Optimally maintaining a multi-state system with limited imperfect preventive repairs

In this paper, the optimal maintenance policy for a multi-state system with no observation is considered. Different from most existing works, only a limited number of imperfect preventive maintenance actions can be performed between two successive replacements. Assume that the system's deterioration state cannot be observed during its operation expected after each replacement, and it evolves as a discrete-time Markov chain with a finite state space. After choosing the information state as state variable, the problem is then formulated as a Markov decision process over the infinite time horizon. In order to increase the computational efficiency, several key structural properties are developed by minimising the total expected cost per unit time. The existence of the optimal threshold-type maintenance policy is proved and the monotonicity of the threshold is obtained. Finally, a numerical example is given to illustrate the optimal policy.     

Optimal age-replacement time with minimal repair based on cumulative repair cost limit and random lead time

In this article, we consider an age-replacement model with minimal repair based on a cumulative repair cost limit and random lead time for replacement delivery. A cumulative repair cost limit policy uses information about a system's entire repair cost history to decide whether the system is repaired or replaced; a random lead time models delay in delivery of a replacement once it is ordered. A general cost model is developed for the average cost per unit time based on the stochastic behaviour of the assumed system, reflecting the costs of both storing a spare and of system downtime. The minimum-cost policy time is derived, its existence and uniqueness is shown, and structural properties are presented. Various special cases are included. Because the framework and analysis are general, the proposed model extends several existing results. Finally, a numerical example is provided for illustration.     

Optimal pricing and lot-sizing for perishable inventory with price and time dependent ramp-type demand

Product perishability is an important aspect of inventory control. To minimise the effect of deterioration, retailers in supermarkets, departmental store managers, etc. always want higher inventory depletion rate. In this article, we propose a dynamic pre- and post-deterioration cumulative discount policy to enhance inventory depletion rate resulting low volume of deterioration cost, holding cost and hence higher profit. It is assumed that demand is a price and time dependent ramp-type function and the product starts to deteriorate after certain amount of time. Unlike the conventional inventory models with pricing strategies, which are restricted to a fixed number of price changes and to a fixed cycle length, we allow the number of price changes before as well as after the start of deterioration and the replenishment cycle length to be the decision variables. Before start of deterioration, discounts on unit selling price are provided cumulatively in successive pricing cycles. After the start of deterioration, discounts on reduced unit selling price are also provided in a cumulative way. A mathematical model is developed and the existence of the optimal solution is verified. A numerical example is presented, which indicates that under the cumulative effect of price discounting, dynamic pricing policy outperforms static pricing strategy. Sensitivity analysis of the model is carried out.     

Computation of the failure probability of deteriorating structural systems

Structural system deterioration is one of the least attended topics in time-dependent structural reliability analysis. There are basically two types of problems in structural deterioration analysis; one is the need for models to simulate the behaviour of deteriorating structural material. This will be done through case by case study in this paper. The other problem is that when both the applied loads and resistance vary with time, the current methods to generate limit state functions for the structural system need validating. To avoid this problem, an alternative formulation for time-dependent reliability is proposed, where the reliability analysis of a deteriorating structural system is based on the reliability of its structural members, which constitute a failure sequence for the structure. The advantage of the proposed approach is that it has effectively obviated the use of global limit state functions and that it is applicable to structures subject to various types of loads and with different structural material properties. An application example is given to illustrate the computation procedure.     

Joint production,inspection and maintenance control policies for deteriorating system under quality constraint

This paper studies the integration of production, sampling inspection and age-based maintenance planning for an unreliable production system subject to gradual deterioration. The deterioration process of the production unit has a twofold effect on its reliability and product quality. To mitigate the effects of such deterioration, an age-based major maintenance can be conducted, which denotes a perfect repair that restores the production unit to initial conditions. The quality control is performed through a sampling plan that inspects a fraction of the parts produced. The problem further considers that the optimal decision must be determined under a constraint on the outgoing quality required by the final customer. In this domain, standard sampling procedures are applicable only to production process that are statistically stable and under control. Nevertheless, such sampling plans disregard the interaction with production management and maintenance issues and they do not consider the effects of deterioration. In this paper a new joint control policy considering the interactions between production-quality and maintenance is proposed. A stochastic mathematical model is developed through specialized optimization techniques to solve such quality constrained problem. Numerical examples are provided to illustrate the usefulness of the proposed approach and to study the interactions between production-quality and maintenance strategies. An extensive sensitivity analysis and a comparative study are conducted to illustrate the effectiveness of the obtained joint control policy.     

Optimal maintenance policy for equipment subject to random deterioration and random failure A modern control theory approach

The stochastic version of Pontryagin's maximum principle is applied to determine an optimal maintenance policy of equipment subject to random deterioration. The deterioration of the equipment with age is modelled as a random process. Next the model is generalized to include random catastrophic failure of the equipment. The optimal maintenance policy is derived for two special probability distributions of time to failure of the equipment, namely, exponential and Weibull distributions Both the salvage value and deterioration rate of the equipment are treated as state variables and the maintenance as a control variable. The result is illustrated by an example.     

