Df. Percy et al., SETTING PREVENTIVE MAINTENANCE SCHEDULES WHEN DATA ARE SPARSE, International journal of production economics, 51(3), 1997, pp. 223-234
When new production lines are established,little information is availa
ble about their reliability. The evaluation of such systems is a learn
ing process and knowledge is continually updated as more information b
ecomes available. This paper considers stochastic models when data are
sparse, with emphasis on preventive maintenance intervention to avoid
system failure. Bayesian methods are adopted, leading to optimal stra
tegies under the model assumptions. This approach also includes prior
knowledge about the manufacturing process and similar systems. Our app
roach is a first reconnaissance into a new held, exemplary of ways to
solve these problems, rather than an algorithm that can be readily app
lied.