The technology of production, transportation, and processing of oil and gas involves various hazardous processes. To mitigate the risk that these processes pose, the technological solutions work closely with the automated control and safety systems. The design and organisation of maintenance for the automated safety instrumented systems (SIS) have a significant bearing on the overall safety of operations in this industry. Over the past few decades, many hydrocarbon resources have been discovered in unconventional environments, such as remote, offshore, and arctic locations. Transportation of engineering personnel to these remote locations and back, and thereby, the organisation of the shift work poses additional challenges for the petroleum sector. Under such circumstances, the workforce-related costs play a considerable role in the overall cost of the technological solution and thereby the decisions regarding the workforce organisation should be addressed in the framework of evaluating and choosing the appropriate safety measures. That is why the research presented in this paper aims to address the lifecycle of the technological solution integrating the problems of SIS design, maintenance planning, and employee scheduling into a single decision-making framework to optimise the set of technical and organisational safety measures inherent in the SIS. The performance and maintenance of the SIS are described with a Markov model of device failures, repairs and technological incidents occurrence. The employee scheduling part of the mathematical model utilises the set-covering formulation of maintenance crews taking particular trips. A black-box optimisation algorithm is used to find reasonable solutions to the integrated problem of engineering design and workforce planning. The decisions include the choices of the components and structures for the safety system, the facility overhaul frequencies, the maintenance personnel size, as well as the schedules of trips and shifts for the crews.
If the inline PDF is not rendering correctly, you can download the PDF file here.
van den Bergh, J., Beliën, J., De Bruecker, P., Demeulemeester, E., & De Boeck, L. (2013). Personnel scheduling: A literature review. European Journal of Operational Research, 226(3), 367-385. doi: 10.1016/j.ejor.2012.11.029
Bourmistrov, A., Mellemvik, F., Bambulyak, A., Gudmestad, O., Overland, I., & Zolotukhin A. (Eds.). (2015). International Arctic Petroleum Cooperation: Barents Sea scenarios. New York, United States: Routledge.
Bukowski, J. (2006). Incorporating process demand into models for assessment of safety system performance. Reliability and Maintainability Symposium 2006, RAMS’06 Annual, 577-581. IEEE. doi: 10.1109/RAMS.2006.1677435
Castillo-Salazar, J. A., Landa-Silva, D. & Qu, R. (2016). Workforce scheduling and routing problems: literature survey and computational study. Annals of Operations Research, 239(1), 39-67. doi: 10.1007/s10479-014-1687-2
Centre for Chemical Process Safety (CCPS). (2010). Guidelines for Safe Process Operations and Maintenance. New York, United States: John Wiley & Sons.
Closed Joint-Stock Company Scientific Technical Center of Industrial Safety Problems Research (STC Industrial safety). (2014). Federal law On industrial safety of hazardous production facilities. Moscow, Russia: STC Industrial safety CJSC.
Dantzig, G. B. (1954). Letter to the editor - A comment on Edie's “Traffic delays at toll booths”. Journal of the Operations Research Society of America, 2(3), 339-341. doi: 10.1287/opre.2.3.339
Helber, S., & Henken, K. (2010). Profit-oriented shift scheduling of inbound contact centers with skills-based routing, impatient customers, and retrials. OR Spectrum, 32(1), 109-134. doi: 10.1007/s00291-008-0141-8
International Electrotechnical Commission (IЕC). (1997). 61508 Functional safety of electrical / electronic / programmable electronic safety-related systems. Geneva, Switzerland: IEC.
International Electrotechnical Commission (IЕC). (2003). 61511 Functional safety – safety instrumented system for the process industry sector. Geneva, Switzerland: IEC.
Jin, H., Lundteigen, M. A., & Rausand, M., (2011). Reliability performance of safety instrumented systems: A common approach for both low-and high-demand mode of operation. Reliability Engineering & System Safety, 96(3), 365–373. doi: 10.1016/j.ress.2010.11.007
Kuo, W., & Zuo, M.J. (2003). Optimal reliability modeling. Principles and applications. Hoboken, New Jersey, United States: John Wiley & Sons.
The Norwegian Oil and Gas Association. (2001). 070 – Application of IEC61508 and IEC61511 in the Norwegian Petroleum Industry, Sandnes, Norway: Norwegian Oil and Gas.
Redutskiy, Y. (2017). Optimization of safety instrumented system design and maintenance frequency for oil and gas industry processes. Management and Production Engineering Review, 8(1), 46-59. doi: 10.1515/mper-2017-0006.