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This paper deals with the production planning problem of a flexible manufacturing system (FMS). This problem is within the class of problems which are usually faced during the life cycle of FMS. There are basically two approaches used to solve this problem: analytical and simulation. The objective of this paper is to develop a methodology for determine the control policy for a given FMS by using the combination of both analytical and simulation approaches. The production rate control of a one-machine one-product system is presented to illustrate our approach. The contribution of the analytical part of the proposed model consists of generating a near-optimal controller based on the concept of an age-dependent hedging point policy. This sub-optimal policy is used as input of the simulation part and the improvement of operating conditions (control policies) achieved with a constant demand rate. The proposed model includes also a stochastic demand and lot sizes in production which consists of similar products batches with bulk arrivals. The robustness of the controller against both demand rates and production types has been validated. [ABSTRACT FROM AUTHOR]

This note addresses the production and maintenance control problem of a failure prone manufacturing system consisting of one machine and producing one part type. The machine is assumed to have three working states: good, average and bad, and a failure state. In the three working states, the machine can produce parts and some of these parts are rejected with a rate depending on the machine state. In the failure state, no part is produced. The state transition of the machine is governed by a continuous-time Markov process. The jump rates from average and bad states to the good state are the preventive maintenance rates and the one from failure state to good state is the corrective maintenance rate. The production rate and the maintenance rates are optimized. Index Terms--Maintenance control, manufacturing system, markov process, production rate.

This note deals with the class of continuous-time linear systems with Markovian jumps. We assume that jump rates are controlled. Our purpose is to study the jump linear quadratic (JLQ) regulator of the class of systems. The structure of the optimal controller is established. For a one-dimensional (1-D) system, an algorithm for solving the corresponding set of coupled Riccati equations of this optimal control problem is provided. Two numerical examples are given to show the usefulness of our results. Index Terms--Controlled jump Markov process, dynamic programming, jump linear quadratic regulator, jump linear system.

This note considers the suboptimal regulator design problem of jump linear system with time-multiplied performance index. The time-multiplied performance index is derived. A necessary condition for a control law with constant gain matrix to minimize the time-multiplied cost is established and a gradient-based algorithm to find a suboptimal control law is developed. Some numerical results are worked out to show the usefulness of the theoretical results. Index Terms--Jump linear system (JLS), suboptimal control law, time-multiplied performance index.