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2017 | 8 | nr 1 | 46--59
Tytuł artykułu

Optimization of safety instrumented system design and maintenance frequency for oil and gas industry processes

Autorzy
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Oil and gas industry processes are associated with significant expenditures and risks. Adequacy of the decisions on safety measures made during early stages of planning the facilities and processes contributes to avoiding technological incidents and corresponding losses. Formulating straightforward requirements for safety instrumented systems that are followed further during the detailed engineering design and operations is proposed, and a mathematical model for safety system design is introduced in a generalized form. The model aims to reflect the divergent perspectives of the main parties involved in oil and gas projects, and, therefore, it is formulated as a multi-objective problem. Application of black box optimization is suggested for solving real-life problem instances. A Markov model is applied to account for device failures, technological incidents, continuous restorations and periodic maintenance for a given process and safety system configuration. This research is relevant to engineering departments and contractors, who specialize in planning and designing the technological solution.(original abstract)
Rocznik
Tom
8
Numer
Strony
46--59
Opis fizyczny
Twórcy
  • Molde University College, Norway
Bibliografia
  • International Electrotechnical Commission (IEC), 61511 Functional safety - safety instrumented system for the process industry sector, IEC, Geneva, Switzerland, 2003.
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  • CCPS (Centre for Chemical Process Safety), Guidelines for Safe Process Operations and Maintenance, John Wiley & Sons, New York, 2010.
  • HSE (Health and Safety Executive), Out of Control, 2nd´ ld., HSE Books, UK, 2003.
  • International Electrotechnical Commission (IEC), 61508 Functional safety of electrical/electronic/programmable electronic safety-related systems, IEC, Geneva, Switzerland, 1997.
  • Bukowski J., Using Markov models to compute probability of failed dangerous when repair times are not exponentially distributed, in RAMS'06 Annual Reliability and Maintainability Symposium, IEEE, 273-277, 2006.
  • Mechri W., Simon C., Ben Othman K., Switching Markov chains for a holistic modeling of SIS unavailability, Reliability Engineering & System Safety, 133, 212-222, 2015.
  • Hauge S., Lundteigen M.A., Hokstad P., Håbrekke S., Reliability prediction method for safety instrumented systems. PDS method handbook, 2010 edition, SINTEF, Trondheim, 2010.
  • Andrews J.D., Ericson C.A., Fault tree and Markov analysis applied to various design complexities, 18th International System Safety Conference (ISSC), 2000.
  • Goble W.M., Control Systems Safety Evaluation & Reliability, 3rd ed., Research Triangle Park: ISA, 2010.
  • Hellmich M., Berg H.P., Markov analysis of redundant standby safety systems under periodic surveillance testing, Reliability Engineering & System Safety, 133, 48-58, 2015.
  • Torres-Echeverria A.C., Martorell S., Thompson H.A., Modelling and optimization of proof testing policies for safety instrumented systems, Reliability Engineering & System Safety, 94, 838-854, 2009.
  • Kuo W., Optimal Reliability Design: Fundamentals and Applications, Cambridge University Press, Cambridge, 2001.
  • Kuo W., Zuo M.J., Optimal reliability modeling. Principles and applications, John Wiley & Sons, Hoboken, New Jersey, 2003.
  • Martorell S., Sánchez A., Carlos S., and Serradell V., Alternatives and challenges in optimizing industrial safety using genetic algorithms, Reliability Engineering & System Safety, 86, 1, 25-38, 2004.
  • Torres-Echeverria A.C., Modelling and optimization of safety instrumented systems based on dependability and cost measures, PhD thesis, University of Sheffield, 2009.
  • Bukowski J., Incorporating process demand into models for assessment of safety system performance, RAMS'06 Annual Reliability and Maintainability Symposium, IEEE, 577-581, 2006.
  • Shershukova K.P., Modelling Safety System Integrated into PCS of Gas Condensate Processing, [in Russian: Modelirovanie sistemy bezopasnosti v sostave ASU TP pererabotki gazokondensata], Dissertation abstract, Moscow, 2013.
  • The Norwegian Oil and Gas Association, 070 - Application of IEC61508 and IEC61511 in the Norwegian Petroleum Industry, Norwegian Oil and Gas, Sandnes, 2001.
  • Closed Joint-Stock Company Scientific technical center of industrial safety problems research, Federal law On industrial safety of hazardous production facilities, STC Industrial safety CJSC, Moscow, 2014.
  • Deb K., Multi-Objective Optimization using Evolutionary Algorithms, John Wiley & Sons, Chichester, 2001.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171517330

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