Abstract: In this paper, the joint optimization of the
economic manufacturing quantity (EMQ), safety stock level,
and condition-based maintenance (CBM) is presented for a partially
observable, deteriorating system subject to random failure. The
demand is stochastic and it is described by a Poisson process.
The stochastic model is developed and the optimization problem
is formulated in the semi-Markov decision process framework. A
modification of the policy iteration algorithm is developed to find
the optimal policy. A numerical example is presented to compare
the optimal policy with the policy considering zero safety stock.
Abstract: In this paper, we present a new maintenance model
for a partially observable system subject to two failure modes,
namely a catastrophic failure and a failure due to the system
degradation. The system is subject to condition monitoring and the
degradation process is described by a hidden Markov model. A
cost-optimal Bayesian control policy is developed for maintaining
the system. The control problem is formulated in the semi-Markov
decision process framework. An effective computational algorithm is
developed, illustrated by a numerical example.
Abstract: In this paper, we present a maintenance model of a
two-unit series system with economic dependence. Unit#1 which is
considered to be more expensive and more important, is subject to
condition monitoring (CM) at equidistant, discrete time epochs and
unit#2, which is not subject to CM has a general lifetime distribution.
The multivariate observation vectors obtained through condition
monitoring carry partial information about the hidden state of unit#1,
which can be in a healthy or a warning state while operating. Only the
failure state is assumed to be observable for both units. The objective
is to find an optimal opportunistic maintenance policy minimizing
the long-run expected average cost per unit time. The problem
is formulated and solved in the partially observable semi-Markov
decision process framework. An effective computational algorithm
for finding the optimal policy and the minimum average cost is
developed, illustrated by a numerical example.
Abstract: Managing the emergency situations at the Emergency
Staff requires a high co-operation between its members and their fast
decision making. For these purpose it is necessary to prepare Emergency Staff members adequately. The aim of this paper is to
describe the development of information support that focuses to
emergency staff processes and effective decisions. The information
support is based on the principles of process management, and
Process Framework for Emergency Management was used during the
development. The output is the information system that allows users
to simulate an emergency situation, including effective decision making. The system also evaluates the progress of the emergency
processes solving by quantitative and qualitative indicators. By using
the simulator, a higher quality education of specialists can be achieved. Therefore, negative impacts resulting from arising emergency situations can be directly reduced.