Emin Li

Near-Optimal Production and Maintenance Control for Failure Prone Production Systems with Demand Uncertainty

Under the circumstances that the demand is uncertain, furthermore, the demand sometimes cannot be satisfied by the production, the paper studies the production and maintenance control problem of failure prone production systems. For the hybrid system, a so-called double level hedging point control policy considering purchasing extra production or maintenance capacity is presented, which has strong dynamic characteristics. By the method that studies the problem from over the finite horizon to over the infinite horizon, meanwhile, utilizing a decomposition method, the corresponding hedging points are obtained respectively. The numerical comparison specifies and to some extent testifies the method.

A Scheduling Model of Unreliable Manufacturing Systems on Receding Horizon

An unreliable manufacturing system is examined. The system can produce several types of products. A setup (with setup time or cost or both) is considered when the production is switched from one type of products to another. The decision variables are a sequence of setups and the production plan. After a more straightforward necessary condition and a necessary and sufficient condition for the optimality of the just-in-time (JIT) control policy were presented respectively, based on the hedging point control policy and the idea of JIT (just-in-time), a new real-time receding horizon scheduling algorithm is presented. Numerical results are also presented.

A new extended system aggregation method of hybrid production lines

Hybrid production lines with unreliable machines and buffers are examined. Different from traditional aggregation method, the unreliable buffers are originally considered and a more general aggregation method is offered, in which not only the unreliable buffers are considered, but also the probabilities of system states are obtained by a discrete model rather than the continuous flow model of unreliable manufacturing systems. The solution technique is offered to get the system sates probabilities. The method advances the traditional system aggregation techniques. Numerical results specify the extended aggregation method and also show that the unreliable limited buffers have a strong impact on the efficiency of the production lines.