Hazard identification methods are important tools to verify that the system is able to operate according to specifications under different operating conditions. Unfortunately, many of the traditional methods are not adequate to capture possible dysfunctional behavior of complex systems that involve highly coupled parts, non-linear interactions and software-intensive functionalities. The rather recent method named system-theoretic process analysis (STPA) is one promising candidate to improve the coverage of hazard identification in complex and software-intensive system. Still, there is no guideline for utilizing system-theoretic process analysis output to evaluate the potential of loss, which is important for basis of decision-making about system configuration and equipment selection. The focus of this article is to place an interface between system-theoretic process analysis and reliability, availability and maintainability (RAM) analysis. The approach named STPA-RAM model is proposed to translate feedback control loops into stochastic Petri nets for discrete event simulation. The proposed approach is demonstrated with a simple case related to subsea design concept. The major conclusion is that STPA-RAM model extends the application of system-theoretic process analysis, while also improving and as such reducing completeness uncertainty and model uncertainty, associated with input data and information for reliability, availability and maintainability analysis.
BaiYBaiQ. Subsea engineering handbook. Boston, MA: Gulf Professional Publishing, 2010.
2.
LevesonN. Engineering a safer world: systems thinking applied to safety. Cambridge, MA: MIT Press, 2011.
3.
AbdulkhaleqAWagnerSLevesonN. A comprehensive safety engineering approach for software-intensive systems based on STPA. Proced Eng2015; 128: 2–11.
4.
RasmussenJ. Risk management in a dynamic society: a modelling problem. Safe Sci1997; 27(2): 183–213.
5.
SeligmannBJNémethEHangosKM, et al. A blended hazard identification methodology to support process diagnosis. J Loss Prevent Proc Ind2012; 25(4): 746–759.
MahajanHSBradleyTPasrichaS. Application of systems theoretic process analysis to a lane keeping assist system. Reliab Eng Syst Safe2017; 167: 177–183.
9.
KimHLundteigenMAHafverA, et al. Application of systems-theoretic process analysis to the isolation of subsea wells: opportunities and challenges of applying STPA to subsea operations. In: Proceedings of the offshore technology conference, Houston, TX, 30 April–3 May 2018. Houston, TX: Offshore Technology.
10.
SulamanSMBeerAFeldererM, et al. Comparison of the FMEA and STPA safety analysis methods–a case study. Softw Qual J2019; 27(1): 349–387.
11.
AbdulkhaleqALammeringDWagnerS, et al. A systematic approach based on STPA for developing a dependable architecture for fully automated driving vehicles. Proced Eng2017; 179(Suppl. C): 41–51.
12.
FaiellaGParandAFranklinBD, et al. Expanding healthcare failure mode and effect analysis: a composite proactive risk analysis approach. Reliab Eng Syst Safe2018; 169(Suppl. C): 117–126.
13.
NakaoHKatahiraMMiyamotoY, et al. Safety guided design of crew return vehicle in concept design phase using STAMP/STPA. In: Proceedings of the 5th IAASS conference, Versailles, France, 17–19 October 2011. Versailles, France: International Association for the Advancement of Space Safety (IAASS).
14.
RoksethBUtneIBVinnemJE. A systems approach to risk analysis of maritime operations. Proc IMechE, Part O: J Risk and Reliability2016; 231(1): 53–68.
YoungWLevesonN. Systems thinking for safety and security. In: Proceedings of the 29th annual computer security applications conference, New Orleans, LA, 9–13 December 2013, pp.1–8. New York: ACM.
17.
FriedbergIMcLaughlinKSmithP, et al. STPA-SafeSec: safety and security analysis for cyber-physical systems. J Inform Secur Appl2017; 34: 183–196.
18.
RodríguezMDíazI. A systematic and integral hazards analysis technique applied to the process industry. J Loss Prevent Proc Ind2016; 43: 721–729.
19.
