developed by Milazzo and co-authors in 2010. Such a methodology has been tested on a new case-study and the results of the assessment have been evaluated from both the sensitivity and uncertainty points of view. An application has been shown with respect to the alkylation unit of a refinery.
Abrahamsen,
E. B.,Asche, F., Milazzo, M.F. (2013) An evaluation of the effects on safety of
using safety standards in major hazard industries. Safety Science, 59: 173-178.
Davoudian, K.,
Wu, J. S., Apostolakis, G., (1994) Incorporating organizational factors into
risk assessment through the analysis of work processes, Reliability Engineering
and System Safety, 45, 85-105.
Davoudian,
K., Wu, J. S., Apostolakis, G. E., (1994) The work process analysis (WPAM II),
Reliability Engineering and System Safety, 45(1-2), 107-125.
Embrey, D. E.,
(1992) Incorporating management and organization factors into probabilistic
safety assessment, Reliability Engineering and System Safety, 38(1-2), 199-208.
Flage, R., Aven,
T., (2009) Expressing and communicating uncertainty in relation to quantitative
risk analysis (QRA), Reliability & Risk Analysis: Theory &
Applications, 2(13), 9–18.
Flemish
Government, LNE Department Environment, Nature and Energy Policy Unit Safety Reporting
Division (2009), Handobook of failure frequencies (Appendix).
Gordon, R.
P. E., (1998) The contribution of human factors to accidents in the offshore
oil industry, Reliability Engineering and System Safety, 61, 95-108.
Healthy
& Safety Executive, (2012) Failure Rate and Event Data for use within Risk
Assessments. Report available at: http://www.hse.gov.uk/ (accessed on the 1st
December 2015).
Izquiedo-Rocha,
J. M., Sanchez-Perea M., (1994) Application of integrated safety assessment
methodology to emergencies procedures of SGTR of a PWR, Reliability Engineering
and System Safety, 45(1-2), 159-173.
Lees, F. P.,
(1996) Loss Prevention in the Process Industries, Elsevier, London.
Milazzo, M.
F., Aven, T., (2012) An extended risk assessment approach for chemical plants
applied to a study related to pipe ruptures, Reliability Engineering and System
Safety, 99, 183-192.
Milazzo, M.
F., Maschio, G., Uguccioni, G., (2010) The influence of risk prevention measures
on the frequency of failure of piping, International Journal of Performability
Engineering, 6(1), 19-33.
Milazzo, M.
F., Vianello, C, Maschio, G., (2015) Uncertainties in QRA: Analysis of losses of
containment from piping and implications on risk prevention and mitigation,
Journal of Loss Prevention in the Process Industry, 36, 98-107.
Modarres, M.,
Mosleh, A., Wreathall, J. A., (1992) Framework for assessing influence of
organization on plant safety, Reliability Engineering and System Safety,
38(1-2), 157-171.
Montmayeul,
R., Monsneron-Dupin, F., Llory, M., (1994) The managerial dilemma between the
prescribed task and the real activity of operator: some trends for research on
human factors, Reliability Engineering and System Safety, 45(1-2), 67-73.
Mosleh, A.,
Goldfeiz, E. B., (1995) An Approach for Assessment the Impact of Organizational
Factors on Risk. Report no. UMNE-95-003, University of Maryland.
Nivolianitou,
Z. S., Papazoglou, I. A., (1998) An auditing methodology for safety management
of the Greek process industry, Reliability Engineering and System Safety, 60,
185-197.
Øien, K., (2001)
A framework for the establishment of organizational risk indicators,
Reliability Engineering and System Safety, 74(2), 147-167.
Papazoglou,
I. A., Aneziris, O., (1999) On the quantification of the effects of organizational
and management factors in chemical, Reliability Engineering and System Safety,
15(1): 545-554.
Papazoglou,
I. A., Aneziris, O., Post, J. G., Ale, B. J. N., (2002) Technical modeling in
integrated risk assessment of chemical installations, Journal of Loss
Prevention in the Process Industry, 15(6), 545-554.
Papazoglou,
I. A., Bellamy, L. J., Hale, A. R., Aneziris, O., Post, J. G., Oh, J. I. H.,
(2003) I-Risk: development of an integrated technical and management risk
methodology for chemical installations,. Journal of Loss Prevention in the
Process Industry, 16(6), 575-591.
Patè-Cornell,
E. M., Murphy, D. M., (1996), Human and management factors in probabilistic risk
analysis: the SAM approach and observations from recent applications,
Reliability Engineering and System Safety, 53(2), 115-126.
Salvi, O.,
Debray, B., (2005) A global view on ARAMIS, a risk assessment methodology for
industries in the framework of the SEVESO II directive, Journal of Hazardous
Materials, 130(3), 187-199.
Schönbeck,
M., Rausand, M., Rouvroye, J., (2010) Human and organisational factors in the
operational phase of safety instrumented systems: A new approach, Safety Science,
48(3), 310-318.
Vianello C., Guerrini L., Maschio G., Mura A. (2014). Consequence analysis: comparison of methodologies under API standard and commercial software.
Chemical Engineering Transactions, 36, 511-516.