A stochastic control algorithm for systems with control dependent plant and measurement noise

The problem of control of a stochastic system with control dependent noise is investigated. Both the system driving noise and system measurement noise have control dependent terms. The approximation of neglecting higher order terms in the control is introduced in the derivation of the a posteriori conditional covariance matrices of the system state. These approximate conditional covariance matrices are used in a stochastic dynamic programming algorithm to obtain a linear feedback law. The control feedback matrices multiplying the estimates for system state are not those of the equivalent deterministic system and the separation theorem in its usual form does not apply to this class of problems. The control policy given by the algorithm reduces to the optimal control policy in two cases in which the optimal control is known. These are the case of no control dependent noise and the case of no measurement noise. A third order numerical example is investigated to illustrate the nature of the algorithm.     

On quadratic optimization in distributed parameter systems

Systems described by parabolic partial differential equations are formulated as ordinary differential equations in a Hilbert space. Quadratic cost criteria are then formulated as inner products on this Hilbert space. Existence of an optimal control is proved both in the case where the system operator is "coercive" and in the case where the system operator is the infinitesimal generator of a semigroup of operators. The optimal control is given by a linear state feedback law in which the feedback operator is shown to be the bounded positive self-adjoint solution of a nonlinear operator equation of the Riccati type.     

Multi-item-multi-plant inventory control of production systems with shortages/backorders

A multi-item model of a production-inventory system incorporating deterioration, shortages and capacity/budget constraints is considered. An optimal control policy for the model is developed using linear quadratic (LQ) theory for the case of deterministic demands. The problem of controlling large-scale production-inventory facilities is also considered, and the interaction prediction method is used to develop optimal policies. Results of simulations show that using the developed policy, any desired inventory levels can be maintained while minimizing costs and satisfying demand without violating capacity constraints.     

Adaptive predictive control policy for nonlinear stochastic systems

The problem of optimal adaptive predictive control for nonlinear stochastic systems is considered. A classification of various suboptimal approaches is given. A new approximation for the probability measure for the extended state of the system is suggested to derive a new suboptimal control law. It is assumed for this approximation that the system operates in closed-loop feedback mode for one part of the extended state vector and in open feedback loop mode for the other part of this vector. The certainty equivalence (CE) assumption is used only for the first part of the extended state vector. An analytical comparison for the suggested control policy shows its superiority in control quality compared with that of the open-loop optimal control policy in the case of an exactly observed first part of the extended state vector. The upper bound of the performance index is determined for this case. The suggested control policy has a simple form for linear systems with unknown parameters. A simulated example is used to demonstrate the potential of the suggested method and its superiority over the usually applied CE policy     

A Dynamic Inspection Model for Wearing Production Systems

The aim of this paper is to correlate the deterioration process of a production system with the items control process and, as a consequence, with the equipment inspection policy. The objective is to consider how the wear of the manufacturing system influences the values of the control process parameters and how these parameters have to be changed in accordance with the need to maintain optimal (working) conditions. Adopting a Weibull failure-time distribution, it is shown how these parameters must be changed (at different times t ) in order to maintain optimal working conditions. To test the inspection model, a weighted cost function dependent on the time loss for the production of defective units and for the production shut-down (in order to make an inspection to control the state of the system) is developed.     

Optimal control of quasi-linear systems of the diffusion type under incomplete information on the state

The problem of optimal control for a stochastic state-linear control system with coefficients of diffusion depending on the vector of state and control with quadratic criterion of the control quality is investigated. We assume that only a part of components of the state vector of the system are measured. On the basis of the Lyapunov-Lagrange method, we propose a method for searching for an optimal control strategy depending on known components of the state vector. The problem of synthesis of a control is reduced to solving a boundary-value problem for a system of ordinary differential equations of the Riccati type. Several model examples with different awareness about the system state are analyzed.     

Control of singularly perturbed hybrid stochastic systems

We study a class of optimal stochastic control problems involving two different time scales. The fast mode of the system is represented by deterministic state equations whereas the slow mode of the system corresponds to a jump disturbance process. Under a fundamental “ergodicity” property for a class of “infinitesimal control systems” associated with the fast mode, we show that there exists a limit problem which provides a good approximation to the optimal control of the perturbed system. Both the finite- and infinite-discounted horizon cases are considered. We show how an approximate optimal control law can be constructed from the solution of the limit control problem. In the particular case where the infinitesimal control systems possess the so-called turnpike property, i.e., characterized by the existence of global attractors, the limit control problem can be given an interpretation related to a decomposition approach     

Optimal control structure of an unreliable manufacturing systemwith random demands

