On the optimization of opportunistic maintenance activities

• Maintenance is a source of large costs; in the EU the maintenance costs amountto between 4% and 8% of the total sales turnover. Opportunistic maintenance is anattempt to lower the maintenance cost by considering the failure of onecomponent as an opportunity to replace yet non-failed components in order toprevent future failures. At the time of failure of one component, a decision is to be made on which additional components toreplace in order to minimize the expected maintenance cost over a planningperiod.This thesis continues the work of Dickman et. al. (1991) and Andreasson (2004) on the opportunistic replacement problem. In Paper I, we show thatthe problem with time-dependent costs is NP-hard and present a mixed integerlinear programming model for the problem. We apply the model to problems withdeterministic and stochastic component lives with data originating from theaviation and wind power industry. The model is applied in a stochastic settingby employing the expected values of component lives. In Paper II, a first steptowards a stochastic programming model that considers components with uncertain lives istaken by extending the problem to allow non-identical lives for component individuals.This problem is shown to be NP-hard even with time-independent costs. We present amixed integer linear programming model of the problem. The solution time of the model is substantially reduced compared to the model presented in Andreasson (2004). In Paper III, we then study the opportunisticreplacement problem with uncertain component lives and present a two-stagestochastic programming approach. We present a deterministic equivalent model anddevelop a decomposition method. Numerical studies on the same data as in Paper I from the aviation and wind power industry show that the stochastic programming approachproduces maintenance decisions that are on average less costly than decisions obtained from simple maintenance policies and the approach used in Paper I. The decomposition method requires less CPU-time than solving the deterministic equivalent on three out of four problems.

Ämnesord

NATURVETENSKAP  -- Matematik -- Beräkningsmatematik (hsv//swe)

NATURAL SCIENCES  -- Mathematics -- Computational Mathematics (hsv//eng)

Nyckelord

mixed integer linear programming

stochastic programming

complexity theory

mixed integer linear programming; complexity theory; stochastic programming

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