WróbelKMontewkaJKujalaP. System-theoretic approach to safety of remotely-controlled merchant vessel. Ocean Eng2018; 152: 334–345.
20.
HafverAEldevikSJakopanecI, et al. Risk-based versus control-based safety philosophy in the context of complex systems. In: Safety & Reliability, Theory and Applications. Boca Raton, FL: CRC Press, 2017, pp. 217–225.
21.
RausandMHøylandA. System reliability theory: models, statistical methods, and applications. 2nd ed.Hoboken, NJ: John Wiley & Sons, Inc., 2004, pp.419–464.
22.
ISO/TR 12489:2013. Petroleum, petrochemical and natural gas industries—reliability modelling and calculation of safety systems. Geneva: International Electrotechnical Commission.
23.
InnalF. Contribution to modelling safety instrumented systems and to assessing their performance: critical analysis of IEC 61508 standard. PhD Thesis, University of Bordeaux, Bordeaux, 2008.
24.
IEC 61165:2006. Application of Markov techniques.
25.
IEC 62551:2012. Analysis techniques for dependability—petri net techniques.
26.
MarsanMABalboGChiolaG, et al. An introduction to generalized stochastic petri nets. Microelectron Reliab1991; 31(4): 699–725.
27.
RauzyA. Guarded transition systems: a new states/events formalism for reliability studies. Proc IMechE, Part O: J Risk and Reliability2008; 222(4): 495–505.
28.
SignoretJ-P. Dependability & safety modeling and calculation: petri nets. In: Proceedings of the 2nd IFAC workshop on dependable control of discrete systems, Bari, Italy, 10–12 June 2009. Bari, Italy IFAC, 2009, pp. 203–208.
29.
WangRZhengWLiangC, et al. An integrated hazard identification method based on the hierarchical colored petri net. Safe Sci2016; 88: 166–179.
30.
DirkSRené SebastianHJanW, et al. Integration of petri nets into STAMP/CAST on the example of Wenzhou 7.23 accident. IFAC Proc Vol2013; 46(25): 65–70.
31.
RoksethBUtneIBVinnemJE. Deriving verification objectives and scenarios for maritime systems using the systems-theoretic process analysis. Reliab Eng Syst Safe2018; 169(Suppl. C): 18–31.
32.
LevesonNThomasJ. STPA primer version 1. Cambridge, MA: MIT, 2013.
33.
BjergaTAvenTZioE. Uncertainty treatment in risk analysis of complex systems: the cases of STAMP and FRAM. Reliab Eng Syst Safe2016; 156(Suppl. C): 203–209.
34.
ThomasJ. Extending and automating STPA for requirements generation and analysis. PhD Dissertation, MIT, Cambridge, MA, 2013.
35.
BalboG. Introduction to generalized stochastic petri nets. In: BernardoMHillstonJ (eds) Formal methods for performance evaluation: SFM. Berlin: Springer, 2007, pp.83–131.
36.
SignoretJ-PDutuitYCacheuxP-J, et al. Make your petri nets understandable: reliability block diagrams driven petri nets. Reliab Eng Syst Safe2013; 113: 61–75.
DiazMJCStankoMSangeslandS. Exploring new concepts in subsea field architecture. In: Proceedings of the offshore technology conference, Houston, TX, 30 April–3 May 2018. Houston, TX: Offshore Technology.
39.
GRIF. Graphical interface for reliability forecasting. Mérignac: SATODEV, 2016.
40.
SINTEF. OREDA-Offshore and onshore reliability data. 6th ed. 2015.
41.
NUREG-1855:2009. Guidance on the treatment of uncertainties associated with PRAs in risk-informed decision making.
42.
BernerCFlageR. Strengthening quantitative risk assessments by systematic treatment of uncertain assumptions. Reliab Eng Syst Safe2016; 151: 46–59.
43.
IEC 61508:2010. Functional safety of electrical/electronic/programmable electronic safety related systems (parts 1–7).