This paper considers an unreliable manufacturing system with random processing times and random product demands. The system can produce many part types and its total capacity is constrained by a fixed constant. The objective is to find an optimal service-rate allocation policy between different part types by minimizing the expected discounted inventory and backlog cost. Structural properties of the optimal control policy are investigated. It is shown that the optimal policy is of a switching structure. For producing a one part type case, the optimal control is a threshold policy. For producing a two part types case, the optimal control can be described by three monotone switching curves and its asymptote properties are derived. Numeric examples are given to illustrate the results     

Optimal control of a queueing system with two interacting servicestations and three classes of impatient tasks

The problem of task selection and service priority is studied for a queueing network with two interacting service stations and three classes of impatient tasks. By using stochastic dynamic programming, a functional equation for the optimal, state-dependent priority assignment policy is derived. Properties of the optimal cost-to-go functions and the optimal policy are established through inductive proofs. It is shown that the optimal policy is governed by two switching surfaces in the three-dimensional state space (one dimension for each task class). For the infinite-time-horizon case, the optimal policy is shown to be stationary. In this case, the optimal cost-to-go function and switching surfaces are obtained numerically by using the overrelaxed Gauss-Seidel method. Sensitivities of the optimal policy with respect to key system parameters are also investigated     

A condition-based maintenance policy for a production system under excessive environmental degradation

In this paper a condition-based maintenance model is proposed for a single-unit system of production of goods and services. The system is subject to random deterioration which impacts not only the product quality but also the environment. We assume that the environment degrades whenever a specific level of system deterioration is reached. The proposed maintenance model aims to assess the degradation in such a way to reduce the deterioration of the environment. To control this deterioration, inspections are performed and after which the system is preventively replaced or left as it is. Preventive replacement occurs whenever the level of the system degradation reaches a specific level threshold. The objective is to determine optimal inspection dates which minimize the average total cost per unit of time in the infinite horizon. Cost function is composed of inspection and maintenance costs in addition to a penalty cost due to environmental deterioration. The maintenance optimization model is formally derived. On the basis of Nelder–Mead method, inspection dates as optimal solutions are computed. A numerical example is provided to illustrate the proposed maintenance model.     

Optimal replenishment decision in an EPQ model with defective items under supply chain trade credit policy

The traditional inventory of the economic order quantity model assumes perfect items in an ordered lot and an infinite replenishment rate. However, such conditions are rare in actual production environments. Additionally, most studies of this problem have only considered suppliers offering the wholesaler a grace period. In practice, wholesalers often extend a fixed credit period to downstream customers as well. This study therefore proposes a production model for a lot-size inventory system with finite production rate and defective quality under the condition of two-level trade credit policy and the condition that defective items involve both imperfect quality and scrap items. Thus, optimal wholesaler replenishment decisions can be determined for defective items under two-level trade credit policy in the EPQ framework. Four theorems for determining the optimal cycle time and the results in this study can be deduced as a special case of earlier models. Finally, illustrative examples are provided to verify the theoretical results.     

Optimal hedging point control for a failure-prone manufacturing system

This paper considers a manufacturing system with multiple operational modes producing one part type. The part processing time at each operational mode is exponentially distributed and its rate is controllable. The demand arrival is random and described by a Poisson process. By minimizing an infinite-horizon discounted expected cost function, the optimal service rate control is derived. It is proved that the optimal policy is of a hedging point structure by examining the properties of the optimal cost function such as convexity, monotonicity and asymptotic behaviours. The hedging points at different operational modes can be ordered according to their production capacities. The relationships of the hedging points with some system parameters are presented. These structural properties of the optimal control policy are helpful in finding simple and realistic suboptimal policies for practical manufacturing systems. A numerical example is given to demonstrate our results.     

Control Policies of an M/G/1 Queueing System with a Removable and Non-reliable Server

This paper considers a single non-reliable server in the ordinary M/G/1 queueing system whose arrivals form a Poisson process and service times are generally distributed. We also study a single removable and non-reliable server in the controllable M/G/1 queueing systems operating under the N policy, the T policy and the Min( N , T ) policy. It is assumed that the server breaks down according to a Poisson process and the repair time has a general distribution. In three control policies, we show that the probability that the server is busy in the steady-state is equal to the traffic intensity. It is shown that the optimal N policy and the optimal Min( N , T ) policy are always superior to the optimal T policy. Sensitivity analysis is also investigated.     

Optimal (s,S) policies with delivery time guarantees for manufacturing systems with early set-up

We consider optimal (s, S) policies with delivery time guarantees for production planning in one-machine manufacturing systems with early set-up. The machine produces one type of product and delivery time guarantee is offered to the customers for each unit of ordered product. The inter-arrival time of the demand and the processing time for one unit of product are assumed to be exponentially distributed. In a (s, S) policy, the machine will shut down when an inventory level of S is attained and once the inventory level drops to s, the machine will re-start. A set-up time is required for the machine. We model the set-up by the exponential distribution. We obtained an analytical form of the steady state probability distribution for the inventory levels derived. The average profit of the system can be written in terms of this probability distribution. Hence the optimal (s, S) policy can be obtained by varying different possible values of s and S.